The Dream Team: Assembling the Right People for Your GenAI Project
So the decision has been made to upgrade your business using generative AI technology. Great! But now comes the hard part: Figuring out how to transform that aspiration into action, and it all starts with people.
The First Move: Assembling the Team
The first move you’ll make in your GenAI journey is assembling the group of folks who will design, build, test, and deploy your GenAI applications. While these projects often involve automating work done by humans, GenAI development is very much a people-centric journey.
Technical Roles
Technical roles are critical in GenAI application development. Depending on whether you’re building your own AI model (unlikely), fine-tuning an existing model (a little more likely), or adopting a pre-built AI model with prompt engineering and RAG (most likely), your GenAI team will require a mix of data scientists, AI engineers, data engineers, and application developers.
Non-Technical Roles
But GenAI is not the exclusive domain of the techies. In fact, compared to classical machine learning projects, the role played by non-technical practitioners is even greater.
You won’t get far without the necessary technical expertise in GenAI. However, when using GenAI to modify core company functions, you’ll need the input from line-of-business experts, such as the head of customer support or the director of warehouse management, to ensure that your GenAI product is a good match to how they see customers and employees interacting with your brand.
The Rule of Three
EPAM, a consulting firm that helps clients build GenAI solutions, uses a rule of three in constructing GenAI teams. The teams are built out following a general rule:
"One is a product manager or business leader who decides what is the prioritization of the backlog," says Pierre Samec, EPAM’s SVP of Enterprise AI Solutions. "One is a subject matter expert. And subject matter expertise is really fundamental in the GenAI space because if you don’t speak the language, it doesn’t work.
The Two-Pizza Team
EPAM currently maintains 13 different pods that attack nine industry verticals and four horizontal organizations. Each individual team usually contains between four and 10 team members, he says.
"It’s somewhere between a one- and a two-pizza team," he says.
The Full-Stack CEO
GenAI tech is evolving at a furious clip, which is good news for your GenAI prospects. Tech giants like Google and Meta have gifted the world pre-trained large language models (LLMs) – you just need to tap into them and use them in a way that’s productive and profitable for your business, without sacrificing security and ethics along the way.
Conclusion
Assembling the right team is crucial for successful GenAI projects. Whether you’re building, fine-tuning, or adopting pre-built AI models, you’ll need a mix of technical and non-technical expertise. Don’t be afraid to tap outside experts or tech consultants to help you build out your team.
Frequently Asked Questions
Q: What role do non-technical practitioners play in GenAI development?
A: Non-technical practitioners, such as line-of-business experts, play a critical role in ensuring that GenAI products align with company values and customer interactions.
Q: What is the rule of three in constructing GenAI teams?
A: EPAM uses a rule of three, consisting of a product manager or business leader, a subject matter expert, and a GenAI builder.
Q: What is the ideal team size for GenAI projects?
A: EPAM recommends teams with between four and 10 members, or somewhere between a one- and a two-pizza team.
