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.
2024
Build multimodal, modular transformers for new enterprise applications.
We will deploy enterprise AI assistants and applications using advanced transformers and developer-friendly frameworks to facilitate processing richer contextual information and enhanced control and monitoring of generative AI.
2025
Alter the scaling of generative AI with neural architectures beyond transformers.
We will use a diverse selection of neural architectures beyond, and including, transformers that are co-optimized with purpose-built AI accelerators to fundamentally alter the scaling of generative AI.
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.
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.
2030
Build empathic and intrinsically responsible AI agents.
Our AI agents will start to understand and adapt to human personality at both the individual and collective levels, thus enabling more natural and effective interactions. The systems empowered by these AI agents will exhibit the emergence of emotional intelligence.
2030+
Build adaptable and generalist AI for effective human-machine collaboration.
Our AI models will be composed of modules with different cognitive abilities (e.g., perception, memory, emotion, reasoning, and action), enabling them to exhibit behavioral norms for social interactions and mutual theory of mind.