Building your AI team structure for success

In a rapidly evolving business landscape where artificial intelligence has moved from experimental technology to competitive necessity, structuring your AI team effectively has become a critical challenge for modern organizations. In a recent talk, Denys Linkov, Head of AI at Wisedocs, shared valuable insights on how companies can strategically build their AI capabilities through thoughtful team construction. His experience offers a practical framework for businesses looking to move beyond the hype and establish sustainable AI operations.

Key Points

• AI team evolution follows distinct stages from initial experimentation to mature integration, with different team structures required at each phase
• Cross-functional collaboration is essential between AI specialists and domain experts to develop solutions that align with business requirements
• Building an effective AI team requires different roles including research scientists, engineers, product managers, and domain specialists working in coordination

The Strategic Phases of AI Team Development

Perhaps the most insightful takeaway from Linkov's presentation is his framework for the evolution of AI teams. He outlines a clear progression that organizations typically follow: from exploratory phases with individual contributors to structured teams with specialized roles, and eventually to integrated AI capabilities across the enterprise.

This matters tremendously in today's business context because many organizations are struggling with where to place AI capabilities within their structure. The "bolt-on" approach of creating isolated AI teams often leads to solutions that never gain traction with the business. Meanwhile, distributing AI talent without coordination can result in duplicated efforts and inconsistent approaches. Linkov's framework gives leaders a roadmap to evolve their AI capabilities in alignment with their organization's maturity and needs.

What makes this particularly relevant is the current AI talent crunch. With demand far outstripping supply for skilled AI practitioners, organizations need to be strategic about how they deploy these valuable resources. The phased approach allows companies to start with a small, focused team and scale intelligently as business value is demonstrated.

Beyond the Talk: Practical Considerations for AI Team Structure

While Linkov provides an excellent foundation, there are additional factors worth considering when structuring an AI team. One critical element is the "translational layer" between technical AI specialists and business units. At Microsoft, this role has been formalized as "AI Business Transformation Managers" who bridge the gap between technical capabilities and business needs. These individuals