IBM AI Roadmap
Large-scale self-supervised neural networks, which are known as foundation models, multiply the productivity and the multimodal capabilities of AI. More general forms of AI emerge to support reasoning and commonsense knowledge.
AI
Roadmap
Strategic milestones
All information being released represents IBM’s current intent, is subject to change or withdrawal, and represents only goals and objectives.
You can learn more about the progress of individual items by downloading the PDF in the top right corner.
2028
Develop broadly intelligent agents that learn autonomously.
We will build autonomous AI that can reliably and efficiently learn from its environment and respond to previously unseen situations through broad generalizations. These AI systems will start exhibiting aspects of cognitive intelligence.
Why this matters for our clients and the world
AI will be capable of continually and efficiently learning from multimodal input about how the world works. Those systems will learn to operate effectively even amid uncertainty and develop problem-solving skills.
The technologies and innovations that will make this possible
We will build agents augmented with multiple memory systems and multiple neural mechanisms that will interact autonomously with each other. We will develop hybrid neural architectures that will rationalize over constantly evolving information about the world. They will learn to refine their multi-scale world model and develop generalizable skills for complex problem-solving.
How these advancements will be delivered to IBM clients and partners
watsonx will support autonomous and broadly intelligent agents with appropriate trust guardrails.