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Twenty years ago, a buyer walked into a sales conversation knowing maybe 20% of what they needed to know. Today that number is closer to 70%. And with AI-assisted research, buyers are arriving with a recommendation already in hand, sourced from a system that has synthesized hundreds of data points on their behalf.

Mark Greco, Executive at HubSpot, was one of the company's earliest employees, joining at startup stage because of his background in SEO and web development. He had built those skills working at Dow Jones evaluating emerging technology and at Groove Networks, where he first met HubSpot co-founder Brian Halligan. Over the following two decades, he watched HubSpot grow from a simple inbound marketing tool into one of the most widely adopted CRM and revenue platforms in the world. He saw every major shift in how B2B companies attract, convert, and retain customers.

In this conversation on The HEX-Files, Mark walks through what the connected CRM era really means, why AI is still in its earliest stages, how buyer behavior is changing faster than most B2B organizations are adapting, and what industrial and technical companies specifically need to do about it. Keep reading for his most practical guidance. (And check out the full podcast episode here.)

“We hadn’t yet figured out that it was going to be called inbound marketing”

When Mark joined HubSpot, the company was a startup built on a simple observation: technology had advanced to the point where ordinary business owners could do things that previously required specialists. Google had established clear enough rules that you no longer needed a black-hat SEO expert. Content management systems like WordPress meant you no longer needed a custom web developer. The playing field between large companies and small ones was leveling fast.

HubSpot’s founders saw that opportunity and built a platform around it. The term “inbound marketing” came later. The underlying insight was there from the start: when a technology shift makes something dramatically more accessible, the companies that move early gain ground that is hard for later movers to recover.

Mark is candid that even inside HubSpot, nobody fully anticipated the scale of disruption that followed. They saw the opportunity to level the playing field. They did not see the complete restructuring of how companies grow that the platform would eventually contribute to. That humility is a relevant context for how he talks about AI today.

“People have struggled with those silos”

Organizational silos between marketing, sales, and service are not new. Mark has watched them persist throughout his career, driven by a combination of budget politics, separate goal structures, and technology that was simply not built to connect teams. Early CRM systems were designed for IT departments and sales management, not for the people actually using them day to day.

  • That created a familiar problem:

  • Adoption was painful

  • Implementation took months

  • Tools that were supposed to align teams often deepened the divide

  • Leadership lacked one clear view

The early signal that connected systems changed outcomes came when HubSpot noticed that companies with a CRM linked to their marketing accounts outperformed those without one. Not by a little. Leads that went into a CRM got followed up on. Leads that went into Outlook address books and Excel spreadsheets disappeared. 

That observation, more than any strategic plan, pushed HubSpot to build its own CRM. What started as a small sales enablement add-on, a tool that let you see when someone had opened your email, grew into the infrastructure for a full SaaS CRM because customers kept asking for more.

The title of Chief Revenue Officer, now common in B2B organizations, barely existed a decade ago. Mark sees it as the organizational response to the same problem the technology was solving: somebody has to own the full revenue journey, not just their department’s slice of it. The conversations HubSpot now has with clients have moved accordingly, from marketing managers and sales directors to C-suite discussions about overall commercial performance, return on investment, and strategic growth.

“AI is really not even an infant. I think it's still an embryo.”

Mark started working on AI inside HubSpot in 2017, when the company acquired a business with machine learning capabilities not yet visible to users. Since then, he has watched the technology evolve from background infrastructure into a set of capabilities that are reshaping how the platform works at every level.

His framing of where AI sits right now is worth taking seriously. Most companies are still using it for what he calls the parlor tricks: blog posts, email drafts, image generation. Those are real productivity gains, but they represent the thinnest layer of what the technology can do. 

The deeper value is in analysis, context, and decision support; areas where AI can process account histories, guide sales conversations with real-time insight, surface the right information to a support rep mid-ticket, or help a buyer compare solutions against a far broader data set than they could assemble themselves.
HubSpot’s current AI strategy runs on two tracks:

  • A co-pilot model, AI running alongside a person to offer suggestions, surface context, and reduce the cognitive load of repetitive decisions. 

  • An agent model, where AI completes specific tasks autonomously. The company recently announced agentic control of its own products, meaning AI can now take actions within the platform rather than just advising users.

When asked which HubSpot AI tool is performing best right now, Mark highlights two. The customer agent, which handles support interactions with access to a full knowledge base rather than a rigid workflow script, operates more like a knowledgeable person than a chatbot. And a contextual AI feature that pulls from a company’s entire HubSpot history, every email, every conversation, every support ticket, every content result, to provide genuinely personalized context to any interaction. For organizations that have been using HubSpot for years, Mark describes that accumulated data as something close to priceless.

“If you’re not showing up in those results, you’ve really got to be there.”

Mark spent years working in search before HubSpot, and the shift from SEO to what he now calls AEO, Answer Engine Optimization, is one he finds genuinely exciting. The fundamental change is in buyer intent. When someone searches Google, they are looking for options. When someone asks an AI engine a purchasing question, they are looking for a recommendation. That is a different kind of query, from a buyer who is further along in their decision, and the AI is giving a short list, not ten pages of results.

The implications for B2B visibility are significant. If your company is not appearing in AI-generated recommendations, you are not appearing at all for that buyer. There is no page two. The companies that show up in those results will have built the kind of authoritative, useful, well-structured content that AI engines draw from when constructing their answers. That is a different content strategy than ranking on Google, and most B2B organizations have not started adapting to it yet.

Mark also raises a point about the quality of leads that AI-assisted search generates. A buyer who has asked an AI to recommend a solution is typically far closer to a purchase decision than one who clicked a search result. They have already done the research, formed a preference, and are now validating. Getting in front of that buyer at that moment, through the right kind of content and presence, is more valuable than reaching ten earlier-stage buyers who are still casually browsing.

“The script is flipped (a lot) on how we all purchase things.”

Mark describes what he calls the two sides of a sales inquiry, each now using AI for their own purposes. On the seller side, account executives can research prospects deeply before any conversation, analyze past interactions, and get real-time guidance on next steps. That capability has been developing for a while.

What is newer is buyers catching up. Buyers are starting to use AI not just to find solutions but to analyze the procurement process itself, identify unanswered questions, and evaluate whether a vendor is genuinely meeting their needs. The information asymmetry that sellers have traditionally relied on is eroding on both sides simultaneously.

The practical consequence is that the experience a buyer has across every touchpoint now gets compared to the seamless consumer experiences they have with companies like Amazon. Disjointed handoffs, slow responses, and inconsistent information signal that the vendor is not organized enough to trust with something important.

“We’re in a very niche market. We don’t need a CRM.”

Mark has heard this objection many times. Industrial and technical companies often define themselves as too relationship-driven or too long-cycle to benefit from modern CRM. His response cuts to a specific vulnerability those companies tend to overlook.

The relationship a company has with a key account exists between people, not organizations. When the person you have spent years cultivating leaves or retires, that relationship does not transfer automatically. If a competitor has been consistently providing useful information to their successor since day one, the relationship you thought you owned has a new challenger.

The other objection is past failure. Many industrial companies tried CRM years ago and found it painful and poorly adopted. Mark's analogy is direct: CRM today is as different from CRM 20 years ago as Spotify is to AM radio. HubSpot reports 80% of new users are active within two weeks. His advice for stuck companies is simple: pick one real business problem, solve it well with a tool people will actually use, and build from there.

“I thought it was as big as inbound marketing. I was wrong. It’s bigger.”

When HubSpot introduced AI features at its 2024 Inbound conference, Mark posted on LinkedIn that it felt like 2008 again. He has since revised that upward. The 2008 shift leveled the playing field between large and small companies. The AI shift is changing the nature of the game entirely.

For sellers, AI compresses the time between insight and action. For buyers, it compresses the time between awareness and decision. For support teams, it makes deep knowledge scalable in a way that previously required large headcounts. Mark's view is simple: the organizations moving fastest are the ones treating AI as something to experiment with actively, not evaluate from a distance.

Explore more ideas and practical advice on this topic.

Catch the full conversation with Mark Greco on The HEX-Files, HexaGroup’s energy marketing podcast for leaders who want real results.

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