Every December, Andreessen Horowitz publishes their "Big Ideas" predictions. Google Cloud also just released their 2026 AI Agent Trends Report. I went through both and pulled out three shifts I think are worth paying attention to.

We've spent the last couple of years typing instructions into AI. Ask a question, get an answer. Give a command, get a result.

That model is already fading.

The shift is toward AI that doesn't wait to be asked. Instead of pulling information from a system, AI agents push insights and take action. It's moving from on-demand intelligence to continuous, autonomous assistance.

This isn't theoretical. It's already delivering measurable results:

The pattern here is clear: AI is moving from assistant to operator. The employees who thrive will be the ones who shift from execution to oversight—from doing the work to directing the AI that does.

The 40-minutes-saved stat from TELUS isn't about replacing workers. It's about freeing them from routine execution so they can focus on strategic decisions. That's a management challenge as much as a technology one.

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This one feels counterintuitive, but stay with me.

For decades, we've designed software, content, and data for human consumption. Visual hierarchy. Intuitive interfaces. Engaging presentations. That made sense when humans were the ones interacting with systems.

But AI agents don't see visual interfaces. They parse structured data, APIs, and semantic markup. The aesthetic appeal of your dashboard? Irrelevant to an agent. The narrative hook of your documentation? Less important than its semantic clarity.

As a16z partner Stephenie Zhang puts it: we're no longer designing for humans, but for agents.

This has real implications. Organizations need to start structuring their internal knowledge and external content in ways that are optimized for agent consumption. The companies that make their systems legible to AI will unlock more effective agentic workflows. The ones that don't will find their AI investments underperforming.

Think about your own organization: Could an AI agent navigate your internal systems? Parse your documentation? Access the data it needs without hitting walls?

If the answer is no, that's a gap worth closing before your competitors do.

Audit your AI readiness. Not just "do we have AI tools?"—but "are our systems structured in ways AI agents can actually use?" If your data is siloed, your documentation is messy, or your APIs are inconsistent, you're going to hit walls.

Voice has been "the next big thing" for years. And for years, it's been too clunky for serious enterprise use.

That's changing.

The conversational AI market is projected to hit $41 billion by 2030. Voice assistant users in the US alone are expected to exceed 157 million by 2026. But the real story isn't consumer adoption—it's enterprise deployment.

Modern voice AI can now handle complex, multilingual conversations. It can adhere to regulatory compliance standards. It integrates deeply with backend enterprise systems. These aren't Alexa skills. They're production-grade business tools.

Where it's landing first:

Voice is evolving from a simple interface to a platform for business process automation. And the organizations that figure this out early will have a meaningful advantage.

If you dismissed voice AI a few years ago, it's worth another look. The compliance and integration capabilities are genuinely enterprise-grade now.

Voice has been "the next big thing" for years. And for years, it's been too clunky for serious enterprise use.

That's changing.

The conversational AI market is projected to hit $41 billion by 2030. Voice assistant users in the US alone are expected to exceed 157 million by 2026. But the real story isn't consumer adoption—it's enterprise deployment.

Modern voice AI can now handle complex, multilingual conversations. It can adhere to regulatory compliance standards. It integrates deeply with backend enterprise systems. These aren't Alexa skills. They're production-grade business tools.

Voice is evolving from a simple interface to a platform for business process automation. And the organizations that figure this out early will have a meaningful advantage.

If you dismissed voice AI a few years ago, it's worth another look. The compliance and integration capabilities are genuinely enterprise-grade now.

These are just three big shifts coming to AI in 2026 (if not already here). Just like other moves in AI, these will be swift and evolve quickly.

The best way to be prepared, regardless of your organization's size, is to start rethinking what your organization and operations look like when AI agents are executing a lot of work.

How will you reallocate human capital? How will you allocate spending to technology vs. other areas? Lastly but critically, how will you reinforce the safe and responsible use of AI?

Keep reading and learning and, LEAD the AI Revolution 💪

Hashi & The Context Window Team!