In digital and AI transformations, start with the problem, not the technology

For digital and AI transformations to succeed, companies need to firstly understand the problems they want to solve, then (and only then) rewire their organisations for continuous innovation.

Summary

This page is a transcript of a podcast in which McKinsey senior partner Eric Lamarre discusses the key elements of digital and AI transformations. Here are some of the main points:

1. Digital and AI transformations should start with the business problem to be solved, not the technology to be used.
2. Talent is a critical factor for success, and companies need to create a modern technology environment that attracts and retains skilled technologists who can work closely with the business.
3. Technology development is more productive and innovative when done in-house, rather than outsourced to third parties. IT should evolve into a distributed function that enables the rest of the organisation to innovate securely and with access to the tools and data they need.
4. Digital transformations require a shift in the roles and mindsets of the C-suite and the control functions, such as finance, HR, risk, and compliance. They need to support persistent funding, talent development, risk management, and process reimagining for distributed digital innovation.
5. Technology is complex and fast-changing, but executives can de-complexify it by establishing a common language and understanding, visiting companies that are ahead in the transformation journey and focusing on the value creation from new technology.