As companies across tech and beyond seek to integrate AI into their processes, products and organizations, they'll need an AI leader to harness its power effectively. However, there’s more than one type of AI leader, reflecting the varied AI needs and maturity of businesses today.
These are the people you want to push innovation further but not necessarily lead the commercial or business implications of their work. Similarly, they may lack experience managing large teams, overseeing complex organizational structures or scaling operations.This archetype concentrates on use cases around personalization, recommendation engines, growth initiatives, pattern recognition and signal analysis to help their organization improve business decision-making and the customer experience.
We see this leader most often at later-stage or mature organizations—usually ones that have several acquisitions under their belt that require a unified data strategy. As such, this leader requires significant experience managing complex engineering initiatives, implementing large-scale data management strategies and connecting data infrastructure initiatives to business results.
This leader thrives at growth-stage organizations with established product suites and revenue streams seeking to create quick wins. They have a strong technical foundation, along with proven commercial experience taking AI projects from concept to market, giving them the savvy and intuition required to identify which POCs are most likely to generate value.
We often see this leader archetype at large, later-stage public companies outside of the technology sector. Although these organizations don’t sell tech products, they're committed to leveraging AI to augment their business strategy and operations.
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