Every year, a16z partners publish their Big Ideas predictions—the problems they think builders will tackle in the coming year.

The 2026 edition is dominated by AI agents. Not AI as a tool, but AI as an actor—systems that do work autonomously, interact with other systems, and operate on behalf of users.

Several predictions have direct implications for marketing. Here’s what caught our attention.

Machine Legibility: SEO for the Agent Era

This is the prediction that stopped us:

“Creation and optimization will shift from being for human eyes and clicks to ‘machine legibility’ for agents.”

Think about what this means.

For 25 years, digital marketing has optimized for human attention:

SEO: Make content findable by humans using search engines
UI/UX: Make interfaces easy for humans to navigate
Conversion optimization: Make it easy for humans to click “Buy”
Content marketing: Make content engaging for humans to read

But if AI agents increasingly act on behalf of users—researching products, comparing options, making purchases—the optimization target shifts.

Your next “customer” might be an AI agent evaluating options for its human principal.

We wrote about this in our A2A Marketing post: the idea that marketing will increasingly need to be machine-readable, not just human-readable.

a16z is now predicting this shift will accelerate in 2026.

What machine legibility means for marketing:

Human-Legible	Machine-Legible
Beautiful landing pages	Structured data and APIs
Persuasive copy	Clear specifications
Social proof (testimonials)	Verifiable claims and data
Brand storytelling	Standardized product descriptions
Engagement metrics	Outcome metrics

This doesn’t mean human-readable marketing dies. It means you need both—content that appeals to humans and data that’s parseable by agents.

The End of Screen Time

Another prediction:

“The traditional ‘screen time’ KPI will end, replaced by outcome-based metrics that measure ROI by value delivered.”

Marketing has been addicted to engagement metrics:

Time on page
Click-through rates
Social media impressions
Email open rates

These metrics measure attention, not outcomes. They’re proxies for value, not value itself.

If agents handle more research and purchasing decisions, engagement metrics become less meaningful. What matters is whether the agent—acting for the user—accomplished its goal.

New marketing metrics might include:

Agent conversion rate (% of agent queries that result in purchase)
Structured data completeness (how much of your product info is machine-readable)
API response quality (how well your systems serve agent requests)
Outcome attribution (did the customer actually get value)

Vertical AI Goes Multiplayer

The prediction:

“Vertical AI will evolve from single-user information retrieval to ‘multiplayer AI,’ where agents representing different stakeholders collaborate and negotiate across organizational boundaries.”

Think about what happens when:

Your marketing agent needs creative assets → talks to a design agent
Your content agent needs SEO optimization → talks to an analytics agent
Your campaign agent needs budget approval → talks to a finance agent
Your brand agent needs to respond to a mention → talks to a PR agent

Marketing becomes a coordination problem between specialized agents, not a task list for a human team.

This connects to our thinking about A2A commerce and x402 payments. Agents won’t just collaborate within your organization—they’ll transact across organizational boundaries, paying for services they need to complete their tasks.

Agent-Native Infrastructure

The prediction:

“Infrastructure will need to be re-architected (agent-native) to handle the recursive, bursty, and high-concurrency demands of AI agents.”

Current marketing technology assumes human operators:

Dashboards designed for human eyes
Workflows that wait for human approval
APIs rate-limited for human-speed interactions
Authentication designed for user sessions

Agent-native marketing infrastructure looks different:

Programmatic interfaces, not just GUIs
Automated decision-making with guardrails
APIs designed for high-frequency agent interactions
Authentication that handles agent-to-agent trust

If you’re building marketing technology, the question becomes: is this designed for humans using AI tools, or for AI agents operating autonomously?

The Year of Hyper-Personalization

The prediction:

“2026 will be ‘the year of me,’ as products in education, health, and media shift from being mass-produced to being hyper-personalized for the individual.”

Marketing has always talked about personalization. But “personalization” usually means:

Segment customers into groups
Show slightly different content to each group
Maybe use their first name in emails

True hyper-personalization means:

Content generated specifically for each individual
Messaging adapted to personal communication styles
Timing optimized for individual attention patterns
Offers based on personal value curves, not demographic averages

This is only possible with AI that can generate and adapt at individual scale. Mass personalization requires mass automation.

What This Means for Marketing Teams

If these predictions play out, marketing in 2026 and beyond requires:

1. Machine-legible brand presence Your brand needs to be understandable by AI agents, not just appealing to humans. This means structured data, clear APIs, and standardized product information.

2. Outcome-focused measurement Move past engagement metrics to actual value delivery. Did the customer get what they needed? Did the purchase work out?

3. Agent-friendly architecture Marketing systems need to work with AI agents—both your own and those representing customers. Human-in-the-loop becomes human-at-the-edge.

4. Personalization infrastructure The ability to generate and adapt content at individual scale, not just segment scale.

5. Cross-agent coordination Marketing as orchestration of specialized agents, not a single team doing everything.

The Transition Period

We’re in a transition. Most marketing still happens through human-readable channels aimed at human attention. That won’t change overnight.

But the direction is clear. The predictions from a16z align with what we’re seeing: marketing is becoming less about persuading humans directly and more about operating in an ecosystem where AI agents are increasingly active participants.

The companies that prepare for this transition—building machine-legible presence, outcome-focused measurement, and agent-friendly systems—will have an advantage when the shift accelerates.

The full Big Ideas 2026 report covers infrastructure, bio, gaming, and more. For more on preparing for agent-era marketing, see our posts on A2A Marketing and Marketing Agents with Wallets.