In the latest episode of "Big Ideas for 2026," a16z pointed out that AI's role is undergoing a crucial transformation, evolving from a tool that passively responds to instructions to a system that understands usage context, takes proactive action, and directly performs tasks for humans in practice. This change is reflected on three levels: how AI user interfaces are designed, who are products and content made for, and how AI can truly enter frontline labor and service scenarios.
The first major change: AI no longer waits for instructions; instruction input is gradually becoming secondary.
Say goodbye to passive operation, AI begins to actively understand and act.
At the beginning of his presentation, Marc Andrusko, partner of the a16z AI Applications Investment Team, stated that his most crucial observation for 2026 is that the prompt box will no longer be the primary entry point for AI applications. He pointed out that future AI applications will not require users to repeatedly issue commands, but will instead continuously observe the user's work status and behavioral patterns in the background.
In this model, AI proactively identifies potential problems or opportunities, proposes specific action suggestions, and may even directly complete part of the work, before finally submitting it to humans for confirmation on whether to adopt it. Andrusko believes this represents a shift in AI's role from a simple tool responding to instructions to a system capable of proactively participating in tasks.
From software tools to the highest-level agent group of several employees
He further pointed out that this shift has also redefined the market size of AI. Previously, the market opportunity for software primarily stemmed from approximately $300 billion to $400 billion in global annual software spending. However, as AI begins to actually take over human work, the market expands to include labor itself. In the United States alone, labor spending reaches a staggering $13 trillion, significantly expanding the potential market for software.
Andrusko describes this direction as akin to employee-level agency. He points out that ideal AI should function like an employee at the highest level of agency, capable of identifying problems, researching the background, proposing solutions, and implementing them independently, only requiring human confirmation at the final crucial moment. Humans will still retain the final decision-making power, but in a large amount of daily work, AI will be able to proactively complete the vast majority of processes.
The second major change: Products and content are no longer designed solely for humans, but rather to serve agents.
Humans no longer operate directly; agents become the primary intermediaries.
After discussing the changes brought about by AI interfaces, Stephanie Zhang, a partner at a16z, shifted the focus to the transformation of creative and product design logic. She pointed out that more and more users are not browsing websites or operating software themselves, but are instead using AI agents as intermediaries to search, read, organize, and evaluate information on their behalf.
In this context, design approaches optimized for human attention begin to fail. News outlets emphasize eye-catching openings and interfaces pursue visual hierarchy, all in response to the limitations of human attention span. However, AI agents will read the entire content and will not stop at the first few paragraphs.
Visual appeal has become secondary; machine readability has become the core priority.
Zhang stated that this shift is already occurring in business practices. Engineers no longer need to manually access monitoring systems to interpret data; AI agents first analyze telemetry data, compile possible causes and insights, and then report back to humans. Sales teams are also gradually shifting from browsing customer relationship management (CRM) systems themselves to receiving key information compiled by the agents.
In this environment, the core of product and content design has shifted from visual presentation and operational processes to whether the information is clearly structured and easy for machines to understand and retrieve. He also mentioned that as content generation costs decrease, the market may see a large amount of high-volume content produced to attract the attention of AI agents, but currently no one can be certain what kind of information the agents truly prefer.
The third major change: Voice AI has moved from the experimental stage into real-world work environments.
From technology demonstration to actual enterprise adoption
After focusing on the interface and design logic in the first two changes, Olivia Moore, AI Application Investment Partner at a16z, shifted the focus back to real-world application scenarios. She pointed out that 2025 was the year that voice AI transitioned from proof of concept to actual enterprise deployment, and this trend will continue to expand in 2026.
She stated that almost every industry has seen cases of testing or large-scale implementation of voice AI, with the healthcare industry being the most prominent example. From communication between insurance companies and pharmacies to patient appointments, reminders, post-operative follow-ups, and even initial contact for psychological counseling, voice AI has already taken on some of the tasks.
Labor shortages and compliance requirements are driving the accelerated deployment of voice agents.
Moore points out that the chronic labor shortage and high staff turnover rate in the healthcare sector are key reasons for the rapid adoption of voice AI. The financial and banking industries have also become rapidly growing areas for voice AI; even with stringent compliance requirements, voice AI has consistently adhered to regulations and its performance can be continuously tracked.
In the recruitment process, voice AI allows job seekers to complete initial interviews at any time, before connecting to subsequent human processes. She also mentioned that voice AI excels in multilingual and accent recognition, and looks forward to expanding its application to more government service scenarios in the future. While some regions currently have an advantage due to lower labor costs, this gap may gradually narrow as models improve and costs decrease.
This article, "AI Agents Say Goodbye to Command Input Boxes? a16z Predicts Three Major Changes in AI Applications in 2026," first appeared on ABMedia, a ABMedia .
