Over the past few months, I’ve spoken with several prominent CMOs at companies ranging from early-stage, AI-native startups to SaaS-era scale-ups, as well as marketing consultants and agencies serving prominent tech brands. My question was straightforward: How is AI changing the KPIs you report upward?

I expected, or perhaps hoped for, a new atomic unit quantifying marketing’s value, like the MQL was for the Inbound era. But it never came. For now anyway, AI appears to be transforming how marketing teams operate — but not necessarily what they’re measured on. The playbook has changed, but not the scoreboard.

Every leader I spoke with agreed that AI has reshaped their workflows (data flows, campaign development, account enrichment), content strategies, and speed of execution. Yet when it comes to the metrics they report to their boards, almost nothing has changed. (Actually one CMO felt like they did have a new, albeit unofficial, KPI: How many AI tools the marketing team is testing. As you might expect, this leader felt like being measured on tool deployment vs. business impact was akin to looking through the wrong end of the telescope.)

Ultimately, most marketing leaders said their primary KPIs still ladder up to the same goal as prior to the rise of AI: driving predictable revenue. One executive put it bluntly: “Do the right thing for the business — that hasn’t changed.”

Even in AI-native companies, where one might expect a new KPI to emerge first, the metrics that reach the board deck are consistent with SaaS businesses: pipeline sourced, lead-to-opportunity and opportunity-to-closed/won conversion rates.

The Cockpit Dashboard is Changing, Even if the Seatback Dashboard Isn’t

I often say CMOs have two dashboards – the operational one they use to fly the plane, and the synthesized one they use to assure the passengers they’ll land on time. Think of them as the pilot’s instrument panel and the passengers’ seatback display. Each serves a different purpose. While the seatback display may remain unchanged, the data marketing teams use to run the business is evolving.

Several CMOs described abandoning traditional top-of-funnel metrics like organic traffic and MQLs, focusing instead on their presence in LLMs. One leader said their board’s biggest concern is “whether or not the company shows up ChatGPT.”

That’s an entirely new kind of visibility metric — one that didn’t exist two years ago. But even this innovation rolls up to familiar outcomes: capturing purchase intent.

Elsewhere, marketing leaders are experimenting with AI-powered enrichment workflows that automatically capture account-level insights or even fill in invisible form fields. Again, these may be new plays in marketing’s playbook — but they ladder up to something familiar: conversion efficiency.

Green shoots?

A few emerging metrics hint at where the next wave of change may come from.

At one AI-driven company, the CMO added a new funnel stage — “evaluation” — to better capture the behavior of users exploring the product directly. At this company, marketing is beginning to resemble customer success in that it’s responsible for identifying “a-ha” moments that correlate to purchase or expansion, and then driving users into those features.

Another leader is developing a new KPI entirely: a “propensity-to-buy” score that combines external behavioral signals and unstructured call data. If this metric sticks, it could become an upper-funnel target for the AI era.

And across the board, there’s greater attention to speed, efficiency, and productivity — though few CMOs are currently reporting on these as KPIs.

AI as a Force Multiplier

One CMO described AI as a “force multiplier.” It hasn’t changed what their team aspires to achieve, but it has changed the rate at which they pursue targets. They develop campaigns more quickly, more easily produce content, and capture more signals to inform targeting strategy. Taken together these three AI-augmented practices allow this company to launch more campaigns concurrently to more and more relevant audiences.

But the outcomes — pipeline sourced, closed/won velocity — are consistent with the past.

Some CMOs warned of “too much of a good thing.” In addition to the marketing leader who quipped about the phantom “tools being tested” KPI, another cautioned that AI can introduce friction: “Sometimes AI interferes with productivity — we now have six tools to visualize an org chart before just using PowerPoint.”

Interestingly, as AI reshapes discovery — especially in the “zero-click” world of LLM answers — several leaders pointed to a renewed emphasis on brand. With search advertising less effective and content increasingly unclickable, marketers are rediscovering the importance of being known and trusted before the query is ever typed.

That credibility, built through public content, becomes the foundation of visibility in the AI ecosystem. Some felt it may give rise to a new era of PR, as LLMs often reference off-domain mentions of a brand.

What’s Next: Maybe … More of the Same?

All signs point to a lag between technological change and measurement change. The tools are evolving faster than the metrics. One CMO estimated it’ll take another six months before AI-related KPIs make their way into board decks; another wondered if a change would, or even should, happen at all. In the end, marketing’s goal is to help generate revenue. AI may have altered how we pursue that goal, but not the goal itself.