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As artificial intelligence technologies rapidly spread across all industries, companies are striving to integrate them into their products, operations, and strategies.
However, not all companies use artificial intelligence in the same way. For example, while a tech startup may need someone capable of building a model from scratch, a retail company might require a specialist to optimize customer data. So, what kind of AI knowledge should a leader possess to manage these needs? Each of these objectives requires different skills, leadership styles, and strategic approaches — and this is where AI leader archetypes come into play. Overall, five main AI leader archetypes have been identified.
Research-oriented AI leader - This leader focuses on scientific research and model development in the field of AI. Rather than managing large teams, they usually act as individual contributors with deep technical expertise. This type of leader is most effective in startups working on new technologies and in research teams within large companies.
Data science-oriented leader - These leaders use data for commercial purposes. They apply analytical approaches to improve customer experience, support product development, and optimize marketing strategies. This type of leader is well-suited for growth-stage companies aiming to scale by making data-driven decisions.
Horizontal engineering leader - This archetype creates AI and data platforms across the entire organization. They build data infrastructure that connects multiple departments and implement a unified data strategy. They are a good fit for large, complex organizations that have undergone numerous acquisitions.
Commercial AI engineering manager - This leader is suitable for fast-paced environments that demand quick results. They rapidly build prototypes, test market-ready products, and scale successful ones. Companies with an existing product portfolio seeking swift outcomes will benefit most from this type of leader.
AI product strategy leader - This leader ensures that AI initiatives align with the company’s overall strategy. Although they may not have deep technical knowledge, they stand out with their vision, market understanding, and ability to work with senior executives. This archetype is ideal for large organizations that use AI as a supportive tool and are planning long-term future strategies.
How to choose the right AI leader?
When selecting an AI leader, ask yourself: Is technology our core business, or is it a supportive tool? Are we aiming to optimize existing processes, or do we want to create entirely new AI products? Successful AI implementation requires not only technological knowledge but also the right leadership approach. An AI leader or strategy that works in one company may not yield the same results in another. That’s why it’s essential to carefully evaluate your business goals before making a leadership decision.
At Crocusoft, we believe that a personalized approach tailored to the organization's goals and stage of development is of great importance. Let's bring the technologies of the future to your organization together!
