The race that began with ChatGPT is evolving. Chat interfaces were the first big wave of consumer AI, but the landscape is changing fast.
AI is moving beyond general-purpose chat into more specialised, capable systems.
As this shift happens, the real question is: What comes next? Understanding this transition isn’t just interesting—it’s essential for anyone navigating what AI is becoming.
Here are the five key shifts that will define AI's next chapter:
1. Agentic AI: from conversation to action
AI is moving from a passive conversation partner to an active problem-solver.
Today's AI can discuss your calendar but can't schedule your meetings. Tomorrow's AI won't just talk—it'll do.
Imagine waking up to: "I've rescheduled your morning meetings because of the snowstorm, ordered snow tires based on your car model, and drafted weather-delay emails to your team—ready to send after your review."
Companies like Adept and Anthropic are moving beyond chat-based AI to systems that can understand tasks and take action. Adept’s ACT-1 works directly with software interfaces.
Claude helps with code tasks in the terminal. New efforts like the Model Context Protocol are making it easier for AI to access tools and data. Together, these advances point toward AI that can reason, find information, and act on its own.
2. Embodied AI: breaking free from the text box
AI is gaining eyes, ears, and even bodies.
The next generation of AI will see, hear, and physically interact with the world. This isn't just about robots—it's about AI that understands and operates in physical space.
Your AI assistant notices your posture slumping during video calls and quietly suggests a break. It recognizes when your child is struggling with homework at the kitchen table and offers age-appropriate help.
AI is starting to interact with the physical world. From Tesla’s Optimus robot to Boston Dynamics' experiments combining robotics with language models, physical capability is growing. While widespread adoption in homes or offices is still early, the direction is clear: AI will increasingly see, hear, and move in the world around us.
3. Personal AI: from generic to "your AI"
AI is becoming personalized down to your specific knowledge, preferences, and needs.
Generic AI trained on the world's data is giving way to systems that know your world—your documents, your history, your priorities.
Based on your past projects, I've identified three approaches to this design problem. The second seems most aligned with your aesthetic preferences, but conflicts with the budget constraints you mentioned last week."
Developing, tools like Rewind and Mem AI aim to create assistants that know your world, not just the world. These systems promise to turn past context into proactive support.
4. Specialized AI: from Swiss army knives to surgical tools
All-purpose AI is being outperformed by domain-specific models built for particular industries and tasks.
The "one model to rule them all" approach is giving way to purpose-built AI optimized for specific domains.
Law firms using legal-specific AI that understands case law, precedent, and jurisdiction-specific details at a level general models can't match. The same goes for medicine, finance, and beyond.
Companies like Harvey in Legal and Hippocratic AI in Healthcare are showing that specialized AI systems can be performant, reliable, and cost-effective, making it easier for smaller organizations to deploy AI for niche use cases.
These tailored solutions provide more precise, efficient, and practical applications in their respective fields.
5. Integrated AI: from feature to fabric
AI is disappearing into the background of everyday products and services.
Tomorrow's most successful AI won't announce itself—it'll quietly make existing tools and workflows better.
Your code editor suggests entire functions that perfectly match your codebase's style. Your email client drafting responses are so well-matched to your voice that you barely need to edit. Your CRM automatically enriches contacts and suggests personalized follow-ups.
Microsoft's Copilot integration across Office and Google's AI features in Workspace show how AI is becoming ambient intelligence rather than a standalone tool.
The story behind these shifts
These five trends are not developing in isolation, they are coming together to shape an AI landscape that looks very different from what we have seen before.
The way AI works, integrates and adapts is shifting in ways that feel more natural, capable, and powerful than ever.
The plot is familiar: a disruptive technology emerges (chat-based AI), creates massive attention, and then matures into something more practical and powerful. We saw this with the early web, with mobile, and now with AI.
For anyone working with technology, the real question is about finding the right approach that fits your needs and brings the most value to the people you serve. AI is evolving fast, and making the right choices now can shape what’s possible next.
The winners in this next phase will be those who understand how these evolving capabilities map to real human needs and business problems.
The future beyond the chatbox is coming faster than most can even realize. The question is: which of these shifts will matter most for you?