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.
2026
Bring robust, strategic reasoning and commonsense knowledge to enterprise AI.
Our AI systems will support faster learning and will have the ability to provide explanations through better introspection, retrospection, and different forms of reasoning.
Why this matters for our clients and the world
AI systems capable of fact-checking and reflective thinking will be faster and more accurate learners and planners. They will earn trust in real-world situations via demonstration of cognitive capabilities.
The technologies and innovations that will make this possible
We will integrate advances in reasoning-focused architectures with learning modules. We will combine and control slow-learning systems with world models that rely on fast-learning systems such as episodic memory modules. We will advance planning techniques to enable the evolution of AI systems towards their end goals.
How these advancements will be delivered to IBM clients and partners
watsonx will display cognitive characteristics, broadening its deployment to scenarios that require high trust in systems.