Brands and agencies are embracing AI adoption in high numbers, but the organizations that struggle to update processes and workflows could impact revenue. These organizations are confident in the benefits of AI transformation long-term, but have hit barriers to broader adoption.

“Most marketers and most agencies at best have a bunch of trials going on in pockets of their organization,” said Matt Spiegel, EVP of TruAudience growth strategy at TransUnion. “The use of AI at an enterprise level to change marketing is extremely nascent.”

Modest advances

The vast majority of organizations have updated some marketing processes with AI, but far fewer have made the kind of changes that impact ROI.

For instance, three-quarters of marketers found AI-enabled marketing efforts have reduced manual effort or time spent on marketing tasks, according to a TransUnion and UTA Advisory study released this week. However, a much lower percentage of marketers have made breakthroughs on reducing media waste (44%), improving conversions or response rates (35%), or reaching more of the target audience at similar spend levels (30%), per the TransUnion study.

“I think there’s a lot of questions around actual, full end-to-end workflows, where humans aren’t touching the process,” said Spiegel. “No, I haven’t seen that, and I doubt it becomes real anytime soon.”

Readiness ratings

Looking forward, many marketers are optimistic about the lasting impact of AI adoption. Some 64% say they’re confident their organization will achieve their AI-enabled marketing goals, per the TransUnion study.

But, only 42% rate people readiness in their organization as high, while just 36% rate their data and process readiness as high.

“Everybody very much wants to get there, but the gaps that exist are twofold,” said Spiegel. “One, it turns out too many people still haven’t fixed their data structure, so they don’t have the right insights to pull together easily. Only then, can you get into organization, design, and process flow, which you also have to redesign as well.”

Fragmented data

Marketers show frustration when it comes to data used in AI workflows. This data limitation keeps organizations from onboarding broader agentic workflows that could, for instance, save money spent on media to convert customers and improve ROI.

• Some 42% reported incomplete or missing data, according to the study.
• Another 69% said data blind spots within walled gardens limit their ability to evaluate AI effectiveness.
• A full 70% said cross-channel blind spots make it difficult to understand AI's impact across the customer journey.

“If you live in a world where your customers or prospects, broadly your consumer insights platform, if that isn’t actually a connected set of information, you have different silos of data,” said Spiegel. “Then, whenever you’re feeding an agent some of that information, then you’re feeding it incomplete information. And then what you end up with are outcomes which are less predictive than you had hoped, that maybe aren’t full-on wrong. But, best-case scenario, they’re marginally improving [instead of being] the game-changer you want.”

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