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2025 was the year AI went from nascent to normal.
Every media team, from media planners to data engineers to brand leads, started testing what AI could actually do for their day-to-day work. Some experiments flourished, some failed, but greardless of the outcome, many companies realized that adopting AI is about more than using a tool; it’s about changing how work happens.
We’ve spent the past year helping media companies deploy AI inside real workflows, in the messy, high-pressure environments where deadlines, clients, and revenue are on the line. Now that teams understand the basics, expectations are changing. Leaders want measurable impact, not experimentation, while teams want AI that actually fits into their processes, not outside them.
With that shift in mind, here’s where we believe the industry is headed in 2026.
As foundational models continue to improve, the performance gap between them is getting smaller. Gartner and McKinsey have both noted this “model convergence,” and it’s reshaping how companies think about AI investment.
The takeaway:
Access to a model isn’t a differentiator anymore.How you use it — your data, your workflows, your speed to action — is what creates real value.
Vendors selling one-off models without context or infrastructure are going to feel more pressure than ever.
2023–2024 saw a lot of enthusiasm around giving teams a general-purpose chatbot and hoping productivity would skyrocket. But most organizations learned the same thing: it rarely works that way.
Forrester reported that over 70% of early gen-AI pilots didn’t reduce operational work because the tools weren’t connected to the data or systems people actually rely on.
Companies are now realizing:
Next year, generic assistants will be replaced by AI that’s built for real jobs inside the business.
Across industries, teams are shifting toward AI that understands their world.
BCG found that domain-adapted models outperform general models by 30–50% on actual business tasks, which tracks with what we’re seeing across our customers too.
Why the shift? Because specialized AI:
It’s becoming clear that value comes from context, not generality.
By the end of 2026, we expect a noticeable separation between media companies that operationalize AI and those that don’t.
McKinsey reported up to 40% productivity gains when AI is embedded directly into workflows, not haphazardly attached on top of them. And we’re seeing that range hold up in practice.
This creates a two-speed industry:
From here, the gap will only further widen.
Brands are getting more familiar with what AI can (and should) do. As a result, they’re expecting partners (see: agencies) to deliver faster, more efficiently, and with better insight.
Forrester’s 2026 agency research shows that 85% of CMOs plan to review media agency contracts with the expectation that AI should already be improving output.
This creates a new reality:
Real capability becomes the deciding factor.
Despite the complexities the industry has experienced with AI in the previous year, the theme for 2026 is remarkably simple: AI only creates value when it’s connected to real work connected to real people.
The media organizations that lean into workflow-native, data-connected, domain-specific AI will move faster and outperform their peers, while the ones relying on generic tools or disconnected pilots will feel increasing friction.
If you want to find yourself in the former of those two groups this year and beyond, check out this one-minute video on how Akkio works.
Transform your campaign workflows with powerful AI that delivers measurable results.