By Alistair Goodman, Cofounder of Emodo
The stock exchange defined by frantic brokers waving papers and shouting bids across trading floors disappeared decades ago. Today, computers execute trades in automated markets where every millisecond matters.
Advertising has been sliding toward a similar model since the introduction of programmatic buying. Over the next two years however, artificial intelligence will accelerate that transition, in the same way that the introduction of program trading did on Wall Street in the 1980s. Tasks that currently require manual coordination across platforms (campaign operations, optimization, reporting, measurement) will be handled by machines designed to interpret signals and act in real time.
The timing of this shift is not accidental. Advances in generative and agentic AI are allowing machines to interpret context, synthesize multiple data signals and make probabilistic decisions far more quickly than traditional rules-based systems. At the same time, the complexity of the digital advertising supply chain has reached a point where human coordination alone cannot scale efficiently. As digital media investment approaches a trillion dollars globally, the industry is increasingly motivated to build protocols and infrastructure that allows machines, not people, to interpret opportunities and execute decisions in real time.
On the programmatic side, this transition is likely to coalesce around three emerging protocols: the Advertising Context Protocol (AdCP), which defines the conditions surrounding an ad opportunity; the User Context Protocol (UCP), which communicates audience and identity signals; and the Agentic RTB Framework (ARTF), which enables automated systems to negotiate and transact during the ad call.
Together, these protocols represent something more significant than incremental automation. They point toward the emergence of an environment where machines interpret context, evaluate opportunities and execute decisions within the roughly 100 milliseconds of an ad request – a near complete automation of programmatic worlflows.
Much of the fragmentation that defines digital advertising today exists because humans are stitching together dozens of tools, intermediaries and data layers. As decision-making becomes increasingly automated and protocol-driven, the system will naturally favor fewer layers, clearer signals and standardized methods for machines to communicate.
At a time when global digital ad spending is approaching $1 trillion, that kind of infrastructure shift has meaningful implications.
The likely outcome is a shift away from static targeting and preconfigured line items toward real-time decisioning and negotiation, where intelligent agents continuously optimize media, creative, and pricing on behalf of publishers and advertisers—unlocking more efficient markets, higher signal fidelity, and new forms of value exchange across the open internet. This should also reduce the need for long tail of experimental intermediaries that rely on small test budgets and manual campaign management. When planning, activation, optimization and reporting become increasingly agentic, the economics of running $10,000 to $20,000 pilot campaigns through complex stacks begin to break down.
The opportunities that remain will likely concentrate in two places: platforms that provide the infrastructure and AI-powered protocols underlying the ecosystem, and agentic, self-serve systems that allow brands and smaller advertisers to participate directly.
In that sense, the future of programmatic may not simply involve more automation. It will involve a smaller, more standardized ecosystem where AI systems negotiate the advertising marketplace on behalf of advertisers and publishers at machine speed.
