The next wave of AI isn\u2019t just about smarter tools, it\u2019s about autonomous ones. And that poses some sticky questions: who is really in control when agents are instructing other agents, and who is accountable if they make mistakes?<\/p>\n
That\u2019s a question that\u2019s starting to keep some media and ad execs up at night.\u00a0<\/p>\n
Their fears come amid a rise in the number of tools: from Salesforce to Adobe to Microsoft and Optimizely, platform providers are introducing agentic AI tools that don\u2019t just assist users but act on their behalf. These systems make decisions, learn from behavior and adapt automatically.<\/p>\n
Meanwhile, protocols like Model Context Protocol<\/a> and Google\u2019s open-source A2A (agent-to-agent protocol) are laying the groundwork for AI agents to log into websites and use APIs on behalf of users, stressed Marc Maleh, chief technology officer at Huge. Over time, these agents can run jobs automatically in the background \u2014\u00a0like swapping out ad creative when the weather changes<\/a> in a given region, he added. But, as agents increasingly take instructions from other agents, the murkier the data and accountability trail gets.<\/p>\n Maleh believes this isn\u2019t theoretical, but a concrete inevitability. And the data seems to point that way. AI agents are flooding the web with (more) non-human traffic, according to the latest report from TolBit, released last week. And they\u2019re starting to outstrip human traffic: TolBit data saw a 9.4 percent reduction in human visitors between Q1 and Q2. The report also pointed to an increase in activity from autonomous headless browsing, which AI engines like Perplexity are using, but appear as human visits in site logs, TolBit claims.<\/p>\n Maleh believes businesses need to put guardrails in place so they can avoid potential instances where AI agents run wild. \u201cIf you\u2019re a brand and you don\u2019t have a governance framework in place and you have a multi-agent system, and you didn\u2019t think through, \u2018Well, I\u2019m accessing Marc\u2019s credit card information with this agent, and that agent is making an assumption that this other agent can access that same information \u2014\u00a0how am I being informed about that?\u2019 Suddenly, I bought a product I didn\u2019t want to buy because this multi-agent system did so. So it\u2019s not just a tech or a data problem, it\u2019s also a brand problem,\u201d he added.<\/p>\n When Huge has engaged in data and AI work with clients like NBCUniversal and Planet Fitness, this topic has come up frequently. Conversations have ranged from how model decisions get documented and communicated, to what mechanisms ensure traceability of agent actions \u2014 like audit trails and data logs. Accountability has been another hot topic: if an agent acts with bias, if it\u2019s had harmful outputs, been mis-executed, who is on the hook: the agency, vendor, brand or end-user agent?<\/p>\n How consumer or customer data privacy is protected is another dominant conversation, along with establishing what controls prevent collusion or unintended outcomes when agents interact with third-party agents, he added.<\/p>\n Orchestration doesn\u2019t guarantee governance\u00a0<\/p>\n Agentic orchestration platforms, like Adobe\u2019s Agent Orchestrator, or Microsoft\u2019s Copilot Studio\u2019s orchestration layer, do bake in governance features, like permissions, logging, intervention points and audit trails. But it\u2019s still possible to have orchestration without governance \u2014 agents passing tasks with no accountability.<\/p>\n Agent orchestration is about how agents run; agentic governance is about whether they run responsibly. So while orchestration can enable governance, without clear policies, it risks becoming automation without accountability.<\/p>\n \u201cIt\u2019s only a matter of time before consumers start to care how their data is being used by multi-modal agentic systems, according to Clive Henry, head of partner solutions at Adobe.\u00a0<\/p>\n Just as personalization sparked data privacy regulations like the General Data Protection Regulation and California\u2019s Consumer Privacy Act, agentic workflows are in their early days \u2014 the rules are still being developed, but the aim is better outcomes for consumers, stressed Henry.<\/p>\n \u201cCompanies that are going to open up their web experiences to these kinds of agentic flows, they\u2019re eventually going to want to know that they\u2019re safe from legal recourse from consumers or consumer groups, based on how they receive and store these kinds of data,\u201d said Henry.<\/p>\n Pushing for agentic governance frameworks within businesses is what\u2019s needed to ensure the necessary guardrails are in place, he added.\u00a0<\/p>\n For media companies, it\u2019s just as big a risk as it is for advertisers. Say, for example, someone is choosing what to watch on TV. In theory, an agent could log into their streaming apps, scan their libraries, and return recommendations based on your mood, favorite genres, or actors. But that raises questions, stressed Henry. If an agent is doing the browsing, who controls the ads that normally appear on these platforms, and what data is used to target them? And if another person uses the same interface, will that agent apply the same username and password as the previous person who watched something earlier?<\/p>\n \u201cI think these are the kind of problems that would lead a media company that has a subscription platform to say \u2018I would prefer not to open up my interfaces to agents until we have standards for these kinds of things,\u2019\u201d he added.\u00a0<\/p>\n Will marketers be advertising to humans or agents?\u00a0<\/p>\n CMOs need to ensure that they are working to ensure the knock-on effect to consumers is raised early on, that this isn\u2019t left solely to CTOs and CIOs, according to David Berkowitz, founder of AI Marketers Guild, a community for marketers, brands, and technologists focused specifically on how AI is changing marketing. \u201cThis could radically shape a world of \u2014 are you even creating messaging for humans \u2014 or bots? And if it\u2019s just seen as some tech policy or implementation, then it\u2019s very possible the CMO is going to get left out,\u201d he said.\u00a0<\/p>\n Perplexity\u2019s Comet browses autonomously to create a daily digest of news. Based on Tolbit\u2019s tests, it looks just like a human using Chrome. Perplexity\u2019s Comet browser doesn\u2019t identify itself as an AI tool in site logs, in the tests Tolbit\u2019s team ran. Instead, it fetches pages under a standard \u201cChrome\u201d user agent and uses the human\u2019s residential IP. So even if a user only sees a summary, publishers\u2019 analytics record it as a normal (human) visit \u2014 when in fact it\u2019s the AI doing the browsing and clicking in the background, claimed Tolbit\u2019s report released last week.\u00a0<\/p>\n \u201cAll parties of sorts, whether you\u2019re a human business, whether you\u2019re an advertiser, a publisher, an agency, is going to have some kind of agentic representation, and some way to have an automated version of that entity that can make decisions and act on the party\u2019s behalf,\u201d said Berkowitz.<\/p>\n AI posing as people shows why agentic guardrails matter.<\/p>\n If agents are more proactively going out and trying to find the right customers, the right visitors, and the right audience targets, then that could radically change advertising, marketing, media and more, added Berkowitz. \u201cHow do we prepare for a future where there are different agents \u2014 essentially bots \u2014 talking to each other, often without human intervention? There are a lot of different rules in play here and I don\u2019t think we want to be in a situation where we just like, let this happen, and see where this goes,\u201d he said.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"The next wave of AI isn\u2019t just about smarter tools, it\u2019s about autonomous ones. 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