The next phase of programmatic advertising may not be about buying media faster—it may be about letting AI participate directly in the transaction. Butler/Till and iHeartMedia have completed what the companies describe as the advertising industry’s first agentic streaming audio media campaign, using an AI-powered workflow to purchase premium streaming audio inventory for a U.S. agricultural solutions company.
The campaign marks a shift in how artificial intelligence is being applied to advertising. Rather than using AI only for audience analysis, media planning or campaign optimization, the workflow allowed an AI agent to participate in the execution of an approved media buy, operating within advertiser-defined objectives, governance rules and human oversight.
That distinction matters.
Traditional advertising automation generally executes predefined instructions. Agentic media buying is designed to evaluate campaign goals, identify available opportunities and make or execute decisions dynamically within boundaries established by marketers.
For advertisers, the potential benefit is a shorter path between strategy and activation. For publishers and media owners, it could mean fewer transaction steps between premium inventory and buyers.
The Butler/Till and iHeartMedia campaign provides an early example of what that model looks like in audio. According to the companies, the agentic streaming audio buy delivered the advertiser’s inventory 42% more efficiently than its traditional direct-buying benchmark. Podcast inventory also produced a higher share of premium non-skippable mid-roll placements: 48% of impressions compared with 33% in the traditional plan.
Those numbers are notable because the argument for agentic advertising is not simply operational efficiency. If AI agents can navigate inventory, pricing and campaign constraints while preserving access to comparable premium supply, the technology could eventually affect how advertisers allocate budgets—not just how quickly media teams execute them.
The development comes as the advertising industry moves toward more standardized infrastructure for AI-driven transactions. The Interactive Advertising Bureau’s 2026 outlook found that 66% of buyers planned to increase focus on agentic AI for ad buying and campaign execution. The same research found that 96% of buyers were already aware of agentic AI for buying.
That adoption curve is still early. IAB’s 2026 digital video research shows that agentic AI use remains concentrated around planning, inventory discovery, optimization and decision support, while direct deal execution and negotiations remain less common.
Against that backdrop, bringing premium audio transactions into an agentic workflow represents a meaningful extension of the model beyond conventional programmatic inventory.
Audio becomes part of the agentic advertising stack
iHeartMedia is positioning the initiative as part of a broader effort to make its audio ecosystem easier to buy and measure through digital advertising infrastructure.
The company recently introduced AudioGraph, a platform intended to bring identity-based audience targeting, planning, measurement and attribution to broadcast radio. AudioGraph supports direct DSP connectivity and automated planning and transaction workflows, while allowing audience definitions to be applied across iHeart’s audio inventory.
That infrastructure could become particularly important as agencies attempt to build cross-channel AI workflows.
Programmatic display and connected TV have already established relatively mature automated buying environments. Audio has historically involved a more complicated mixture of direct sales, broadcast transactions, podcast marketplaces and digital inventory.
Agentic buying could potentially abstract some of that complexity.
Instead of asking a media team to manually compare inventory opportunities across channels, an AI agent could eventually work against predefined objectives such as audience reach, cost efficiency, frequency, geography, brand-safety requirements and performance thresholds. The human team would remain responsible for strategy and governance while the agent handles portions of the execution.
That is closer to an AI-enabled media operating layer than a conventional optimization feature.
Why publishers may care
For media owners, the promise is more complicated.
Automation can reduce transaction friction, but publishers also need mechanisms that protect pricing, inventory quality, audience data and commercial relationships. An agent that can make decisions at machine speed creates little value if every transaction requires extensive manual intervention or if buyers and sellers cannot agree on standardized rules.
The IAB Tech Lab is already working on this infrastructure problem. Its 2025 annual report highlighted an Agentic RTB Framework designed to allow real-time bidding systems, AI agents and third-party services to operate within a common architecture. It also reported work on standards for agentic ad buying.
That suggests the industry is beginning to treat agentic advertising as an infrastructure challenge, not simply an AI-product category.
For enterprise advertisers, that distinction will be important. The value of an agentic media platform will depend less on whether it can make autonomous decisions and more on whether those decisions can be audited, constrained and measured against business outcomes.
Human oversight remains the key requirement
The Butler/Till campaign does not represent fully autonomous advertising—and that is arguably the more important point.
The workflow operated under marketer-defined objectives and human governance. That model reflects where enterprise AI adoption currently stands: organizations are increasingly willing to automate execution, but they remain cautious about giving systems unrestricted authority over budgets, brand safety and commercial relationships.
Gartner estimates that more than 70% of global advertising spend will flow through self-service advertising platforms in which AI materially influences media buying, cost and outcomes by 2028. In the U.S., Gartner expects the figure to reach 80%.
At the same time, Gartner reports that only 30% of CMOs currently consider their organizations mature or fully developed in AI readiness, even though marketers allocate an average 15.3% of their budgets to AI initiatives.
That gap highlights the challenge facing enterprise media teams. Buying technology is relatively straightforward. Establishing governance, data access, measurement standards and accountability around AI-driven decisions is considerably harder.
For agencies, this could create a new role: supervising networks of specialized media agents rather than manually executing every campaign task. For publishers, it could create new machine-readable marketplaces for premium inventory. For advertisers, it could eventually mean campaigns that react continuously to changing objectives and market conditions.
The Butler/Till and iHeartMedia campaign is therefore less important as a one-off technology demonstration than as an indication of where media buying infrastructure is heading.
The broader question is no longer whether AI can recommend a media plan. It is whether advertisers and publishers are prepared to let AI transact against that plan—and whether the industry can build the standards, controls and measurement systems required to do so responsibly.
Market Landscape
Agentic advertising is moving from experimentation toward infrastructure development. IAB research shows buyer interest is already expanding, while the organization’s technology arm is working on standards designed to make agentic transactions interoperable across the advertising supply chain.
The market is also converging around AI-driven execution across major advertising ecosystems. Google, Amazon, Microsoft and other large technology platforms already use machine learning extensively in bidding, targeting, optimization and measurement. The emerging agentic model extends that automation by giving AI systems more responsibility for coordinating multi-step workflows.
Audio presents an especially interesting test case because it sits between traditional broadcast media and digital advertising. iHeartMedia’s AudioGraph strategy is aimed at connecting broadcast radio with digital-style targeting and measurement, while its relationships with platforms such as Amazon Ads demonstrate the broader movement toward interoperable audio buying infrastructure.
For enterprise marketers, the competitive question will increasingly be whether DSPs, SSPs, agencies and media owners can expose enough inventory, identity, measurement and governance data for AI agents to make reliable decisions across channels.
Top Insights
- Butler/Till and iHeartMedia completed an agentic streaming audio campaign, allowing AI to participate directly in premium inventory purchasing under human-defined governance.
- The campaign delivered streaming audio 42% more efficiently than the advertiser’s traditional direct-buying benchmark, according to the companies.
- Podcast inventory included 48% non-skippable mid-roll impressions versus 33% under the traditional plan, highlighting potential inventory-efficiency gains.
- IAB data shows 66% of buyers are increasing focus on agentic AI for ad buying and campaign execution as media automation expands.
- AudioGraph could help iHeartMedia connect broadcast, streaming and podcast inventory with digital-style targeting, measurement and emerging agentic transaction workflows.
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