The AI GPS: A Dashboard for the Enterprise CFO

Many corporations are starting their #AIjourney in the wrong way. They make two mistakes. First, they lack an #AIstrategy. Second, they don’t engage the right members of their senior management teams in their AI decisions. As they face skyrocketing AI charges, #CFOs find themselves in the middle of a tug-of-war among the corporation’s various organizations. I describe a four-graph #dashboard that acts as the corporation’s #AIGPS. The CFO owns the dashboard. The executive team uses the dashboard to monitor AI strategy’s performance, and the CEO uses it to communicate the corporate AI efforts. 

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Beyond the ETA: The Context-Dependent Robotaxi CX

Autonomy is table stakes, and supply-side orchestration, which Uber is already winning, is becoming table stakes too. The next differentiator in robotaxi customer experience is demand-side. Namely, a system that anticipates each traveler’s intent (route risk, speed-versus-safety trade-offs, the right mode for the moment) and orchestrates the trip to satisfy it. I call this Context-Dependent Ride Management. It is the layer where the premium, monetizable, flagship customer experience will be built.

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The AI Delegation Trap and the Productivity J-Curve

The Productivity J-Curve best explains AI’s productivity paradox. The investments across different categories beyond technology initially depress measurable output. Rather…

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The Inadequacy of Enterprise AI Committees and Centers of Excellence

General-Purpose Technologies, such as AI, must cause the enterprise to rethink and redesign its workflows, organizational structures, and business models. Most information technologies targeting the enterprise, e.g., business intelligence, refine and optimize existing processes rather than forcing their complete redesign. Failing to distinguish between a true General-Purpose Technology and a standard information technology leads CEOs to the dangerous trap of considering AI committees and Centers of Excellence as the appropriate bodies to introduce AI to their corporations.

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Architecting the Corporate Industrial Policy to Survive the AI Stakeholder Squeeze

Incumbent corporations are investing in and incorporating AI, yet most fail to fundamentally alter their operating models or achieve strong ROI as a result. The root of this failure is not technological. It is macroeconomic and organizational. US enterprises are attempting to execute a paradigm-shifting technological transition within a market environment that offers them no structural shock absorber, in the way a formal industrial policy can. These enterprises must navigate the AI transition while addressing a rapidly changing market environment and the AI Stakeholder Squeeze.

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