A 2026 Epsilon benchmark survey of 257 marketing decision-makers, conducted with Fuld Inc., points to a wide gap: most teams deploy AI for internal efficiency, then evaluate it on revenue. Forrester data highlights a similar tension across firms.
Seventy-one percent said their primary use of AI is productivity and efficiency. Only 9% named revenue generation. Yet when asked how they measure AI performance, 46% pointed to revenue.
That mismatch matters. It’s like installing a tool to speed up internal workflows and then judging it by whether it lowered acquisition costs. The activity is back-office; the scorecard is customer-facing.
Why this matters for marketers
AI answer engines and generative search have changed the mechanics of attention. You cannot simply buy visibility inside an AI-generated answer the way you could buy a search ad. You have to earn it through reputation, relevance, and proof that an AI system deems worth citing.
That shift is already showing up in adoption data. GEO — AI-powered search optimization — is now the most widely used AI tool in marketing at 54%, ahead of conversational AI and data analysis. A year earlier, content-generation tools ranked near the top; this year they did not crack the top 10.
If your brand isn’t visible inside the AI answer, productivity gains rarely convert to revenue. Forrester’s research found firms with high AI use report meaningful efficiency gains, but cost savings of under 10% and revenue gains of under 5%.
Close the gap with customer value
The fix is not another AI dashboard. It is asking a sharper question before choosing any AI use case: Does this make the business more valuable to customers, or just faster internally?
- Reframe the scoreboard. Revenue should measure customer-facing AI, not workflow automation alone.
- Prioritise AI visibility. Track how often your brand appears in AI-generated answers and referral traffic, not just content output.
- Use AI as an amplifier. The Playing to Win framework is a useful lens: AI should amplify an existing winning strategy, not replace strategic thinking.
- Close the perception gap. C-level marketers rate their organizations as extremely mature in AI at 67%, but only 33% of senior managers agree. Leadership and practitioners need to look at the same scoreboard.
Some signals are promising. Adobe found AI referral traffic to U.S. retail sites grew 693% year-over-year during the 2025 holiday season and converted 31% better than non-AI traffic. Delta CEO Ed Bastian has linked AI to long-term profitability gains through better pricing and scheduling — but anchored those gains to a better customer experience.
What to watch next
As the AI tooling layer becomes commoditised — Menlo Ventures reports 76% of AI use cases are already purchased rather than built — simply using AI no longer creates differentiation. The brands that win will be those that connect AI productivity to customer value and measure both on one coherent scoreboard.
Source: MarTech
