B2BVault's summary of:

Big Ideas 2026: Part 1

Published by:
a16z
Author:

Introduction

This article shares the biggest tech problems builders will focus on in 2026, based on insights from a16z partners.

What's the problem it solves?

Builders are facing new limits with AI, data, software, and people. Old systems were built for humans, not AI agents, massive data, or deep personalization. These ideas explain what must change next.

Quick Summary

In 2026, companies will focus on fixing messy data. Most business data lives in files, videos, emails, and images. AI breaks when this data is outdated or wrong. Startups that clean, organize, and keep this data fresh will unlock real AI value.

AI will also change how work gets done. Security teams will use AI to remove boring manual work. Software systems will stop being simple databases and turn into smart engines that act on goals. Apps and content will be built for AI agents, not human clicks or screens.

At the same time, AI will reshape creativity, video, health, and education. Video will feel like a place you can enter. Creative tools will mix text, images, sound, and video. Health tools will focus on staying well, not just treating illness. Education will move toward fully AI-powered schools built around adaptive learning.

Key Takeaways

  • Unstructured data is now the biggest AI bottleneck
  • AI agents need new infrastructure built for speed and scale
  • Cybersecurity hiring improves through automation
  • Software shifts from systems of record to systems of action
  • Content and apps will be designed for AI agents, not humans
  • Screen time stops being a useful success metric
  • Video becomes interactive and persistent
  • AI enables deep personalization in health, learning, and media
  • Collaboration between multiple AI agents creates new moats
  • Education will produce AI-native workers, not just graduates

What to do

  • Audit where your data lives and how messy it is
  • Invest in tools that clean and structure unstructured data
  • Design products assuming AI agents are the main users
  • Measure outcomes, not time spent in your product
  • Explore personalization as a core feature, not a bonus
  • Prepare teams for agent-based workflows and automation
  • Watch vertical AI tools that support multi-party collaboration

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