Michael Krigsman is hosting a CXOTALK series of conversations with innovators. For episode 219, he talks about approaches to investing in AI, common AI adoption problems and business areas most suited to AI. We summarize and react to the episode below.
Krigsman speaks to Michael Chui, a Principal at the McKinsey Global Institute, and David Bray, CIO at the Federal Communications Commission in the episode. He asks them the following questions:
- How should organizations think about investing in AI? - Chui says organizations should use AI insights to capture value at scale. Transforming the way they operate at scale requires an understanding of current mindsets, having the right talent in place and making the appropriate changes to processes and practices.
- What are the adoption problems around AI and machine learning? - Bray says the secret to success is actuallly changing what people do in an organization. Achieving positive outcomes requires an understanding how the current processes work, why they're being done that way and effectively leading organizational changes due to AI and machine learning adoption.
- Which business areas most suited to AI? - Chui mentions predictive maintenance. This is the ability to predict when something's going to break, rather than waiting until it breaks and then fixing it. Not only does it reduce costs, but maintains all other operations that would have otherwise been delayed. Bray also mentions use cases for smart cities like preventitive maintenance on roads.
At Stir Trek, we heard from several developers that technologies that help them scale operations are valuable, which is consistent with Chui's viewpoint on how organizations should think about investing in AI. To combat potential AI adoption challenges mentioned in the article, we have developed a flexible API with extensive documentation that puts the power of machine learning in developers hands. They can then work with their counterparts to change or improve existing processes at their companies.