IBM 8 Bar Logo

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.

2023

Extend foundation models beyond natural language processing.

In 2023, we will expand enterprise foundation model use cases beyond natural language processing (NLP). 100B+ parameter models will be operationalized for bespoke, targeted use cases, opening the door for broader enterprise adoption.

2024

Build multimodal, modular transformers for new enterprise applications.

We will deploy assistants and enterprise applications using transformers that process richer context and large language model (LLM)-oriented frameworks which provide better 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 AI.

We will support faster learning and the ability to provide explanations through better introspection, retrospection, and different forms of reasoning.

2028

Develop autonomous and broadly intelligent agents.

We will build autonomous AI that learns reliably and efficiently from its environment and responds to previously unseen situations through broad generalizations. These AI systems will start exhibiting aspects of biological 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.