Your sellers spend most of their week not selling. AI can change that

How much of the week goes on selling?

In 2024 Salesforce found that sales reps spent 70% of their time on non-selling tasks. Its 2026 survey puts selling time at 40% for the average seller. Different samples, same story: most of a seller's week is admin. Sponsorship makes it worse, because every proposal is bespoke, every renewal needs a recap and every activation needs reporting that someone compiles by hand. Smaller rights holders feel it most, since a small partnerships team can't afford to spend its week formatting slides.

The productivity evidence for generative AI is now solid. Workers using it reported saving 5.4% of their work hours in the previous week, about 2.2 hours for someone working 40 hours. In a study of 5,179 customer support agents, access to an AI assistant raised issues resolved per hour by 14% on average, and novice and low-skilled workers improved by 34%. That last number is the one I'd underline: newer sellers stand to gain the most.

A person still closes the deal. AI's job is to get that person into the room more often.

Where sellers expect AI to help

Sellers already know where AI helps. In Salesforce's 2026 survey, they expected AI agents to cut prospect research time by 34% and email drafting by 36%. More than half (54%) said they'd already used agents, and top performers were 1.7 times more likely than underperformers to use agents for prospecting.

Map that onto sponsorship. Prospecting means scanning which brands are launching, expanding or spending in your market, proposals mean matching your inventory to a brand's objectives and writing it in their language, and reporting means pulling reach, content and activation results into a recap a marketing director will actually read. AI can draft all three, and it can help turn your fan data into insight, so sellers walk into sponsor meetings knowing the audience and able to show exactly what a deal delivers. It can also keep your inventory, rate card and past case studies in one searchable place, so every proposal starts from your best previous work, never a blank page. Your team still decides what to say and who to say it to.

What do the teams getting value do differently?

Using AI isn't the same as profiting from it. BCG found that 74% of companies have yet to show tangible value from their use of AI. The leaders put 10% of their resources into algorithms, 20% into technology and data and 70% into people and processes. So the algorithms, the part most people picture, get the smallest share. Sales and marketing account for 20% of the AI value the surveyed companies generate.

For a sponsorship team, the lesson is simple: the tool matters less than the workflow around it. Pick the work, change the process and train the people, then measure what moved.

We've seen what disciplined adoption can deliver. A Tier 1 European sports club saw a 4.8% EBIT uplift within 12 months, with the gains coming across 10 distinct AI initiatives. I'd back focused use cases with clear owners over a company-wide licence that nobody owns.