From "prompt" to "autonomy": three transformations that will redefine the AI industry by 2026

During the “Big Ideas for 2026” seminar organized by Andreessen Horowitz, leading venture capital investors outlined a radical vision of the future: artificial intelligence will no longer be a passive tool awaiting commands but an autonomous agent capable of anticipating needs and acting independently. Three fundamental changes will mark this transition, with implications that go far beyond the technical realm.

The interface that will disappear: when agents replace commands

Marc Andrusko, partner of the AI applications investment team at a16z, presents a provocative thesis: by 2026, the input box will cease to be the focal point of human-machine interaction. Next-generation applications will no longer ask users for explicit instructions but will observe their behaviors, intervene proactively, and propose action plans for ratification.

Behind this paradigm shift lies a quantum leap in the potential value of AI. Andrusko notes that the agent market does not need to compete within the $300-400 billion annual global software spending but within the volume of the labor force spending pyramid: in the United States alone, $13 trillion. This means approximately a 30-fold expansion of market opportunities.

To understand the ideal model, Andrusko refers to a type of human employee. The less proactive identify a problem and ask for guidance. Those at the top of the pyramid—the S-level—identify the problem, diagnose causes, study alternative solutions, implement them, and return to the owner only for final approval. “This,” says Andrusko, “is the future of AI applications.” LLMs are becoming faster, cheaper, and more sophisticated; users will still require a final validation step in high-risk scenarios, but models are already capable of proposing intelligent suggestions and only need a click to confirm.

Applications like a native AI CRM exemplify this transition. Today, a salesperson opens the system and manually decides what actions to take. Tomorrow, the AI agent will constantly scan opportunities, review two years of emails to rediscover abandoned leads, suggest timely follow-ups, and organize the calendar. Human input will become an exception, not the norm.

Designing for machines, not for humans: machine legibility at the center

Stephanie Zhang, growth partner at a16z, introduces a disruptive design principle: software will no longer be optimized for human eyes but for automatic comprehensibility. What works for human consumption may be irrelevant for agents, and vice versa.

Zhang recalls the fundamentals of journalism: start with the “5W and 1H” to attract human attention, as readers skip details buried in subsequent pages. However, agents read every word of an article with equal emphasis. For years, organizations have optimized every interface for human clicks and intuitive dashboards. With the rise of agents, the visual hierarchy will lose weight in favor of machine legibility—the new standard of optimization.

Already today, site reliability engineers no longer browse Grafana dashboards; AI SREs receive telemetry data, analyze it, and report hypotheses directly on Slack. Sales teams no longer navigate CRM manually; agents aggregate data and synthesize it for human reading. Visual design, once a top priority, gives way.

The crucial question remains open: what are agents looking for? We do not know for sure yet. But Zhang foresees a concrete risk: as content production costs approach zero and organizations compete to attract agents’ attention, masses of ultra-personalized, high-frequency content will emerge—a sort of “keyword stuffing of the agent era.” This phenomenon will transform how we create content and the tools we use.

From science fiction to the real market: the explosion of voice agents

Olivia Moore, partner of the AI applications investment team at a16z, documents a phenomenon already underway: voice agents are transitioning from technical demonstrations to large-scale enterprise deployment. Real companies, in nearly every sector, are testing and implementing voice AI systems.

Healthcare represents the most dynamic field. Voice agents handle calls for insurance companies, pharmacies, providers, and even direct interactions with patients: from scheduling appointments to post-operative follow-ups, up to initial psychiatric consultations. The main driving factor? High turnover and recruitment difficulties in the sector. Voice agents offer reliability and scalability where humans are scarce.

In banking and financial services, the insight is counterintuitive: voice AI surpasses humans. While people regularly make compliance errors, voice agents adhere to rules with meticulous precision, and every interaction remains traceable. This regulatory compliance advantage transforms the competitive landscape.

In recruiting, from entry-level retail positions to mid-level consulting roles, voice AI offers candidates interviews at any time, then inserts them into the human selection flow. The BPO and call center sectors will undergo a transition. Some will experience a gradual decline, others a faster collapse. As an industry adage states: “AI won’t take your job; a person using AI will.” In the short term, clients will continue to seek comprehensive solutions—call centers and BPO—but will choose providers offering lower prices or higher volumes thanks to AI integration.

A final promising horizon concerns government and citizen services. Some voice agents already handle non-emergency calls to 911; extending this technology to emergency calls, DMV transactions, and any government interface could transform an experience that is currently frustrating for both citizens and operators.

The overall picture: three pillars of a revolution

These three changes—the disappearance of the input box, optimization for agents rather than humans, and the scalability of voice agents—are not isolated developments. They represent the definitive transition from a paradigm where AI assists humans to one where AI operates autonomously, requiring supervision only at critical moments. The volume of the opportunity pyramid expands 30 times, shifting from traditional software spending to total labor force expenditure. As technology matures, costs will decrease, models will improve, and service providers who innovate will be able to offer unprecedented capabilities at competitive prices. The era of agents is not tomorrow; it has already begun.