Technology and Innovation Community

Latest piece published by McKinsey Quarterly:

"Where AI will create value-and where it won't"

Key steps for leaders to unlock value:

• Assess the impact of AI on profit pools. Leaders should develop a detailed view of how AI will reshape industry economics-where value is created, lost, or shifted. They should also assess the impact of AI-powered productivity improvements and, more fundamentally, of innovation and lower transaction costs on revenue, costs, and margins.
• Build or strengthen AI-powered competitive moats. As AI adoption spreads, differentiation will stem from how companies build and combine hard-to-replicate competitive moats. Leaders should evaluate which sources of advantage can endure in an AI-driven environment, from proprietary data to network effects to structural cost advantages. The priority is to develop a reinforcing system of moats tailored to your position and deepening them before competitors do or before advantage solidifies elsewhere.
• Turn speed into a structural advantage. The ability to test, learn, and scale faster than competitors is a primary source of advantage in an AI-shaped economy. As experimentation cycles compress and the cost of iteration falls, organizations that move quickly improve at a higher rate. Faster experimentation generates more data; more data improves models and decision quality; better performance attracts more users and activity. Over time, this compounding dynamic widens the gap between leaders and laggards. CEOs should therefore invest in increasing organizational velocity-removing bottlenecks, accelerating deployment, and enabling continuous learning-recognizing that advantage accrues not just from what you build but how fast you improve.
• Rewire the business. Capturing the AI opportunity requires a fundamental rewiring of business units and functions around a scalable AI backbone. This includes redesigning end-to-end processes, modernizing data and technology infrastructure, embedding AI into decision-making and operations, and reshaping roles, governance, and ways of working. Leading organizations are not just experimenting with AI; they are rebuilding how the business runs so that AI can scale across functions and continuously improve performance.

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- Todor

Thanks Todor and Carlos both for your postings, happens to be timely for one of my side projects, whether some kind of systematic AI reporting from companies that would be helpful to investors. Clearly, recent S&P500 earnings reports talk extensively about AI, its use by companies and relevant impacts, but primarily as narrative to pre-empt investor questions. Some companies say more (like concrete stats) that is translatable by investors into value, some seem to say a lot but not anything that can get pinned down into value (sometimes makes you wonder if they directionally orientated but with no metrics).  Todor, the McKinsey article thankfully goes back to Drucker first principles.