Mark Zuckerberg Envisions Billions Using Personal AI Agents by 2028

Washington DC, United States Jul 30, 2026 ALN: Meta founder and CEO Mark Zuckerberg is trying to sell investors on his prediction for the future — one where billions of people will have their own personal AI agents in the next five years. (Let’s hope that future also comes with data centers efficient enough to power all those agents — without triggering a fresh wave of climate disasters.)

“I think that it’s extremely unlikely if you look out five years from now, for example — whatever period of time you want — that you don’t have billions of people with a personal agent that understands your goals and that is just working on your behalf 24/7 to achieve your goals in whatever the domain is that you care about,” Zuckerberg said on Wednesday’s quarterly earnings call with investors.

The concept of personal AI agents is not entirely new. Over the last few years, advancements in artificial intelligence have led to the development of increasingly sophisticated systems capable of performing tasks ranging from scheduling appointments to managing personal finances. These systems leverage vast datasets, machine learning algorithms, and natural language processing to create a more personalized user experience. The idea of having an AI that can understand an individual's preferences and goals is appealing, especially in a world where technology is becoming more integrated into daily life.

Zuckerberg's vision aligns with broader trends in technology, where personalization and automation are key focal points. As people increasingly rely on technology to manage their lives, the demand for tools that can assist with decision-making and task management is likely to grow. In this context, personal AI agents could serve as an extension of existing technologies, providing users with tailored support that adapts to their unique needs.

He added that he could see people using these agents to help them with their finances, health, interpersonal relationships, and household management. This multi-faceted utility reflects the diverse roles technology plays in modern life, where individuals seek solutions that can simplify complex tasks and enhance their overall well-being.

“As we move toward a future where we’re all interacting with multiple agents, I think that WhatsApp and our other messaging surfaces are going to become increasingly important,” he said, noting that WhatsApp is already the leading platform where users interact with Meta AI. This suggests that Meta is positioning its existing platforms as central hubs for AI interactions, potentially increasing user engagement and retention.

Meta is not alone in setting high expectations for AI systems that can act on a person’s behalf rather than just answer questions. Google emphasized custom AI agents as a key new feature in its Search overhaul, which sparked outcry from users who felt bogged down by the constant onslaught of AI results on Google. This backlash highlights the challenges companies face as they integrate AI into their services, balancing innovation with user experience. Meanwhile, subscriptions to Anthropic’s Claude have skyrocketed as engineers fawn over the agentic coding assistant Claude Code, illustrating the competitive landscape in the AI sector.

Compared to its competitors, however, Meta may not enjoy as much confidence from investors as it continues dumping cash into innovative projects that may or may not pan out — Meta’s stock dropped almost 10% after posting this quarter’s earnings. This decline reflects investor skepticism regarding the company’s ability to translate ambitious AI visions into profitable ventures. Meta’s Reality Labs, the organization responsible for its AR glasses, VR headsets, and related software, lost around $4.6 billion this quarter, roughly in line with the losses the division has posted each quarter since 2021. That’s a running total now of around $88 billion. These figures raise questions about the long-term sustainability of Meta’s investments in cutting-edge technologies, especially in an environment where profitability is increasingly scrutinized.

Meta’s AI spending is likely to climb even higher, which is more of a concern at this juncture. The company reported free cash flow of $784 million this quarter, down from $8.55 billion the same quarter last year. That’s a 91% drop year over year, exacerbated by the company’s investments in AI infrastructure. This week, Meta and BlackRock announced a partnership to build a $14 billion data center in El Paso, Texas. Such significant investments in infrastructure are essential for supporting the computational demands of AI technologies, but they also contribute to the financial pressures the company is facing.

“We believe that there will continue to be a significantly higher margin on selling intelligence rather than selling compute directly, but we think that there’s a big opportunity, obviously, to sell compute as well,” Zuckerberg said. This statement underscores a strategic pivot towards monetizing AI capabilities, suggesting that Meta sees greater potential in developing and offering AI solutions rather than merely providing the underlying hardware.

Ultimately, he believes that the personal agents that Meta is developing will be “the foundation for our next wave of products and revenue lines in the months and years ahead.” This ambition reflects a broader trend within the tech industry, where companies are increasingly looking to AI as a primary driver of future growth. As personal AI agents become more prevalent, they could transform not only how individuals interact with technology but also how businesses operate and engage with customers.

So far, Meta’s business agents, rolled out globally on WhatsApp and Messenger this quarter, have been adopted by more than one million businesses. This early success indicates a willingness among businesses to integrate AI into their operations, potentially paving the way for broader consumer adoption. It may be harder to get people to adopt consumer AI agents, but the road to “billions” has to start somewhere — the company can’t get there on enterprise agents alone. The challenge lies in convincing individual users of the value and utility of personal AI agents in their daily lives, which will require effective marketing and user education efforts.