I love data because when you put the right numbers next to each other, they tell a story. And the story AI is telling us about marketing right now is fascinating.

McKinsey & Company's 2026 State of AI research found that 80% of respondents say AI has improved individual productivity, and about half say it helps them make better decisions. Yet only 37% report a positive impact on organizational EBIT.

That's quite a gap. I don't think we have an AI adoption problem anymore. We have an AI application problem.

And after working with AI every day, particularly in AI SDR programs, I'm beginning to think AI is doing something even more valuable than making marketing faster: It's exposing what was already wrong with our go-to-market strategy.

Faster Bad Marketing Is Still Bad Marketing

Salesforce's 2026 State of Marketing research makes the point beautifully. Seventy-five percent of marketers have adopted AI. Yet 84% admit they're still running generic campaigns. At the same time, 83% say customers increasingly expect two-way conversations.

We have more technology capable of personalization than ever before, yet we're still sending generic marketing. That's not an AI problem. That's a strategy, data and workflow problem.

AI can write 100 personalized emails faster than I can write one. But if we don't understand the ICP, the buyer, the business problem or why that person should care, we haven't created personalization. We've created 100 different versions of irrelevant. Now we can send them faster. Progress?

Our AI SDR Work Is Teaching Us the Same Thing

When people first see an AI SDR platform, it's easy to focus on what it can automate: research, personalization, sequences, engagement and follow-up. But the technology isn't the hard part.

The hard questions haven't changed. Who are we trying to reach? What problem are we solving? Why should they care now? What signals indicate interest? What content helps? And when should automation stop and a human step in?

Give AI a strong ICP, good data, clear positioning, relevant content and thoughtful guardrails, and it can scale a good go-to-market motion. Give it a fuzzy ICP, mediocre positioning and generic content, and it can produce mediocre marketing at breathtaking speed.

AI didn't create the problem. It scaled it. This is one of the biggest lessons I think we're learning together as marketers. There is no 20-year AI marketing playbook sitting in someone's drawer. We're building it while we're using it.

And Guess What? Buyers Have AI Too.

This is the part of the conversation I find particularly interesting.

I've long respected Khali Henderson , and I've been following the work she is doing with the new AI Revenue Institute. Their research looks at the other side of this equation: how AI is changing B2B buyer behavior.

AIRI surveyed 521 active B2B purchasers and purchasing influencers. Sixty-two percent use AI to fact-check sales claims against public sources. Fifty-four percent use it to build vendor comparison matrices, and 56% use AI to determine what they should be looking for when selecting a provider.

Even more interesting, 56% said they had removed a vendor after AI uncovered a gap between the vendor's claims and its capabilities. Think about that for a minute.

We've spent enormous amounts of time asking, "How can we use AI to reach the buyer?" Maybe we also need to ask, "What happens when the buyer uses AI to investigate us?"

Your buyer can ask whether your claims are true, how you compare with competitors, what questions they should ask you and what alternatives they haven't considered. AI isn't only making sellers smarter. It's giving buyers a better BS detector.

AI Visibility Is Only the Beginning

This is why AI visibility can't become another checkbox on the marketing plan. Yes, you want your company to appear when someone asks an AI platform about your category. But showing up is only the beginning. What happens when AI starts digging?

Does your website support what your salesperson just said? Do credible third parties support your claims? Does your content demonstrate actual expertise? Does your positioning match what customers say about you?

This connects directly to the work we're doing around ICP, content, AI visibility and AI SDRs. They aren't separate activities anymore. They're becoming pieces of one connected revenue system. And that changes what creates competitive advantage.

Everyone will have access to AI. The advantage will come from what we give it: customer knowledge, proprietary insights, accurate data, experience, a real point of view and human judgment.

The model isn't the moat. Your context is.

More Isn't the Goal. Better Is.

There are real downsides to this transition. McKinsey found that 47% of midlevel managers and individual contributors reported at least one negative effect associated with AI use, compared with 31% of executives and senior managers. Those included stress, mental fatigue, concerns about critical thinking and pressure to take on more work.

Saving someone ten hours doesn't improve their job if we immediately reward them with fifteen more hours of work. We're also creating a sameness problem. When everyone uses similar models to create similar content from similar information, the internet gets very efficient at producing beige.

That's why human experience becomes more important, not less. Your perspective matters. Your customer's actual words matter. Your original data matters. Your stories matter. Relationships matter.

AI can help find the right person and perhaps start the right conversation. It cannot manufacture trust.

The Bigger Opportunity Is Learning

This may be where AI becomes most valuable to marketers. Not content. Feedback.

We can see much faster which personas engage, which industries respond, what objections emerge, which messages get ignored, what content gets consumed and where people disappear.

Instead of launching a campaign, waiting 90 days and conducting the marketing equivalent of an autopsy, we can learn while the market is responding. That turns marketing from a production engine into a learning system. And perhaps that's the real transformation.

McKinsey found that the organizations getting the greatest value from AI aren't simply handing employees more tools. They're redesigning how work gets done. Nearly three-quarters of its AI high performers report fundamentally redesigning workflows, compared with about one-quarter of other organizations.

That should be our goal: Not more AI. Better marketing because of AI.

AI can make us dramatically more productive, but productivity doesn't guarantee profitability. AI can personalize at scale, but it can't compensate for bad data or a weak understanding of the customer. AI SDRs can expand what sales and marketing teams can accomplish, but they don't eliminate the need for strategy, content, judgment or human handoff.

And while we're learning how to use AI to understand buyers, buyers are learning how to use AI to understand us. I think that may be the biggest change of all.

The winners won't be the companies producing the most AI-generated content or sending the most personalized emails. They'll be the companies that are easiest to understand, easiest to validate, genuinely relevant to the right customers and consistent everywhere a buyer, or their AI assistant, looks.

AI can make marketing faster. Our job is to make sure it also makes marketing better.

A few weeks ago, I wrote about why AI in sales and marketing is not “set it and forget it.”

This is the story that usually comes next.

A company buys an AI SDR platform with a lot of optimism. The team is excited. Leadership is excited. There is finally going to be more coverage, more outreach, more consistency, more personalization, and ideally, more pipeline.

The system gets connected. Lists get loaded. Messaging gets approved. Campaigns go live. Then everyone watches: Week two. Week four. Day 30. Day 60. Some replies come in. Maybe a few meetings get booked. Maybe there is some engagement, but not enough to make anyone comfortable. By day 90, someone in the room asks the question: “Is this working?”

And that is usually where the conversation goes sideways. Because sometimes what they really mean is: “Why hasn’t this fixed our pipeline yet?” That is a very different question.

AI SDR systems can be incredibly powerful. I believe that. Salesforce found that 83% of sales teams using AI reported revenue growth in the previous year compared with 66% of teams that were not using AI. That matters.

But AI does not enter your sales organization, wave a wand, and remove every weakness that existed before it arrived. In fact, sometimes it does the opposite. Sometimes it finds them faster.

The First Thing AI Does Is Turn on the Lights

Imagine walking into a dark room.

You know there is furniture in there. You know there are probably a few things on the floor. You just cannot see them very well. Then someone flips on every light at once. Suddenly, you see everything: the chair nobody pushed in, the pile of papers in the corner, the coffee stain on the rug, and the things that were always there are now impossible to ignore.

That is what AI SDR systems can do inside a sales motion. They create more activity, more data, more testing, more outreach, and more visibility. And when you move faster, weak spots become easier to see.

If one industry responds and another does not, you see it faster. If one buyer persona engages while another ignores you, you see it faster. If prospects open emails but do not reply, you see it faster. If meetings get booked but never become opportunities, you see that too.

And if qualified opportunities are handed to sales but stall immediately, well, that is not exactly an AI problem. The system may simply be showing you what was already there.

Your AI SDR framework makes this point clearly: AI improves speed, consistency, research, coverage, and testing, but it does not repair an unclear market, weak offer, poor data, or broken execution model.

That is not a criticism of the technology. That is the value of the technology.

The 90-Day Problem

Here is where expectations get interesting.

Many companies think in 30-, 60-, and 90-day increments. It makes sense. Quarterly reviews are built into how businesses operate. New systems need checkpoints. Teams want to know whether an investment is showing traction. There is nothing wrong with that. In the first 90 days, you should absolutely learn a lot.

You should know whether the lists are accurate. You should know whether the messaging is landing. You should know whether the personalization is relevant. You should know whether people are replying, whether the system is interpreting intent correctly, and whether leads are being routed properly. Those are very reasonable expectations.

But now ask a different question: how long does it normally take your human sales team to close a net-new customer? Sixty days? Ninety? One hundred twenty? Longer?

If a human salesperson cannot typically identify, develop, and close a new opportunity in 30 days, why would we suddenly expect AI to uncover one, warm it up, move it through your buying process, navigate the budget, survive procurement, and close it in less time?

AI can make parts of that process faster, but it cannot erase the process. That is the distinction people miss.

Sometimes the AI Is Working Fine, and the ICP Is Not

This one comes up constantly.

A company says it has an ICP. Then you ask them to describe the ideal customer. “Mid-market.” Okay. What else? “Technology companies.” Anything more specific? “Companies with 50 to 500 employees.” That is not an ICP. That is a list filter.

A real ICP should tell you who the company is, what is happening inside that business, who owns the problem, what trigger makes the problem urgent, and whom you should absolutely not waste time pursuing.

The AI SDR framework identifies this as one of the foundational requirements. A strong ICP tells the AI not just whom it can contact, but why that company may have a reason to care now. There is a big difference between those two things, and AI exposes that difference quickly. If your target is too broad, the AI will scale irrelevance beautifully.

That matters because Gartner found that 73% of surveyed B2B buyers actively avoid suppliers that send irrelevant outreach. It also found that 61% prefer an overall rep-free buying experience.

So the answer to weak performance is not always more outreach. Sometimes it is a smaller, smarter audience. I have said this before, and I will probably say it again: not everyone is your customer. AI did not change that. It just gave you a faster way to prove it.

Then There Is the Offer

This is another uncomfortable moment. The team sees low reply rates and immediately starts rewriting the email. Maybe the subject line is wrong. Maybe the CTA needs work. Maybe the message is too long. Maybe we need more personalization. Maybe the prompt is not good enough. And yes, sometimes the copy absolutely needs work.

But sometimes the email is fine - the offer is not (or worse, there is NO offer).

I wrote about this before in It’s Not You, It’s Your Offer. Buyers are not sitting around waiting to admire your messaging. They are deciding whether the outcome you are offering is valuable enough, credible enough, urgent enough, and easy enough to justify a conversation.

AI can express an offer 50 different ways; it cannot manufacture a reason to care. That is one of the strongest points in the AI SDR framework: a weak offer does not become strong simply because the outreach is automated. It becomes scaled indifference.

That is an important distinction, because if the offer is the problem, switching platforms will not fix it. Neither will doubling the volume.

Personalization Is Not the Same as Relevance

This is where AI can be impressive and still miss the point. We have all seen messages that say: “I noticed you are in Dallas.” “I saw you went to Ohio State.” “I saw your recent LinkedIn post.” Technically, that is personalized. Commercially, it may mean absolutely nothing.

Relevant personalization should connect an observed fact to a plausible business problem.

For example, if a company is suddenly hiring six implementation specialists, that may suggest implementation capacity is becoming a bottleneck. If you solve that problem, now you have a reason to reach out. That is useful personalization.

The AI SDR framework makes the same distinction. Good personalization links a real signal to a business issue and then to the offer. Everything else is often just decorative personalization. And buyers are getting very good at spotting the difference.

This Is Why the Funnel Matters

I have seen teams get excited about email sends, opens, replies, and meetings. All useful. None of them are revenue.

A better view is the whole journey: Accounts targeted → messages delivered → replies → qualified replies → meetings held → opportunities created → revenue.

Then look at where things break. If replies are low, maybe targeting, relevance, or the offer needs work. If replies are strong but meetings are weak, maybe the CTA or qualification process needs attention.

If meetings are strong but opportunities are not, the handoff or discovery process may be the problem. If opportunities are strong but nothing closes, that is a very different conversation.

The AI SDR framework recommends measuring this complete funnel because efficiency metrics can hide quality problems. That may be one of the biggest changes AI brings to sales development. Not just more activity. Better visibility into what that activity means.

The Real Story

I am still bullish on AI SDR systems. Very bullish. I think they will change sales development dramatically. They already are.

Salesforce’s data showing stronger reported growth among AI-using sales teams supports the potential. The technology can give companies better research, more consistent outreach, faster testing, stronger prioritization, and significantly more coverage than most human teams can manage alone.

But the companies that get the most from AI SDR will not be the ones that simply automate more: they will be the ones that use the technology to get smarter. They will listen to the response data. They will refine the ICP. They will improve the offer. They will tighten the handoff. They will coach the sales team. They will measure the entire funnel.

And they will understand that sometimes a disappointing early result is not proof that AI failed. Sometimes it is the first clear look they have had at what was already broken.

That is not failure; that is useful, because once you can see the cracks, you can finally fix them.

We have read the statistics.

AI is making teams more productive. AI is helping us personalize at scale. AI is writing content, analyzing data, prioritizing prospects, drafting emails, creating campaigns, summarizing meetings, researching accounts, and supposedly freeing all of us from the tedious work that used to consume our days.

Wonderful.

So why does sales and marketing still feel so dang hard?  Why aren't deals magically closing faster? Why are marketers still struggling to get attention? Why are salespeople still trying to figure out which prospects are actually worth calling?

And why, after implementing all of this technology, do we somehow still need people?

Because somewhere between the AI hype and the actual implementation, a lot of businesses made a very old mistake with a very new technology: They treated AI like something they could set and forget.

You can't.

AI Is an Enabler, Not an Autopilot Button

The Channel Marketing Association has been making this point for a while.

In its July 2025 "IN WITH AI" newsletter, CMA shared research showing:

• 64% of businesses said AI was improving customer relationships through more tailored messaging and smarter partner touchpoints.

• 60% reported measurable productivity improvements from automation.

• 59% of global marketers ranked AI-driven personalization as its most impactful use case.

• 47% were already using AI for content creation, including campaign materials and co-branded assets.

• Yet 62.6% were concerned about AI-generated misinformation.

That last number may be the most important one.

Because all the productivity in the world doesn't help if what you're producing is wrong, off-brand, irrelevant, or aimed at the wrong buyer.

CMA Co-Founder Kathryn Rose ⭐ has framed AI as an enabler for the channel, not a replacement for the people doing the work. CMA's 2025 AI in the Channel programming focused on practical uses including partner enablement, personalization, pipeline prioritization and sales acceleration, with an emphasis on making AI part of a larger growth strategy.

That distinction matters: AI can help you work faster; it cannot decide what your business should stand for. It cannot magically know your customer better than you do. It cannot repair a lousy offer. It cannot create trust because someone uploaded a spreadsheet and pressed "generate."

And it certainly cannot compensate for a GTM strategy that was bad before AI entered the room.

There Is No "Set It and Forget It"

I spend a ridiculous amount of time working inside AI platforms.

And one thing becomes obvious pretty quickly: what worked three months ago may not work exactly the same way today.

Researchers have documented substantial changes in the behavior and performance of the same commercial LLM services over relatively short periods of time. One widely cited study examining different versions of GPT-3.5 and GPT-4 found meaningful shifts across tasks and concluded that continuous monitoring was necessary when organizations rely on LLMs.

There is also a broader problem researchers call knowledge or data drift. The world changes. Language changes. Your customers change. Your source material changes. Your inputs change. The systems themselves can change. New 2026 research on continuous knowledge drift found that even common approaches designed to keep models current can struggle with evolving real-world information.

For marketers, you don't need the academic terminology to recognize it. You've probably experienced it.

You build a project, establish the voice, load the background, and you work with it for months. Then one day you look at what it generated and think: "Who wrote this?"

And occasionally the solution really is some version of, "Forget what I told you six months ago because apparently we've wandered into the woods."

AI needs management. It needs context. It needs training. It needs validation. It needs good source material. And it needs a human who knows when the output is technically correct but strategically terrible.

That isn't a bug in your AI strategy. That is your AI strategy.

And Now Your Email May Have Two Audiences

This is where marketing gets really interesting.

For years, we have obsessed over writing subject lines that make humans open emails. Now an AI system may summarize your email before the human reads it.

Think about that.

A 2026 Validity study, reported by Demand Gen Report, surveyed more than 500 U.S. marketers and 1,000 consumers and found that 55% of consumers make some decisions based on AI-generated email summaries without reading the entire email. The breakdown included people choosing to skip the full email, not open it, or delete it based on the summary. Only 10% said they completely trust those summaries to accurately represent the email.

Yes, you read that correctly: people don't necessarily trust the AI. They're still letting it influence what they read. That creates a completely different marketing problem.

You aren't only asking: "Will a human open this?" You also have to ask: "Will an AI understand this, summarize the important part, identify our message as relevant, and will the hook survive the summary?" "Will the CTA even make it into what the buyer sees?"

Validity's Guy Hanson describes this shift rather plainly. Mailbox providers are increasingly using AI and engagement signals to determine which messages users see, and he recommends that marketers start thinking about emails much like search professionals think about content: make the message easy for a machine to understand and accurately restate.

Which means your clever little six-paragraph wind-up before getting to the point? Probably not helping.

You Are Still Not the Target Audience

This brings me back to something I have been saying for years: You are not the target audience. I keep saying this in my posts because marketers have a remarkable ability to create campaigns based on what we like rather than what customers actually respond to.

AI does not make that problem disappear. It can actually make it worse. Because now you can produce a lot more of the wrong thing, much faster. Congratulations on your efficiency.

If your ICP is wrong, AI scales bad targeting. If your positioning is weak, AI scales weak positioning. If your offer isn't compelling, AI generates 15 beautifully formatted versions of an offer nobody wants.

If your customer data is garbage, personalization simply becomes highly personalized garbage. And if everyone internally thinks the campaign is fabulous but the customer doesn't care, AI isn't going to save you.

AI amplifies: that’s the opportunity and the danger.

The "AI Sound" Problem Is More Complicated Than We Think

There is another complaint I hear constantly: "That sounds like AI." Sometimes it does. We've all seen the posts: the dramatic setup, the perfectly symmetrical bullets, the strangely inspirational conclusion. The sentence structure that makes you wonder whether every executive on LinkedIn suddenly hired the same copywriter.

But there is another reason marketing is beginning to sound different: marketers are adapting to the systems sitting between us and our buyers. We are front-loading important information, tightening messages, making structures easier to scan, using clearer language, and are becoming more explicit about context and next steps.

Some of those changes may resemble AI-generated content because both marketers and AI systems are responding to the same environment: massive information overload and increasingly automated filtering.

So the goal shouldn't be: "Make sure nobody thinks AI touched this." The goal should be: Make sure it sounds like us, communicates something worth knowing, and survives whatever machine or human evaluates it first.

Those are very different standards.

AI Needs a Teammate

The most useful framework here may be one CMA has promoted around moving AI from "tool" to "teammate": Context. Training. Validation.

Context means giving AI enough information about your company, audience, offer, market and goals to produce something useful.

Training means teaching it how you communicate, what good looks like, and what belongs nowhere near your customer.

Validation means somebody still checks the work.

Every time.

Because personalized outreach at scale is fantastic until your "personalized" email congratulates someone on a job they left two years ago. Automation is great until your campaign keeps hammering a prospect who already told sales they're not interested. And AI-generated thought leadership is wonderfully efficient until your CEO reads it and says, "I would never say this."

That's where people come in. Not because AI failed. Because AI was never supposed to eliminate judgment.

Faster Isn't the Same as Better

This may be the biggest misconception surrounding AI in sales and marketing: we've confused production with performance.

Producing 10 times more content doesn't mean you generate 10 times more demand; sending 10 times more personalized messages doesn't mean you close 10 times more business, and finding 10 times more prospects doesn't mean you've found 10 times more customers.

AI can dramatically compress the time between idea and execution. But revenue still requires the things it required before: knowing your market, understanding your customer, having an offer worth considering, earning attention, building trust, creating relevance, and following up intelligently.

Having an actual human conversation when it matters.

Technology makes those things easier to execute; it doesn't make them optional.

The New Marketing Question

The question isn't whether AI belongs in marketing and sales. That debate is over: it does.

The better question is whether you're managing AI as part of your GTM system or merely adding AI tools to the same processes that weren't working before. Because AI isn't a crockpot.

You don't throw your ICP, a few prompts, and your old email sequence into the thing, turn it on low and come back eight hours later to a fully cooked pipeline.

You have to work with it, train it, challenge it, monitor it, update it, and sometimes tell it to forget what you've previously taught it because your business, your customer, or the model itself has changed.

Most importantly, someone still has to know what good looks like. That someone is a person.

AI can help us execute at a scale we couldn't have imagined a few years ago. But strategy, judgment, creativity, trust, and relationships still belong to humans.

And perhaps that's the real story of AI in marketing and sales: the technology changed the work. It didn't remove the responsibility for doing the work well.

So I'll leave marketers and sales leaders with two questions: Are you using AI to make a good strategy move faster? Or are you simply automating the problems you already had?

Okay, maybe three questions: when your next message goes out, do you know who is actually reading it first?

Every Friday afternoon, I have the privilege of leading a grief support group for women.

The rest of my week looks very different.

I spend hours working with AI platforms, helping organizations improve sales outcomes, rethink their go-to-market strategies, and figure out where technology can create better business results. Like many of you, I'm fascinated by what AI can do. Every week, there seems to be another breakthrough, another tool, another promise that work will become faster, smarter, and more efficient.

At first glance, these two parts of my life couldn't be more different. One is about technology. The other is about humanity.

Or so I thought.

The truth is, the lessons I've learned sitting in that room every Friday have changed the way I think about AI, leadership, sales, marketing, and community. And perhaps most importantly, they've reminded me what technology can never replace.

When most people hear the word grief, they immediately think about death. Sometimes that's true. But grief is much broader than that.

Every Friday, I sit with women who are grieving the loss of a spouse, a parent, or a lifelong friend. Others are grieving a marriage that ended, a job they loved, a pet that had been part of the family for fifteen years, or children who have grown up and no longer need them the way they once did.

Grief isn't always about losing someone. Sometimes it's about losing the future you expected to have. As I listen to these women tell their stories, I've noticed something. Very few of them are looking for advice. They're looking for connection.

Sometimes the most important thing that happens during our time together isn't something I say at all. It's the moment another woman quietly says, "I thought I was the only one who felt that way."

You can almost see the weight shift. The circumstances haven't changed. The pain hasn't disappeared. But they're no longer carrying it alone.

That is the power of community.

I've spent more than three decades building communities in business. Partner communities. Customer communities. Industry communities. Executive communities. For years, I talked about community because it drives engagement, advocacy, referrals, retention, and business growth.

All of those things are true.

But my Friday group has taught me something much more important. Community isn't valuable because it helps businesses grow. Businesses grow because community helps people belong. That's a very different perspective.

The more time I spend working with AI, the more convinced I become that this distinction matters. AI is remarkable. It can analyze millions of data points in seconds. It can draft emails, summarize meetings, identify buying signals, create presentations, organize research, and eliminate countless hours of repetitive work. I use it every day, and I encourage clients to use it. I believe organizations that ignore AI will eventually struggle to compete.

But here's what AI can't do: It can't notice the woman who hasn't spoken in twenty minutes and gently invite her into the conversation. It can't recognize that someone smiled while describing the hardest year of their life. It can't build trust simply by showing up, week after week, consistently creating a safe place where people know they'll be heard.

It can't create belonging.

That's because belonging isn't built through automation. It's built through presence. One conversation. One relationship. One act of trust at a time.

Ironically, the more sophisticated AI becomes, the more valuable these uniquely human skills become. The organizations that will thrive won't simply be the ones that adopt AI the fastest. They'll be the ones who use AI to give their people more time to do what only people can do.

·       Listen.

·       Coach.

·       Lead.

·       Encourage.

·       Build relationships.

·       Create communities.

Because community isn't something you automate. You can't launch it and check back next quarter. You can't install software and expect trust to appear. You can't "set it and forget it." Communities require intention. They require consistency. They require people who are willing to show up, especially when it's inconvenient.

Every Friday reminds me that healing doesn't happen because someone has all the answers. It happens because someone knows they don't have to walk through life alone.

Business isn't all that different: Customers aren't looking for another vendor. Employees aren't looking for another paycheck. Partners aren't looking for another logo. People are looking for organizations they can trust.

Organizations that listen, remember their names, that show up when things get difficult, and make them feel like they matter.

Technology can help us become more efficient. It can remove friction. It can surface insights we would have never found on our own.

But if efficiency becomes the goal instead of the tool, we've missed the point.

AI scales information. Communities scale trust.

And trust has always been, and will always be, the foundation of every meaningful relationship: whether you're helping someone navigate grief, serving a customer, leading a team, or building a business.

Every Friday, I leave that room reminded that people are carrying burdens most of us never see.

Every Monday, I return to a business world racing to embrace the next technological breakthrough.

I've realized those two worlds aren't separate at all. They're teaching the same lesson. Technology will continue to change how we work. Community will continue to change why people choose to work with us.

The future will be driven by the organizations that understand both.

Everywhere you look, the headlines tell the same story: AI is transforming sales and marketing. AI is increasing productivity. AI is accelerating growth. AI is changing everything.

And the numbers certainly support the excitement.

Nearly 88% of digital marketers report using AI daily. More than 85% of content professionals use AI to create content, while 45% use it specifically for brainstorming and ideation. Sales teams are embracing it as well, with 63% using generative AI to automate administrative work and 68% saying AI insights help them close deals faster. Global spending continues to climb, with AI in marketing projected to exceed $47 billion, and sales and marketing receiving more than half of all corporate AI investment budgets.

On the surface, it sounds like we have entered a golden age of productivity.

Marketers are publishing 42% more content. AI-powered campaigns are launching up to 75% faster. Predictive AI is improving conversion rates by 20% to 30%. Companies deploying AI in marketing report ROI improvements ranging from 20% to 30%.

So here's the question: If AI is working so well, why are so many organizations struggling to show meaningful business impact?

According to a recent Massachusetts Institute of Technology study highlighted by Harvard Business Review , only about 5% of AI implementations are delivering measurable business returns.

Think about that for a minute: nearly everyone is investing, but only a tiny fraction are seeing transformational results. That is not a technology problem. That is a business problem. And more specifically, it is a people problem.

Technology Has Never Been the Hard Part

For decades, businesses have had access to the same tools: the same CRM platforms, the same marketing automation systems, the same email tools, the same analytics dashboards, and the same internet. Yet some organizations consistently outperform others. Why? Because technology has never been the differentiator.

People are. Strategy is. Execution is.

The organizations generating real value from AI are not simply adding another piece of software to their stack. They are fundamentally rethinking workflows, processes, and decision-making. McKinsey & Company 2025 State of AI report found that organizations seeing the greatest impact are significantly more likely to redesign workflows, invest in change management, and embed AI into how work actually gets done rather than treating it as a standalone tool.

That distinction matters. A tool without a strategy is just an expense. A tool without experience is just experimentation. A tool without community and collaboration is often a very expensive lesson.

The AI Adoption Trap

I see this every week, Barbara Goworowski and I discuss it every day, and it looks like this: A company purchases an AI platform. The executive team gets excited. A few employees start experimenting. Some content gets generated. A few emails get automated. Maybe a chatbot appears on the website. And everyone declares victory.

Meanwhile, nobody has stopped to ask the harder questions. What business problem are we solving? How will we measure success? What process are we improving? How does this improve the customer experience? What happens to the human interaction our buyers still expect?

The reality is that many organizations have confused activity with outcomes.

Publishing more content is not the same as generating more revenue. Sending more emails is not the same as creating more opportunities. Automating tasks is not the same as improving customer relationships.

The Human Element Isn't Going Away

One of the biggest misconceptions about AI is that it somehow replaces the need for human expertise. It doesn't. In fact, it often amplifies it.

The best salespeople still understand buyer psychology. The best marketers still understand customer motivations. The best leaders still understand how to build trust.

AI can help identify patterns and summarize information. It can draft content and automate repetitive tasks.

But it cannot sit across the table from a customer and recognize hesitation in their voice. It cannot build genuine trust during a difficult conversation. It cannot understand the emotional context behind a buying decision. And it certainly cannot replace the years of experience that help professionals recognize opportunities, risks, and nuances that data alone may miss. (Need a good book on this? I recommend The AI Edge from Jeb Blount )

We cannot abandon the psychology of sales and marketing simply because we have new technology. People still buy from people. Trust still matters. Relationships still matter. Understanding still matters. In fact, as AI becomes more common, those human skills become even more valuable.

Because when everyone has access to the same technology, differentiation shifts back to the people using it.

The Bottom Line

The future of sales and marketing isn't AI versus humans. It's AI-enabled, people-powered. Organizations that understand that balance will be the ones creating measurable results, while others are still trying to figure out why their expensive new tool isn't changing the business.

What are you seeing in your organization? Are you using AI to replace human interaction, or to make your people even more effective?

Let’s kill the “Field of Dreams” strategy once and for all. Just because you can build something doesn’t mean you should. And just because you built it doesn’t mean anyone will buy it.

Hollywood sold us the fantasy: “If you build it, they will come.” Spoiler: they won’t.

Not unless the product solves a real problem, fits the market, and can actually be sold by the people responsible for moving revenue.

And yet, companies launch products, partner programs, portals, pricing models, and “innovative new solutions” every single day based almost entirely on internal assumptions.

That’s not strategy. That’s optimism wearing a PowerPoint presentation. And the cost of getting it wrong is massive.

Research consistently shows that somewhere between 40% and 90% of new products fail after launch. Not because the engineering was bad. Not because the team lacked effort. Not because marketing forgot to add enough LinkedIn hashtags.

They fail because companies built something the market didn’t actually want, didn’t understand, or didn’t value enough to change behavior for.

Rule #1: You Are Not the Target Audience

You know your company too well.

You know your product roadmap. You know your differentiators. You know how much work went into every feature release.

Congratulations. None of that means your customers care. One of the biggest dangers in product development is proximity bias: being so close to the solution that you mistake internal excitement for external demand. I see this constantly in B2B tech and especially in the IT channel.

Leadership teams sit in conference rooms convincing themselves:

• “Customers will love this.”

• “Partners have been asking for this.”

• “This changes everything.”

Meanwhile, no actual customer or partner was included in the conversation. As I’ve written before, marketers and business leaders are notoriously bad at recognizing this problem because they often market to themselves instead of their audience.

A real Ideal Customer Profile (ICP) is not:

• “Mid-market companies”

• “Healthcare”

• “Anyone concerned about security”

• “Businesses with endpoints”

That’s not an ICP. That’s a census category.

Real ICPs include:

• Buying triggers

• Budget realities

• Internal political blockers

• Existing tech stack

• Operational maturity

• Business pain

• Desired outcomes

• Risk tolerance

• Staffing limitations

Because if you don’t know exactly who you’re building for, your positioning becomes generic, your messaging becomes weak, and your sales process becomes a group therapy session about “market conditions.”

Rule #2: Your Customer’s Perception Is Your Revenue Reality

You may think your product is revolutionary.

Your customers may think it’s:

• Too expensive

• Too confusing

• Too risky

• Too similar to competitors

• Too difficult to implement

• Too hard to support

• Another dashboard nobody asked for

And guess whose opinion wins?

This is why customer councils, partner advisory boards, beta groups, and focus groups matter so much. Because perception drives adoption. Adoption drives revenue. And revenue is what keeps everyone employed.

Companies that ignore external feedback loops often end up solving imaginary problems while missing the real operational frustrations customers are screaming about daily. The market rarely punishes you immediately for this mistake.

It punishes you six months later when:

• adoption stalls,

• churn rises,

• partners disengage,

• sales cycles drag,

• and marketing starts blaming “awareness.”

Your Channel Partners Are Not Just Resellers. They’re Market Intelligence.

This is where companies dramatically underestimate the value of channel partners. The best partners sit closest to the customer. Closer than your executive team. Closer than your product managers. Sometimes even closer than your own sales organization.

Partners hear the objections. They see failed implementations. They know which competitors keep showing up in deals. They understand what customers complain about after deployment. They know what buyers actually prioritize once budgets get involved.

That insight is gold.

A strong partner advisory council gives you something most companies desperately lack:

Reality.

Partners can quickly tell you:

• Whether your pricing model creates friction

• If margins are attractive enough to motivate selling

• Whether onboarding is too complicated

• If implementation will overwhelm SMB customers

• Whether your support model is scalable

• If your product actually solves a meaningful business problem

• Whether your messaging resonates in real sales conversations

And perhaps most importantly: They can tell you whether your solution is easy to explain. Because if your partners can’t clearly articulate your value proposition in under two minutes, your product launch already has a problem.

Why Smart Vendors Bring Partners in Early

Too many vendors treat partner councils like a checkbox activity after launch. That’s backwards.

The smartest channel organizations involve partners before:

• pricing is finalized,

• messaging is locked,

• packaging is completed,

• and roadmap decisions are cemented.

Because changing direction early is manageable. Changing direction after a failed launch is expensive.

A good partner council helps vendors:

• Validate Product-Market Fit: Partners know whether your solution addresses a real-world pain point or simply adds complexity.

• Pressure-Test the GTM Strategy: Channel conflict, unclear margins, weak enablement, and unrealistic expectations can all be identified before launch.

• Improve Technical Readiness: Partners often uncover implementation issues, onboarding friction, or support gaps before customers ever see them.

• Accelerate Adoption: Partners who help shape a product become emotionally invested in its success.

People support what they help build. And frankly? Partners are far more likely to champion a vendor who actually listens to them. Imagine that.

Focus Groups Still Matter (Yes, even in 2026)

There’s also this strange modern belief that dashboards, AI, and analytics somehow replaced human conversations. They didn’t.

Focus groups still matter because data tells you what happened. People tell you why. And those are very different things.

Focus groups help uncover:

• Messaging confusion

• Emotional buying triggers

• User frustrations

• Packaging concerns

• Feature prioritization

• Hidden objections

• Perception gaps

• Implementation fears

Things your CRM absolutely will not tell you.

Research shows:

• 79% of researchers use focus groups to refine messaging and positioning

• Traditional focus group use has actually increased in recent years

• Companies using active customer feedback loops reduce launch risk and accelerate speed-to-market

Because iterative feedback beats executive guessing every single time.

Community Is the Competitive Advantage

The strongest companies don’t just sell products. They build ecosystems of feedback. As I’ve said before: “A business without a community is just another brand shouting into the void.”

Community is not just marketing fluff. It is operational intelligence. Customer councils. Partner advisory boards. Peer groups. Online communities. Events. Beta programs.

These are not “nice-to-have” programs. They are strategic infrastructure. The companies winning today are the ones listening faster than competitors can react.

The Best Product Teams Don’t Build Faster.

They Listen Better.

That’s the real competitive advantage.

Not louder launches. Not AI buzzword bingo. Not another “single pane of glass.” Not slapping “platform” onto your homepage and praying investors get excited.

The companies that consistently win are willing to hear uncomfortable feedback before the market punishes them for ignoring it.

Because launching without validation isn’t confidence.

It’s gambling with payroll.

Final Thought

Every failed product launch usually starts the same way:

• Leadership got excited.

• Internal teams agreed with each other.

• No one challenged assumptions.

• Customers weren’t consulted early enough.

• Partners were informed instead of involved.

And then everyone acts shocked when adoption struggles. No company should build in a silo. Not anymore.

Your partners see things you don’t. Your customers know things you don’t. And your market is changing whether your roadmap acknowledges it or not.

So before your next launch, ask yourself: Are you building for the market? Or are you building for your own ego?

Because there’s a difference. And your revenue knows it.

Let’s start with a reality check. Just because you’re selling something doesn’t mean anyone wants to buy it.

That’s the uncomfortable truth most teams avoid. It’s easier to blame the sales team, the messaging, the market, or now, AI. But more often than not, the issue is much simpler and much more foundational.

You’re talking to the wrong people.

The Expensive Lie: “We Can Sell to Anyone”

Somewhere along the way, many businesses convinced themselves that broader was better. “Our solution works for everyone.” No, it doesn’t. And deep down, you already know that.

What that actually translates to in the real world is vague messaging, an inconsistent pipeline, and a sales team chasing anything that looks remotely interested. It creates a false sense of activity, but not progress.

When you try to appeal to everyone, you dilute your value. Your message becomes generic. Your differentiation disappears. And your buyers feel it immediately.

You’re not struggling to sell. You’re struggling to focus.

An ICP Is Not a Marketing Exercise. It’s a Business Strategy.

Your Ideal Customer Profile is not a persona. It’s not a slide in a pitch deck. It’s not something marketing owns, while sales does their own thing.

It is the foundation of your go-to-market strategy.

It defines whom you target, how you position, where you invest, and just as importantly, where you don’t. When your ICP is clear, everything sharpens. Messaging becomes more precise. Sales conversations become more relevant. Prioritization becomes easier because you no longer have to debate every edge case.

And the data backs this up in a big way. Companies that define and operationalize their ICPs see better outcomes across the board dramatically. Win rates increase by as much as 68 percent when teams focus on best-fit accounts. Conversion rates can jump by over 70 percent when targeting is aligned to a well-defined ICP. And when marketing is aligned to that same profile, revenue from campaigns increases by up to 40 percent.

Janet Schijns at JSG always reminds me, “Words walk, numbers talk.” And she’s absolutely right.

The Part Most Teams Skip: Who You Should NOT Sell To

Here’s where things usually fall apart. Most companies define who they want. Very few define who they don’t. An ICP is not just about targeting. It is about filtering.

Because the fastest way to lose time, money, and momentum is chasing deals that were never going to close in the first place.

You see it every day. Sales teams are taking meetings with companies that don’t have the budget, the urgency, or the problem you actually solve. Product teams building features for outlier customers. Marketing generating leads that look good on paper but go nowhere.

That’s not pipeline. That’s noise.

A strong ICP eliminates that noise. It forces clarity. It creates discipline. And it gives your entire organization permission to say no.

Now Add AI and Watch What Happens

This is where the conversation gets interesting. Because AI is changing how fast we can find and engage potential buyers.

AI-powered systems can scan data, identify patterns, surface intent signals, and prioritize accounts in ways that were not possible even a few years ago. Tools like AI SDRs can build lists, trigger outreach, and engage prospects around the clock.

On the surface, it feels like a silver bullet. But it’s not. Because AI does not decide who your ideal customer is. It works off the definition you give it.

If your ICP is clear, AI becomes a force multiplier. It helps you find the right accounts faster, engage them more effectively, and prioritize where your team should spend time.

If your ICP is unclear, AI just helps you chase the wrong accounts faster. Same effort. Same noise. Just at scale.

AI Needs a Target. Your ICP Is the Target.

Think about how these systems actually operate: they look at historical data. They analyze patterns. They try to identify signals that resemble previous wins.

But if you have not clearly defined what a “good customer” looks like, those patterns are incomplete. The system fills in the gaps. It guesses. And suddenly your “high-intent” leads are just slightly better guesses than before.

That’s not strategy. That’s automation without direction.

A strong ICP changes that completely. It gives AI a clear target. It defines what good looks like across firmographics, behavior, buying triggers, and real-world pain points.

Now your systems are not just generating activity. They are generating relevance.

What High-Performing Teams Do Differently

The teams that are winning right now are not using AI to cast a wider net. They are using it to tighten the net.

They start by deeply understanding their best customers. Not just surface-level attributes like industry or company size, but what actually drives buying behavior. What problems create urgency? What events trigger action? What makes a deal move versus stall?

Then they operationalize that.

They feed it into their CRM. They align sales, marketing, and product around it. They use it to prioritize accounts, shape messaging, and guide outreach. And then they layer AI on top of it.

Now, AI is not guessing. It is executing against a clear strategy. It is identifying lookalike accounts, prioritizing high-fit opportunities, and helping teams focus where deals are most likely to close. That is where the real leverage shows up.

The Business Impact Is Not Subtle

When you get ICP right, the impact is not incremental. It is exponential.

Teams that focus on ICP-aligned customers achieve higher contract values because they sell to organizations that actually need and value what they offer. Annual contract values increase by nearly 30 percent when you are targeting the right customers.

Retention improves because you are solving real problems for the right buyers. Expansion becomes easier because those customers are better fits from the start. And perhaps most telling, 71 percent of companies that consistently exceed their revenue and lead generation goals have a clearly defined ICP guiding their efforts.

This is not a marketing best practice. This is a revenue strategy.

Most ICPs Are Useless

Let’s be honest for a second. Most companies technically “have” an ICP. It’s sitting in a document somewhere. It was built once, maybe during a strategy session, and hasn’t been touched since. And no one actually uses it.

That is not an ICP. That is a checkbox.

A real ICP is alive. It shows up in your systems. It shapes your decisions. It evolves as your market evolves.

If it isn't influencing how your sales team prioritizes accounts, how your marketing team builds campaigns, and how your product team makes decisions, it isn't doing its job.

The Bottom Line

AI can help you find opportunities faster than ever before. But it cannot tell you who you should be selling to. That is still on you. And if you get that wrong, AI will not fix it. It will just help you miss your targets faster and more efficiently than ever before.

The Challenge

So, here’s the question: Do you actually know who your best customer is? Or are you still taking meetings and hoping to figure it out along the way? Because in a world where AI can find anyone, the companies that win are the ones who know exactly who to ignore.

What’s your ICP, and when was the last time you challenged it?

Why the phone still has to ring, and why the human on the other end matters more than ever.

Let me just say it plainly, because I have been saying it to clients for the better part of a year now: AI is better than most SDRs at prospecting.

It is faster. It is more consistent. It does not forget to follow up. It does not have a bad morning, it does not need a pep talk before picking up the phone, and it does not get discouraged when someone hangs up. It can research accounts, identify buying signals, draft outreach, and prioritize opportunities in minutes.

And still, with all of that horsepower, it will not close your deal. That is the part everyone keeps dancing around in board meetings, SKOs, and LinkedIn posts.

Jeb Blount said it best: "AI is not going to kill sales. What it is going to do is punish mediocrity in sales."

That is exactly what is happening right now in companies I engage with every week. I spend my days with leaders who are looking for a silver bullet that will make leads appear, pipeline grow, and quotas hit themselves. AI is great at recognizing patterns, reading intent, and pointing you to the right companies and people for what you sell. What it cannot do, and what it will never do, is make the phone ring on its own.

The Lie We Are Telling Ourselves

Ever stare at your pipeline and think, "We are doing everything right, so why is nothing closing?" Activity is everywhere. Emails are flying out. Sequences are humming. Dashboards look impressive to anyone who is not actually paying attention. And yet deals stall.

So what happens next? We add more. More outreach, more automation, more AI. We rarely stop to ask whether the strategy itself is broken. We just scale the activity and hope volume fixes it. AI makes that very easy to do, and that is the trap. And hope is never a winning GTM motion.

AI will execute exactly what you tell it to do. It just does it faster and at scale. If your messaging is off, AI does not fix it. If your targeting is wrong, AI does not fix it. If your value proposition is soft, AI does not fix that either. It just helps you fail more efficiently, in more inboxes, with prettier subject lines.

What AI Actually Is

Matt Dixon framed it in a way I wish every sales leader would tape to their monitor: "Think of AI as Jarvis to Iron Man or Iron Woman." Not the hero. The assistant. The enhancer. The thing that makes you faster, sharper, and more effective. When you use AI that way, it becomes a competitive weapon. When you expect it to be the hero, you end up disappointed, and your buyers end up annoyed.

Blount and Anthony Iannarino make the same point in The AI Edge. They describe three kinds of people in this new world: those displaced by robots, those controlled by robots, and those enhanced by robots. The entire book is an argument for becoming category three. Lean into being human, and use AI to create time and leverage so the human parts can shine.

What AI Actually Does Well

AI removes friction. It takes the busywork off your plate and eliminates every excuse for lazy outreach or poor preparation. Most importantly, it gives you time back, and time is the only resource in sales you cannot manufacture.

This is real and measurable. IBM Citing McKinsey & Company research, reports that companies using generative AI to improve the customer experience are 1.7 times more likely to outperform peers than those that do not (Hayes, IBM Think). Salesforce, in its own reporting on AI for prospecting, points out that AI agents serve as productivity multipliers at every step of the sales cycle, delivering faster time-to-value and ensuring leads do not slip through the cracks. That is a legitimate edge. It is also exactly where the role of AI ends.

AI should be doing your research, your list building, your first drafts, your follow-up reminders, your CRM updates, your pre-call briefings, and your call summaries. That is where it shines. It supports. It accelerates. It assists. No AI should sell for you. It helps you find the right opportunities at the right time and get you into better conversations faster. That is where its job ends and yours begins.

The 30 Percent Rule Most Teams Ignore

Here is where most teams get this wrong. They do not know where to draw the line between what to hand off and what to hold onto. I use a simple rule with clients, and it clears things up fast. AI should handle about 30 percent of the work, the repetitive, mechanical, time-consuming tasks. The remaining 70 percent belongs to you. And that 70 percent is everything.

That is where judgment lives. That is where creativity lives. That is where real communication happens. That is where deals are actually won. The moment you start handing that part over to AI, everything begins to sound the same. Everything starts to feel generic. Generic does not convert. It never has.

Why AI Does Not Close Deals

AI is great at information. Sales is about interpretation. Buyers do not make decisions because your email was well structured or because your sequence had perfect timing. They make decisions because they feel confident. Confident in the outcome. Confident in the partner. Confident that they are not about to make a very expensive mistake.

AI cannot create that feeling. It can give you talking points. It can give you insights. It can even make you sound smart. But it cannot sit across from a nervous buyer and feel hesitation in the room. It cannot adjust in real time when the VP of Finance raises an eyebrow. It cannot navigate multiple stakeholders with competing priorities and read who actually signs the check. It cannot make the cost of doing nothing feel real.

Without that, there is no urgency. And no urgency means no deal.

Trust and Human Skills Just Got More Valuable

This is where most people get it backwards. They assume AI reduces the need for human skill. It does the opposite. In a world flooded with automation, human connection stands out. People still buy from people they trust, and trust does not come from automation. It comes from someone showing up, listening, and actually caring whether the answer they give is the right one.

I see this play out every week. A client will tell me their team is running thousands of sequenced emails with near-zero reply rates, and in the same breath, mention that the one rep who picks up the phone and visits prospects in person is outperforming the rest of the team three to one. That is not a coincidence. That is the market telling you something.

The Market Is Already Reacting

We are already seeing what happens when AI gets misused at scale. Mass outreach, generic messaging, and personalization that is not actually personal. Buyers are no longer just ignoring it. They are blocking it. And when you get blocked, you do not just lose a deal, you lose access.

In the early days of AI email, companies burned entire lists in twenty-four hours and got blocked by every company they targeted. The old rule was that if you sent a bad email, someone would delete it. The new rule is, if someone thinks AI sent it, they block you, because they know ten more are coming. You do not lose the prospect to a delete button anymore. You lose them permanently.

At the same time, something interesting is happening on the other side of that same shift. Real human interaction is becoming more valuable than it has been in the past 20 years. Thoughtful outreach. Real conversations. Showing up like a person, not a process. For field sales, right now is a boom time for in-person prospecting. You show up, and people are happy to see you. In a world full of noise, being real wins.

AI Raises the Bar. It Does Not Lower It.

Your buyers are using AI too. They are researching before they ever talk to you. They are validating your claims. They are comparing you to your competitors before you even know you are in the deal. By the time you show up, they are informed and skeptical.

Your job is no longer to provide information. Your job is to provide clarity. To guide. To challenge. To help them make a confident decision in an environment where every vendor is armed with the same data and the same talking points. That role is not going away. It is becoming more important by the quarter.

What Smart Leaders See Coming

There is also a bigger shift happening that most leaders are underestimating. LinkedIn's Dan Shapero framed it about as well as anyone: if every seller on your team is 30 percent more effective, are you going to want more sellers, or fewer sellers? If you have an opportunity in front of you, you'll want to double down.

This is not a story about replacing salespeople. It is a story about amplifying them. The teams that understand this will scale. The ones that do not will try to cut their way to efficiency and wonder why growth stalls out two quarters later. Aneesh Raman from LinkedIn put it even more plainly, that "social skills will matter now more than ever." When everyone has access to the same tools, the differentiator is not the tool. It is the human driving it.

The Bottom Line

AI did not replace sales. It removed the excuses. You do not get to say you did not have time. You do not get to say you did not know enough about the account. You do not get to say you were not prepared for the meeting. Now you are, or you can be. So if deals are not closing, it is not a technology problem. It is a human one.

In the age of AI, we do not need less human touch. We need more. More genuine relationships. More real conversations. More of the things that no model can replicate and no competitor can copy.

The Challenge

So here is the question I leave with every team I work with. Are you using AI to make your sales team better, or just to make them ignore you faster? And more importantly, what is in your 70 percent that no one else can replicate? That is where your revenue lives. That is where it has always lived. The only thing that has changed is that the tools around it have gotten better, and the bar for being human has gotten higher.

Ever hear someone say: “We sent two emails, posted on LinkedIn, and nothing happened.” Or my personal favorite: “We tried social selling.” Spoiler: You didn’t try social selling. You tried activity and expected outcomes.

Let’s be honest about how B2B buying actually works today.

Because if your go-to-market strategy assumes a clever post or a couple of emails should generate revenue, you’re misunderstanding the entire buying process. And the data makes that painfully clear.

The Buyer Is Already Moving Without You

Research from Gartner shows that buyers are roughly 80% through their decision process before they engage with a vendor.

By the time someone fills out a form or agrees to a meeting, they’ve often already done significant homework. They’ve researched vendors, asked peers for recommendations, read analyst reports, explored LinkedIn conversations, participated in industry communities, and compared multiple solutions and alternatives. In many cases, they have already formed an initial opinion about the market and the providers within it before a sales conversation ever begins. In other words, the buying journey started long before your outreach arrived.

Your email didn’t create the opportunity. At best, it entered the conversation when the buyer was already forming opinions.

Now layer on another reality.

The typical B2B purchase now involves 6 to 11 stakeholders.

Each stakeholder evaluates the decision through a different lens. Finance looks for cost justification, security focuses on risk mitigation, IT cares about integration and technical stability, operations wants minimal disruption to existing workflows, and leadership expects clear, measurable outcomes. Sales doesn’t close when a single person says yes. Sales closes when the entire buying group reaches alignment and everyone stops saying no. That alignment takes time. This is why most complex B2B sales cycles stretch over six to nine months, from problem recognition to a signed agreement.

Activity Is Not a Go-To-Market Strategy

One of the most common mistakes I see in organizations is what I call random acts of marketing and sales. A few cold emails. A handful of LinkedIn posts. Maybe a webinar or two.

Then everyone waits for pipeline.

When nothing happens, the typical conclusions are predictable: “We need better messaging.” “We need more outreach.” “We need another SDR.” But rarely does anyone pause to ask the more important question: do we have a system that consistently builds trust with buyers before they actually need us? Because in reality, that’s what drives revenue.

Email works. LinkedIn works. Events work. Communities work.

But none of them work in isolation.

They work when they are part of a coordinated demand engine designed to reach buyers across multiple trust signals.

AI Is Transforming Sales, But It’s Not Replacing People

This is where the conversation often becomes extreme.

Some people claim AI will replace the entire sales organization. Others dismiss it entirely.

Both views miss the point.

AI is incredibly powerful when applied to the right parts of the sales process. It excels at analyzing buyer intent signals, identifying high-probability accounts, researching prospects at scale, monitoring market and ecosystem activity, personalizing outreach, and helping sellers prepare more informed conversations. In other words, AI doesn’t replace good sellers; it makes them faster, better prepared, and more informed. But AI doesn’t replace the human elements that move complex deals forward.

AI does not build long-term trust, navigate internal buying politics, interpret subtle hesitation within a buying committee, or develop credibility within an industry ecosystem. Those are human capabilities. The most successful organizations today recognize this and are not choosing between AI and people: they are leveraging both. They are building hybrid systems where AI amplifies human expertise.

Where Modern B2B Sales Actually Happen

Today, successful revenue teams operate across several interconnected channels that reinforce one another.

Not separately. Together.

1. People Sales is still fundamentally human. Relationships, credibility, and expertise matter because buyers trust people long before they trust vendors. Great sellers create confidence, guide complex decisions, and help organizations navigate risk, making them an essential part of moving deals forward.

2. AI and Data Signals AI dramatically improves how organizations identify and engage potential buyers. It helps teams detect important signals such as job changes, funding announcements, technology adoption, hiring patterns, content engagement, and intent signals across digital platforms. Instead of guessing who might be interested, teams can prioritize accounts that are already showing signs of need.

3. Email Outreach Email remains one of the most direct ways to start conversations with potential buyers. But effective outreach today is informed by research, aligned to real buyer problems, personalized to the specific account, and timed around meaningful intent signals. The goal isn’t to send more messages, it’s to send the right message at the right time to the right buyer.

4. LinkedIn Visibility LinkedIn is not a lead-generation machine on its own; it’s a credibility engine. Buyers watch those who consistently share useful insights, understand the industry, participate in conversations, and contribute valuable perspectives. Visibility creates familiarity, familiarity builds trust, and trust influences buying decisions long before a sales conversation ever begins.

5. Ecosystems and Communities Ecosystems and communities may be the most underestimated influence in B2B sales. When buyers are uncertain, they rarely ask vendors first; they ask peers, partners, and trusted communities (Pax8 , GTIA - Global Technology Industry Association , ConnectWise do this well). Questions like “Have you worked with them?”, “Who’s strong in this space?” or “What’s your experience?” often surface in industry groups, partner ecosystems, events, and professional communities. When someone is trusted and responds positively, the buying process accelerates dramatically.

Sales Is a System of Signals

The most important shift organizations must understand is this: deals rarely happen because of a single interaction. They happen because multiple trust signals accumulate over time. A buyer might see your insights on LinkedIn, hear your name mentioned by a peer, read your content, receive a thoughtful email, encounter your perspective in a community discussion, or see your company referenced by analysts or partners. Individually, none of these moments closes a deal. But together, they build credibility - and credibility dramatically increases the likelihood that when a buyer finally reaches out, you are already the name they trust.

The Bottom Line

A clever email won’t build a pipeline. A single LinkedIn post won’t close a deal. And AI alone won’t replace the human side of sales. Modern B2B revenue comes from systems, not tactics -systems that combine human expertise, AI-driven insights, targeted outreach, visible thought leadership, strong ecosystem relationships, and credibility within trusted communities. When those elements work together, sales become far more predictable. Deals don’t feel forced; they feel inevitable. Because by the time the buyer finally decides to talk to you, you’re already the name they trust.

Let me ask you a question: Are you building a repeatable sales motion…Or are you just hoping the next email works better than the last one?

(Because Buyers Trust People More Than AI)

Let’s be real: AI didn’t kill the buyer journey; it just made it painfully obvious how little control anyone thought they had in the first place.

In 2025, your buyers aren’t waiting for your drip campaign, your “helpful” nurture sequence, or your cleverly gated white paper. They’re building their own path, which is messy, nonlinear, peer-influenced, and 100% on their terms.

And here’s the kicker:

Buyers now spend 83% of their time doing independent research, and long before you ever get a seat at the table. Eighty-three percent. That’s not a buyer’s journey. That’s a buyer blackout period.

And while marketers scramble to out-produce each other with AI-generated content, buyers are quietly choosing a different algorithm: community, peers, people they trust. Ecosystems where vendors don’t control the conversation.

Because when AI floods the market with more content than a human could read in ten lifetimes, trust becomes the only filter that matters.

The Trust Rebellion: Buyers Believe People, Not Pitch Decks

Want to know what actually influences a B2B decision in 2025? Hint: it is not your landing page, your tagline, or your chatbot. 74% of B2B buyers rely on peer recommendations and third-party validation before engaging a vendor directly.

Let me translate that with just the right amount of sarcasm: Your buyer trusts a stranger on Reddit more than your entire marketing department. And that’s not personal, it’s math. When everything online now “sounds strategic,” “leverages AI,” and “empowers digital transformation,” buyers have one sanity check left: “What do people like me say about you?”

AI creates content. Community creates confidence. And confidence closes deals.

Buyers Don’t Follow Funnels Anymore, They Follow People

The old-school funnel was built on a fantasy: that buyers move step-by-step, predictably, and in response to your messaging. It was a cute idea then, but it is completely outdated now.

Today’s buyer journey looks like a paint spill. It is nonlinear, cross-channel, influence-heavy, and invisible until very late. By the time a buyer finally fills out your form or requests a demo, your fate is sealed. Why? Because most vendors are chosen before first contact. Your company and products are not being evaluated; you’re being confirmed.

And if your community hasn’t already validated you, educated them, or made you visible in the spaces buyers trust? You’re not losing. You never even entered the race.

The Buying Group Has Exploded: And So Has the Need for Community Proof

Barbara Goworowski recently did some research at JSG and she shared that buying committees now average 11+ stakeholders and 57 digital touchpoints. Before they ever talk to you. Before they attend your webinar. Before your SDR sends that “bumping this up in your inbox” email.

You know what influences that many people across that many touchpoints? It is not brand campaigns, or sales outreach, or SEO. It is now community, ecosystems, partner influence, and shared experience. Community is the only scalable trust engine that reaches people before you do.

Brand Gravity Is Now the Game, and Community Is the Mass

Marketers call this phenomenon “Brand Gravity,” the magnetic pull created when credibility, social proof, and consistent visibility attract buyers into your orbit. Community is the single biggest contributor to that pull.

It provides:

• real human validation

• use-case storytelling

• partner amplification

• social proof at scale

• third-party credibility

• places where buyers see themselves in your customers

AI cannot replicate that.

AI can hand buyers information. Community hands them confidence. And confidence, not content, is what moves a deal from consideration to closed-won.

Where Community Actually Shows Up in the Buyer Journey

Let’s map it out:

Early Journey: “Who should I even look at?”: Buyers check communities, partner sites, and peer channels first. If you’re not there, you don’t exist. (Yes, that’s harsh. It’s also accurate.)

Mid Journey: “Do I trust them?”: Community members share experiences, wins, frustrations, and real talk. Buyers trust that more than anything your brand publishes.

Late Journey: “Are they the safe choice?”: More stakeholders = more risk mitigation. Community equals risk insurance.

That’s why vendors with strong ecosystems and engaged communities consistently hit shortlists before sales even knows a deal exists.

AI Will Scale Your Content. Community Will Scale Your Revenue.

AI improves efficiency. Community improves certainty.

AI can:

• generate copy

• repurpose content

• automate workflows

• speed up research

But AI cannot:

• build belonging

• create shared identity

• replicate lived experience

• produce peer validation

• generate trust

And trust is the irreplaceable currency of modern B2B.

The Bottom Line

Your buyers aren’t looking for more content. They’re looking for signals, real human ones. Signals that your customers succeed with you. Signals that your partners advocate for you. Signals that peers trust you enough to mention you when you’re not in the room.

AI may shape what buyers see, but community shapes what buyers believe. And belief, not brand, not algorithms, not keywords, is what wins deals now.

So, ask yourself: when your buyer starts researching at 8 p.m. in a Slack group, Reddit thread, LinkedIn comment section, or partner community…are you even in the conversation?

Because in 2025, your brand isn't beating ChatGPT, but your community will.

Ever notice how every conversation right now somehow circles back to AI? AI will replace jobs. AI will write content. AI will run sales calls. AI will tuck us in at night.

Let’s be real: AI isn’t replacing humans, it’s replacing mediocrity.

And in a world where algorithms are automating everything that can be templated, the one thing that can’t be replicated is you. That’s where personal branding comes in.

Personal Brand = Modern Reputation

Gary Vaynerchuk said it years ago, but it’s more relevant than ever: “Personal brand” is just a modern way to say “reputation.”

And your reputation, unlike your job title, follows you everywhere.

Yet too many professionals, especially in sales, still treat personal branding as optional. It’s not. It’s your modern resume, credibility engine, and insurance policy rolled into one.

According to LinkedIn, 56% of professionals say a strong personal brand has directly led to new opportunities.

And in the age of AI, that number’s only going up; because buyers, employers, and partners want to know who they’re dealing with, not just what they’re buying.

AI Raised the Bar. It Didn’t Eliminate It.

AI can crank out blog posts, emails, and LinkedIn updates faster than any of us can sip our morning coffee.

But here’s what it can’t do:

• Build trust.

• Tell your story.

• Make people feel something.

That’s the “human edge.”

75% of consumers say their desire to interact with a real person increases as technology improves (PwC). 88% say authenticity matters when deciding which brands to support (Stackla).

AI may power efficiency, but authenticity powers connection. And connection is what converts.

Why Sales Pros Need Personal Brands

If you’re in sales, your LinkedIn profile is doing one of two things right now:

1. Making you money.

2. Making you invisible.

People don’t buy from logos; they buy from people they trust.

A Sprout Social, Inc. study found 76% of buyers are more likely to purchase from a brand they feel connected to, and that connection often starts with a person: the one sending the message, not the company posting the graphic.

When sales teams build personal brands:

• Visibility becomes credibility. Thoughtful insights attract inbound leads instead of endless cold calls.

• Conversations become conversions. A consistent voice turns curiosity into confidence.

• AI becomes an amplifier, not a crutch. Use it to draft or summarize, but you remain the differentiator.

Because when your competitors all sound like ChatGPT , your humanity becomes your superpower.

Your Network Is Your Multiplier

Here’s where Jay McBain’s concept of “Superconnectors” comes in and it’s pure gold for anyone building a personal brand.

McBain, Chief Analyst at Canalys, mapped the entire tech ecosystem: hundreds of thousands of partners, thousands of vendors, and tens of millions of people, all converging in about 1,000 “watering holes” (industry events, associations, podcasts, and media).

His takeaway: influence doesn’t live in algorithms; it lives in humans who connect humans.

“Superconnectors and great community management have created billionaires across the channel,” McBain says. “These founders believed in the grassroots, bottom-up approach when investors didn’t understand the vision.”

Translation? Your personal brand doesn’t grow in isolation. It compounds through participation: showing up, speaking up, and connecting people in ways that matter.

In a noisy digital world, the fastest path to visibility isn’t shouting louder, it’s being known for bringing people together.

The Data Doesn’t Lie

Let’s talk numbers (because words walk, but numbers talk):

• 82% of people are more likely to trust a company whose leaders are active on social media. (Brand Builders Group)

• 77% of B2B buyers say they are more likely to purchase from a company whose leadership team is visible and active on LinkedIn. (Edelman)

• Companies with engaged employee advocates see 58% better brand visibility and 20% higher lead conversion rates. (LinkedIn)

• Brand consistency increases revenue by up to 33%. (Lucidpress)

Visibility isn’t vanity: it’s velocity.

Start Small, But Start Now

Building a brand doesn’t mean becoming an influencer. It means becoming findable, credible, and valuable at scale.

Start here:

1. Own your story. What do you want to be known for?

2. Pick your lane. Focus on three to five topics aligned with your expertise.

3. Show up consistently. Once a week is fine; just show up.

4. Engage, don’t just post. The comment section is the new sales floor.

5. Use AI as your intern, not your imposter. Let it help, not replace.

The Human Algorithm Always Wins

A 2023 McKinsey study estimates 30% of all work activities could be automated by 2030. That’s not a death sentence, it’s an opportunity.

Because what can’t be automated? Judgment. Experience. Empathy. Reputation.

Personal branding isn’t about chasing clout, it’s about future-proofing your relevance. And every day you delay building yours is a day you limit your upside.

AI may write faster. But you connect deeper. And in business, connection still closes deals.

The Bottom Line: AI may be writing the headlines, but you are still the story. And in a networked world, your superpower is how you connect the dots…and the people.

Your Turn: Are you building your personal brand or waiting for someone else to tell your story? And who are you connecting along the way?

Ever sat in a leadership meeting where everyone knows something’s broken, but no one wants to touch it?

The go-to-market plan that’s been running on fumes. The “key” hire who hasn’t hit their numbers in 18 months. The product feature nobody buys but marketing keeps promoting because it’s “part of our DNA.”

And yet, quarter after quarter, nothing changes.

Here’s the truth: your business can’t afford to cling to what’s not working.

The Cost of Standing Still

When leaders delay tough calls, the losses go far beyond this quarter’s P&L.

• Over 60% of new B2B product launches fail to meet revenue targets, often because they’re built on opinions, not market data.

• Low-performing employees can drag team productivity down by 30% or more; keeping them for “one more quarter” is a silent profit killer.

• Companies that realign their GTM strategy twice a year see shorter sales cycles and faster win rates compared to those that “set it and forget it.”

Every month you leave a bad strategy or an underperforming role in place, you’re not “avoiding disruption.” You’re compounding the cost.

Why We Resist Change (Even When We Know We Should)

Most leaders don’t ignore problems out of ignorance; they do it out of discomfort.

1. Emotional loyalty: We like the people involved, so we give infinite grace instead of clear accountability.

2. Sunk cost fallacy: “We’ve already invested so much” becomes the reason to keep investing.

3. Fear of short-term disruption: We’d rather accept slow decline than trigger a bumpy reset.

4. Hope as a strategy: Believing the same inputs will magically yield new outputs.

The problem is, business outcomes don’t care about our comfort zones.

Change Is a Business System, Not a Crisis Response

The most successful companies don’t wait for revenue to crater or morale to collapse before they move. They build evaluation and adjustment into the operating rhythm.

Here’s how:

1. Run on Data, Not Drama

Gut instinct is fine for ordering lunch, not for running a P&L.

• Define clear KPIs for people, processes, and campaigns.

• Review quarterly with a bias toward evidence, not emotion.

• Use data to decide whether to double down, redesign, or shut it down.

2. Audit Your GTM Regularly

Markets shift, buyer behavior shifts, and competitors shift. If your GTM plan is older than 18 months without a refresh, it’s probably stale.

• Evaluate ICP, messaging, pricing, and partner strategy as a unit, not in silos.

• Align your market action plan with actual buyer triggers and trends.

3. Set Timelines for Improvement

If a role, program, or product isn’t hitting the mark, define the window for change.

• Skills gaps get training. Role mismatches get reassignment.

• Miss the milestones? Make the change.

• Accountability without a deadline is just a wish.

4. Fail Fast, Fix Faster

Speed matters. The faster you see what’s broken, the faster you can redirect resources.

Stop letting zombie initiatives eat budget and mindshare.

The Human Side of Hard Decisions

Making a strategic pivot or letting someone go isn’t cruelty, it’s clarity.

Keeping a failing system or role in place doesn’t just hurt numbers; it erodes trust.

• Teams notice when poor performance is tolerated.

• Customers notice when your offer feels stale.

• Partners notice when you keep backing losing plays.

Inaction signals that you value stability over success, and not in a good way.

A Simple Framework for Moving Forward

Use this Evaluate-Decide-Act-Measure loop every quarter:

1. Evaluate: Gather data on performance vs. goals. Look for patterns, not one-off events.

2. Decide: Based on evidence, choose to improve, pivot, or sunset.

3. Act: Implement changes with urgency and clarity.

4. Measure: Track the impact of the shift against defined metrics.

Rinse and repeat. Build the loop into your leadership cadence so change becomes a standard business function, not a panic button.

A Reality Check for Your Business

Ask yourself:

• What am I holding onto because it’s comfortable, not because it’s working?

• If I were starting fresh tomorrow, would I still choose this strategy, product, or person?

• What’s the cost? In dollars, time, and opportunity of waiting another quarter?

If you can’t answer without wincing, the decision’s already made. You just haven’t acted yet.

Momentum Belongs to Movers

In every turnaround I’ve led, the second the hard decision gets made, whether it’s ending a product line, replacing a leader, or rewriting GTM, the business breathes again.

Fresh ideas emerge. Morale lifts. Customers re-engage.

Not because it’s easy, but because movement creates momentum.

The alternative? Slowly drifting into irrelevance while competitors pass you by.

Bottom line: Growth isn’t just about doing more of what works. It’s about stopping what doesn’t. Change is not the enemy of stability. It’s the engine of it.

So, what’s the one thing you know needs to change? And when are you going to do it?