The Secrets of AI Value Creation

14Talent

No institution can possibly survive if it needs geniuses or supermen to manage it.

—Peter Drucker (management consultant, educator, and author, laying the foundations of modern management theory)

AI talent is one of the key capabilities to create value with AI. However, many organisations new to AI are missing out on the value it can create due to a failure to invest in it. From a budget allocation perspective, it is the investment in talent that differentiates AI achievers and AI beginners. Although the more mature AI organisations invest 27% of their AI budget on talent, those just beginning to explore it allocate about 15% (Celi and Miles 2020). However, it is not just investment in talent, it is the investment in the right talent pool that differentiates AI achievers from beginners. Although AI is traditionally associated with STEM fields and experts (physicists, mathematicians, computer scientists, and data scientists), the experience of AI achievers has shown that successful value creation requires more than just that. AI value creation will need to acquire a diverse set of competencies, including technical and nontechnical abilities.

Evidence for that requirement comes from the shifted expectations at the leadership level of AI initiatives. In the early 2010s, many enterprises began their data‐driven journey by appointing chief data officers (CDOs). Initially, CDOs were expected to have a background in data management and data governance, but now they require ...