Scaling Enterprise Technology for AI

Companies need to reshape their technology function and adopt an "AI everywhere" approach to successfully scale AI solutions across the enterprise.

Themes

AI-Driven Transformation

Timeframe

near-term

Subcategories

Artificial Intelligence Corporate Strategy Operational Efficiency Risk Management Software Development

Impact areas

AI Scaling Enterprise Technology Operating Models Talent

Detailed Analysis

Scaling AI requires significant changes to the technology function. The report emphasizes that "companies can’t scale their AI solutions without also reshaping their technology function." This includes re-architecting the tech stack with an "AI everywhere" approach, integrating AI into operational systems, workflow systems, and data analytics systems. Furthermore, upgrading ways of working is crucial, requiring the adoption of MLOps processes, federated AI development models, and AI-first software development processes. These changes will impact talent, funding, and risk management within the technology function.

Context Signals

Companies moving beyond AI experimentation to scale up solutions. The need for CIOs to own, develop, and maintain production-grade AI solutions. Rapid evolution of generative AI technologies.

Edge

Companies that adopt an "AI everywhere" approach will gain a competitive advantage. MLOps and federated AI development models will become increasingly important for managing AI solutions. The role of the CIO will become even more critical in driving AI adoption and transformation.

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