A Non-technical Leader’s Guide to AI Success
There’s a reason why most AI/ML projects are not successful. It’s a leadership problem. Leaders — you should stop treating AI as another IT initiative. AI is inherently different and it requires leaders to change their thinking, culture and approach.
The last decade was about convincing the world that AI works. This decade is about using AI responsibly and profitably. Today’s AI is as much about business and society as it is about technology. Leaders, regardless of their background, need to take control of AI. Here’s a simple illustration that I prepared to guide the CFOs, CMOs and any CXOs.
The shape of the guide is intentionally non-linear. Obviously each of the ten items is a huge topic. The key point for a leader is to note that there’s a lot of thinking, planning and change management needed before you start any modeling or coding work. And the governance, monitoring and corrective actions continue after the model is in production. In other words, the technical work for AI (which gets most of the attention) is sandwiched between critical business and product work that requires full attention of a full breadth of leaders and decision makers.
So, now is a good time for all leaders to become familiar with the vocabulary of AI and learn the fundamental concepts so that leaders can communicate effectively with AI experts, ask the right questions and work together with their teams to make their next AI initiative a success.
