How are UK businesses using AI in sales and marketing?

Marketing and sales run more AI than any other function, and can prove less of it. In aibl’s survey of 755 UK mid-market business leaders, the marketing, sales and customer experience group reports the lowest measurable ROI of any functional pillar at 45%, alongside the highest shadow AI use at 64%. AI is running across these teams. Whether it pays is the part most still cannot show.

Why marketing and sales show the lowest return despite the most activity

Revenue teams lead the field on AI activity and trail it on proof. In aibl’s survey of 755 UK mid-market business leaders, marketing, sales and CX leaders report 45% measurable ROI, the lowest of the functional pillars, and the highest failure rate at 85%.

On the adoption map they are broad but shallow: AI running in many places, little of it scaled. The reason is timing. Revenue teams measure activity early and outcomes late, so the spend lands before the proof does, and the return shows up as anecdote rather than a number the CEO reviews.

The attribution gap is the real problem, not the tools

The missing piece is the line connecting AI spend to revenue in a form the finance team accepts. Marketing and sales adopt fast, but the governance that would measure the result lags: the pillar’s jump from a written policy to an enforced one is the smallest in the survey, at 8 points.

Build the attribution layer before scaling further, so conversion gains show up as return rather than anecdote. Our guide to building an AI business case your CFO will approve covers how to write the success metric and baseline in before you spend.

Shadow AI is highest in revenue teams

Marketing and sales carry the highest shadow AI use of any function, at 64%. That is a demand signal as much as a compliance risk: people reach for unapproved tools when the approved route is slower than the deadline.

Across the survey, shadow AI falls from 75% where governance is weakest to 35% where it is mature. The fix is speed, not policing. Make the sanctioned tool quicker to reach than the workaround. Our piece on why staff use unapproved AI tools sets out the pattern.

Where AI is genuinely working in marketing and sales

The gains are real where customers feel them. Among leaders with a customer-facing view, 64% report better conversion and 62% faster response times. The work is landing; what is missing is the measurement that turns it into a return the board can see.

So the task is not more tools. It is connecting the conversion and response gains you already have to the AI spend that produced them, in a form that survives a finance review.

What this means for the CMO

Start with attribution, not another tool. Decide the one metric that proves marketing AI is working, write down where it stands today, and measure against it a quarter later.

Then govern the tools your team already uses: a fast, approved route cuts the shadow AI that sits at 64%. And put a named owner on the outcome, because across the survey AI with no single owner returns just 18%. Our analysis of who should own AI covers the ownership data.

Frequently asked questions

Read the full State of UK AI Adoption 2026 report →

Closing an attribution gap takes measurement capability most marketing teams do not hold in-house. The AI Enablement Directory lists UK partners in data and analytics, and AI implementation and deployment. New findings land each Friday in aiblBRIEF, our free weekly newsletter.

About the research: the State of UK AI Adoption Survey 2026 was run with aibl’s research partner Executive Summary. It covers 755 UK mid-market business leaders in organisations with revenues of £20m to £500m, fielded January to March 2026. Every figure above describes the leaders surveyed.