AI and Decision Factories

AI represents a seismic shift, like discovering virgin economic territory with enormous possibility. Unfortunately, history shows we often struggle to rapidly harness such innovations. Why? A failure to completely reimagine operating models and embrace complex change.

AI has been compared with electricity for years, and for good reason. Early factories merely swapped in electric motors without changing layouts or workflows. Productivity crawled. Real gains came when pioneers like Henry Ford rebuilt processes around the new technology. Once people clicked to this change, it wasn’t just the work-process that changed, it was the entire work place. New factory layouts enhanced productivity even further. It was only then that work was revolutionized.

AI has reached a similar threshold today. Its potential is vast but many applications remain incremental, simply grafting AI onto outdated frameworks. Take the use of chatbots in customer service—the ultimate “low hanging fruit”. In many cases, these AI systems are integrated into the existing customer service framework without significant alterations to the overall process. They are often designed to mimic the way a human would handle a query, following a fixed script or set of rules. Is it cheaper and more efficient? Sure, to a point. Is it transformative, reimagining the whole concept of what it takes to satisfy a customer in the digital age? As anyone who has sat on hold with an airline will know, no, it’s not.

So the mindset must move from using AI to automate tasks to using AI to reinvent work. Make no mistake, this is hard. By definition, there are major asymmetries in what it’s possible to imagine. The transition requires a cultural and operational metamorphosis.

This is why we embrace complexity. We think about designing incentives, understanding mechanisms of reinforcing feedback, zooming in and zooming out so that it’s possible to account for multiple levels and scales, understanding self-organization and distributed control, and planning for emergence and adaptation.