Pixar's animated classic, The Incredibles, superhero villain Syndrome says he'd sell superpowers to everyone — and "when everyone's super, no one will be." It is how B2B go-to-market (GTM) feels right now. AI ships to your competitors the same day it ships to you. Everyone in your category has access to the same tools as you do.
Yet the problem isn’t necessarily access to AI; it’s that access isn’t a strategy.
A 2025 study by MIT found that 95% of generative AI pilots deliver zero measurable return. S&P Global added their findings to the ring, saying that 42% of companies had scrapped most AI initiatives last year, up from 17% the previous year. Which begs the question, how can GTM teams make the leap from AI fluency to AI impact?
I recently caught up with HubSpot’s CEO Yamini Rangan on our Under The Hood podcast to discuss what separates the businesses achieving outcomes from the ones creating activity and how they are rebuilding their GTM for the AI era.
Season 5, Episode 1 of Under the Hood, featuring Yamini Rangan, CEO at HubSpot
How We Deliver Value Changed, Not Why
The fundamentals really haven’t changed. Talk to any CRO and they name the same three goals that they did five years ago. "They want to build pipelines, close deals, and automate tasks for their teams so they can grow," says Yamini. “What has changed is the involvement of applications and agents to deliver those outcomes."
Yamini discussed with me how SaaS used to be a tool you operated. The software sat there and a human drove it, pointing, clicking, navigating, and the results came from human effort channeled through the interface. In the AI era, the software does the work itself. You're not operating an instrument anymore; you're delegating an outcome.
What’s most important is the speed at which outcomes must arrive. I call this #ROAI. It’s ROI that has to be measured and provide compounding value, where week one's output compounds into week two's and so on.
Yamini points out that “what [HubSpot] customers need is to deploy AI and technology quickly and get fast outcomes. They need to be able to see that AI is working in their environment…and that means the way we as sales, marketing, and service professionals interact with customers is changing pretty dramatically.”
I have always advocated that there are no more siloed marketing and sales teams; they are part of the revenue team. Now the AI era is blurring sales and customer success, collapsing pre-sales and post-sales into one seamless motion. To make sense of this, it helps to understand the ways buyer research and evaluation has evolved.
Buyers Engage AI Before They Engage You
As marketers, our content now has two audiences; the human and answer engines. The old marketing playbook is played out. We can’t rely solely on publishing a blog, ranking it, capturing email addresses, and nurturing the leads. Buyers are instead finding you in their social feeds, in online communities, such as Reddit, and by directly asking questions of AI-powered answer engines, such as ChatGPT, Gemini, Claude, Copilot, and Perplexity.
Here’s why all this matters: ChatGPT claims it handles ~2.5 billion queries a day and 93% of Google AI Mode searches end without a click. What this means in practice is that marketing has to diversify their channels and appear wherever their buyers are unpacking problems, finding solutions, comparing vendors, and more.
Crucially, it’s about meeting the needs of high-intent buyers — and it works. Yamini shared that HubSpot has been adopting AEO (answer engine optimization) for almost two years and reports AI referred leads are converting 3x better than organic search.
Then, having done deep, agent-assisted discovery, those buyers finally engage sales. For the unprepared sales rep, this means the buyer is much more informed about the rep's business than they are of the buyer’s. Opening the call with "tell me about your business" is doomed to fail.
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Aligning Sales and Customer Success
When it comes to value being activated immediately, sales and customer success can't run as a relay team. The handoff is where the promises made in the sale can quietly fail to materialize. Sales and customer success often carry different incentives, and misalignment shows up as friction the customer feels. Yamini shared with me that HubSpot brought both teams under one leader this year for exactly this reason. Someone needs to go back and confirm that the promise landed.
A couple of years ago I designed a growth model called the Infinity Track® that delivers a frictionless customer journey and breaks down the siloes between marketing, sales, and customer success.
The Infinity Track ®
The outer loop of branding and positioning cuts through the sea of sameness of content, especially “AI slop.” The inner loop on the right is where marketing, sales, and customer success drive outcomes as one unit.
Marketing uses context for hyper-personalized communications, creates content at scale, and introduces AI Agents to nurture leads conversationally. Sales applies AI to read buyer intent signals, time the message, and deliver thoughtful solutions. Customer success then combines human expertise and AI to run handoffs and real time updates, and ultimately delight the customer.
Bringing it all together, the Infinity Track® allows once separate teams to leverage AI to optimize the buyer journey and its outcomes, with a shared view of success.
Three Stages of AI Adoption — Where Do You Sit?
Most companies can tell you which AI tools they've trialed or bought. Few can tell you what stage of maturity they're actually operating at.
McKinsey’s State of AI in 2025 Report states most organizations are experimenting with or piloting AI, and while there’s high curiosity, nearly two-thirds are yet to scale AI across the organization. What experimentation looks like will be different for each and every business, even from function to function.
Experimentation typically involves individuals trying things — useful tests, ad hoc, yet invisible on any P&L. Others go beyond experiments by putting AI alongside people in the flow of work, changing how the job gets done rather than just how fast. This can involve removing manual steps from tasks that already existed.
The more AI mature a company is, the more agents and processes will support the customer journey, instead of a single function. The results really take off when the value builds on itself: every interaction adds context, that context makes the next output better, and the gap between you and a competitor with the same tools widens.
Knowing which stage of adoption you are at matters because each level of maturity has different priorities to work towards and constraints to stay inside of.
Yamini categorizes AI adoption in three stages:
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AI fluency — individual productivity created with AI tools
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AI impact — team-level productivity tied to commercial numbers
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AI maturity — institutional productivity, measured in revenue per employee.
Let's break those down:
AI fluency is where you measure metrics like a percentage of the team using AI on a daily or weekly cadence. Yamini shared that HubSpot ran it as a transparent dashboard with healthy inter-function competition. It was useful, she said, but it doesn’t really make the company grow.
AI impact is where you reimagine one process and hold it to commercial numbers. Here you measure things like pipeline created, days to close, leads generated, and tier-one tickets, depending on your goals.
AI maturity is where you focus on one metric: revenue per employee. Yamini was candid with me in saying that HubSpot isn't quite there yet even though the team is averaging a 96% daily AI use.
Yamini says, “There's a ton of AI slop, and there's a ton of AI output, but you really want to drive outcomes." Want to increase yours? Yamini suggested, "Start with the biggest goal and the blocker to that goal."
Bridging the Gap from AI Fluency to Impact
Whether you are in a marketing, sales, or service role, where you start depends on where the goal or blocker is. Maybe you are challenged with dormant accounts and thin data. Identify the problem, strategize the approach, and then apply tech like HubSpot’s suite of AI agents. Maybe like many organizations you are seeing a declining top of funnel or reduced web traffic. You could look at deploying an AEO strategy or trialing channel diversification.
Remember that the goals haven't changed — marketing still builds pipeline, sales closes deals, service retains. As Yamini concluded in our podcast chat: "The winning teams will be the ones that stayed disciplined about the outcome instead of chasing every new solution."
