As organizations increasingly recognize the importance of leveraging generative AI to enhance their operations and stay competitive, the adoption and implementation of this technology come with their own set of challenges. Limited resources, tight budgets, and overloaded teams are common obstacles that businesses face. To overcome these challenges and ensure the success of gen AI initiatives, organizations must focus on the people behind the technology and the dynamics within their teams.
Combining AI Experts and IT Veterans
To extract maximum value from gen AI, organizations should form teams that blend the domain-specific knowledge of AI experts with the practical experience of IT veterans. These teams often consist of individuals from different generations, with varying skill sets and levels of business understanding. IT veterans bring the contextual knowledge of the business and experience in managing legacy systems. This knowledge is crucial for embedding gen AI into existing products and workflows while maintaining the company’s forward momentum. On the other hand, AI-native talent, such as data science graduates, possess the technical skills necessary to work with AI tools and apply AI techniques to an organization’s data. They understand which data should be used and have the ability to transform it for optimal use.
Challenges of Integrating Gen AI Teams
One of the primary challenges organizations may face when forming gen AI teams is resource scarcity. IT teams are already burdened with the task of keeping existing systems running smoothly, and asking them to incorporate gen AI into their technology landscape can be overwhelming. While it may be tempting to isolate gen AI teams due to a lack of labor capacity, this approach hinders integration of the technology into core application stacks. To overcome this challenge, organizations may need to make difficult decisions, such as cutting and consolidating previous investments, to create capacity for new gen AI initiatives.
Clarifying the Problem Space
To ensure successful integration of gen AI, teams must have a clear understanding of the problem they are trying to solve, the desired outcome, and the necessary levers to achieve that outcome. Creating an outcome map that links the target outcome to supporting levers and identifies impediments can help align resources and set clear expectations. By focusing on the problem space rather than speculating about solutions, organizations can avoid potential failures and excessive rework. This approach is reminiscent of the big data boom, where companies realized the need to deeply understand their problem space before applying new technologies.
Enhancing Understanding Through Education
A growing trend among IT professionals is continuing their education to gain data science skills and effectively drive gen AI initiatives. Data science graduate programs cater to new college graduates, mid-career professionals, and senior executives. These programs foster improved understanding and collaboration between IT veterans and AI-native talent. While not a requirement for gen AI success, these programs offer IT professionals the opportunity to learn technical data science concepts that power gen AI within their organizations.
Bridging the Gap for Gen AI Success
Bridging the generational and knowledge gaps between veteran IT professionals and new AI talent requires a deliberate strategy. By considering the advice mentioned above, organizations can set themselves up for success and drive the next wave of gen AI innovation within their organizations. The collaboration between AI experts and IT veterans is crucial for leveraging gen AI to its full potential and achieving positive business outcomes.
In conclusion, organizations must recognize the importance of forming effective gen AI teams and fostering collaboration between AI experts and IT veterans. By combining domain-specific knowledge with practical experience, clarifying the problem space, and enhancing understanding through education, businesses can overcome challenges and drive gen AI initiatives to success.
