AI-agent era could reshuffle big-tech winners, Div Garg says, warning Alphabet and Meta may face outsized risks

The “AI-agent” era, in which software systems can take actions toward goals rather than only generate text, may create a different winners-and-losers landscape than the one investors have focused on so far. In an interview published by Yahoo Finance, Div Garg, founder and CEO of AGI Inc., said that the biggest downside risk may fall on companies with the most at stake in today’s AI distribution and product cycles, even if they are also among the most visible AI leaders.

Garg’s central claim is that Alphabet and Meta could “have the most to lose” in this transition. The argument, as framed in the interview, is not that these companies lack technical capability, but that the economics and user journeys built around today’s AI offerings may be disrupted when agents become a primary interface for tasks, decision-making, and downstream actions.

The interview also references Garg’s own background and choices around major AI ecosystem players. He is described as having rejected OpenAI, pointing to his view that the direction of AI commercialization and partnership models matters as much as model quality. Garg’s perspective suggests that, for him, agent-focused competition is likely to favor companies and developers that can control key layers of the stack, such as integration points, data flows, and action permissions.

For Alphabet specifically, the tension is straightforward to understand even without new disclosures from the company: its consumer AI visibility is closely tied to products that distribute through search, browsers, ads, and developer platforms. Agent systems that can perform multi-step tasks may shift user behavior away from classic “query-to-result” patterns toward “goal-to-execution” workflows, potentially changing what users consider the default destination.

Meta faces a parallel exposure, albeit through different distribution. Meta’s large installed base on social platforms makes it a major funnel for AI experiences, including content recommendations and AI-assisted creation. If AI agents become the primary tool for planning, shopping, communication, and coordination, Meta’s advantage could depend on how quickly it can embed agent capabilities into its apps without undermining the incentive structures that drive engagement and ad delivery.

An “agent” in this context generally means software that can interpret a user objective, break it into steps, call tools (such as web services or internal systems), and keep track of progress toward an outcome. That shifts the bar from single responses to reliability, safety, and the ability to complete tasks. In practice, the companies that control the most action-relevant surfaces could gain, while those that rely on earlier-generation AI patterns could be forced into costly reinvention.

The Yahoo Finance interview does not provide new, company-specific performance data or forward guidance from Alphabet or Meta. It also does not lay out detailed, verifiable evidence on market share, agent adoption rates, or revenue impact attributable to the “AI-agent era.” As a result, the view should be treated as a strategic argument from an industry founder rather than a quantified forecast that the two companies have endorsed.

Looking ahead, investors and industry watchers will likely focus less on who demos the most impressive agent behavior and more on who can operationalize it at scale, including latency, safety controls, and the product design that turns agent capabilities into repeat usage. For Alphabet and Meta, the key question implied by Garg’s warning is whether their existing distribution and monetization engines translate cleanly into an interface where users ask for outcomes and agents handle the steps. If not, the competitive center of gravity could shift faster than current product roadmaps suggest.