In a two-part series, I introduce the Enterprise Capital Gate, the AI GPS’s companion instrument. The Gate is used for AI project capital decisions to address specific risks. Decisions are based on the project’s innovation horizon and stage. The Gate’s mechanics come from venture capital and corporate innovation portfolio practices.
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.
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.
The Productivity J-Curve best explains AI’s productivity paradox. The investments across different categories beyond technology initially depress measurable output. Rather…
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.