Why advertisers now want transparent AI in programmatic buying

The most interesting shift in programmatic isn’t happening in product roadmaps or conference keynotes. It’s happening in RFPs — the formal requests companies use to evaluate and choose tech partners. Buyers have stopped treating AI as a box-ticking feature and started treating it as core infrastructure that deserves real scrutiny.

What’s changing is not just how AI is described, but how it is evaluated. Buyers are increasingly interested in whether automated systems can be understood, guided, and governed; not simply whether they exist.

That shift is now reshaping how advertising technology is discussed in procurement conversations and long-term platform decisions.

Why procurement is asking deeper questions

As AI takes on a more central role in advertising decision-making, procurement teams are applying more rigorous standards to how these systems are assessed. Automation is no longer viewed in isolation, but as part of the operational and governance framework that underpins spend, performance, and accountability.

That perspective is shaping enterprise buying.

And as AI extends into planning, targeting, and distribution, marketers are leaning on agencies not just for execution but to interpret the logic behind AI-driven decisions. Outcomes alone aren’t enough — explanations matter.

The real problem: A decade of opaque optimization

Programmatic has carried a chronic imbalance for years: scale increased, but visibility did not. As optimization systems became more automated, many of them turned inward. Key components were sealed off from buyers: signals weren’t disclosed, bid logic couldn’t be inspected, override controls were minimal, supply-path decisions were hard to trace, and identity handling operated behind closed doors.

The industry gained speed but lost clarity. And the consequences are familiar: erratic pacing, unexplained performance swings, inconsistent efficiency, and long troubleshooting cycles when campaigns behave unpredictably. The opacity didn’t just limit insight; it eroded control.

The new expectation: Transparent AI

As AI plays a larger role in advertising decision-making, expectations around oversight and governance are evolving. Rather than focusing solely on whether a platform uses AI, buyers are increasingly interested in how automated systems behave in practice and how much visibility and control practitioners retain as those systems operate.

In this context, discussions are shifting toward understanding the kinds of inputs that influence optimisation, how automated behaviour changes over time, and where human judgment can be applied to guide or constrain outcomes. There is also growing interest in how identity signals are treated within optimisation workflows, and how supply-path decisions contribute to performance and efficiency.

Taken together, these considerations reflect a broader shift toward treating AI as part of an operational framework rather than a standalone feature. As automation becomes more central, the ability to understand and manage its behaviour is increasingly viewed as an important aspect of responsible platform adoption.

The future of the craft

Now, a different class of advertising systems is taking shape.

Decision components are modular, making it possible to see how each contributes to outcomes. Interfaces expose the relative weight of signals. Traders can adjust bid factors and constraints. Supply paths can be traced and compared. And mid-flight reporting shows not just what changed, but what triggered the change.

The idea that AI will replace traders confuses scale for strategy. Programmatic has always been about making better choices with imperfect information. The teams who thrive will be the ones who treat AI as an instrument of analysis, not an autopilot. They’ll know which signals genuinely move outcomes and which are noise. They’ll spot when a system needs intervention and when it’s better left alone. They’ll read optimization patterns with the same fluency that planners once read media plans.

Advertisers aren’t resisting automation. They’re pushing back on opacity. The old model of sealed optimization loops doesn’t fit a world where identity is fragmented, supply paths are being rebuilt, and every budget line is under examination.

Traders aren’t being replaced, but the black box is. The future belongs to systems that show their reasoning.