Four stages of maturity in AI use

Artificial intelligence (AI) is playing an increasing role in organisations, as they strive to leverage AI to create value and gain competitive advantage. But the (generative) AI market is still young, immature and complex. Not every organisation is equally advanced in deploying artificial intelligence.

The Massachusetts Institute of Technology's Center for Information Systems Research (MIT CISR) has developed a model that describes four stages of AI maturity within organisations. This model helps organisations assess their current AI capabilities and plan for further development.

Phase 1: Experimentation and Preparation.

In this initial phase, organisations focus on educating their staff about AI, formulating AI policies and conducting experiments with AI technologies. The goal is to lay a foundation for future AI initiatives and to build comfort with automated decision making.

According to a study by MIT CISR published in December 2024, 28% of the companies surveyed were in this phase. One example is Kaiser Permanente, a U.S. healthcare organisation that has developed seven principles for responsible AI use, emphasising privacy, equity and trust.

Phase 2: Pilots and Capacity Building

In the second phase, organisations begin implementing AI pilots that create value for both the company and employees. These pilots help refine AI strategies and develop needed skills.

MIT CISR found that 34% of companies are in this phase. An example is insurance company Guardian Life, which developed an AI pilot that summarises documentation for underwriters, saving them five hours daily and accelerating the transformation process.

Phase 3: Developing AI Work Methods.

In this third phase, AI is industrialized within the organization. Companies build scalable architectures, automate processes and cultivate a test-and-learn culture. AI is being integrated into daily business operations.

About 31% of companies are at this level. One example is Ally, an American digital bank that uses the Ally.ai platform to integrate natural language processing and predictive analytics, leading to time savings in millions of customer interactions and an acceleration of marketing efforts.

Phase 4: Becoming AI-Future Ready

In the final phase, organizations have fully integrated AI into their business models, making them agile and innovative. They leverage AI to create new products and services and develop ecosystems.

MIT CISR's research suggests that companies in this stage significantly improve their financial performance and stay ahead of the competition.

Work on your AI maturity

The MIT CISR AI maturity model provides a framework for organisations to evaluate their current position and develop a strategy for further AI integration. By building the right capabilities and implementing AI responsibly, companies can not only improve operational efficiency, but also realize new growth opportunities.

We recommend that you convene a team to discuss which of the four stages your organisation is currently in and what your ambitions and timelines are regarding your company's use of AI.

Then discuss what other capabilities and skills of the enterprise need to be worked on. In doing so, use the TIMAF Digital Maturity Model that helps determine broad digital maturity and the key organisational, informational, technological and cultural dimensions that should contribute to it.

Read the MIT article Building Enterprise AI Maturity, with a podcast for “on the go.