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Reinvent the enterprise with generative AI

Generative AI is a fast-evolving technology capable of driving unprecedented productivity and growth across the enterprise. Reinventing with gen AI is an ongoing effort that demands a strong and secure digital core, safe and responsible AI use and balanced investments in both technology and people.

What you can do

Move from isolated use cases to a comprehensive, value-led approach that spans the entire value chain. Prioritize both table stakes use cases that lead to radical efficiencies, and strategic bets that offer truly novel advantages.

85%

of organizations increasing technology investments are focused on gen AI.

Elevate IT for the AI era with a strong, secure digital core—one that includes a modern data foundation and a flexible AI architecture that supports multiple foundation models and future-proofs against model changes.

60%

of surveyed organizations are strengthening their digital core.

People are fundamental to realizing the value of AI—so invest in them equally. By adapting operating models, embracing new ways of working and committing to continuous learning at all levels, you can maximize AI’s potential and sustain growth.

95%

of employees surveyed are excited to work with gen AI.

Establish and embed responsible practices across the design, deployment and scaling of generative AI across the enterprise. Use technology to systematize responsible AI practices—this will drive value while effectively managing AI risks.

2%

of all companies have identified as having fully operationalized responsible AI across their organization, with a further 31% expected to do so in the next 18 months.

Embrace generative AI reinvention as a continuous strategy. Define a modular, step-by-step approach to innovation, allocating capital, time and talent over multiple years.

What you should know

  • Demystifying AI

  • Responsible AI

  • European Union AI Act

  • Secure gen AI

  • Gen AI in marketing and sales

Leading industry-wide reinvention

  • Semiconductors

  • Biopharma

  • Retail

  • Life sciences

  • Consumer goods value chain

  • Consumer goods

  • Travel