The world of AI is rapidly evolving, with more people considering themselves as AI developers due to the accessibility of generative AI tools. However, not too long ago, companies struggled to find and hire highly skilled data scientists and machine learning engineers, also known as “unicorns”. Now, with generative AI, almost anyone can interact with AI outputs, but that doesn’t make everyone an AI Developer. The rise of the AI “citizen developer” has led to a shift in organizations, where more people are involved in AI projects, primarily focusing on prompt engineering and image generation tasks.

Generative AI has democratized natural language processing and image generation tasks, empowering casual users as “citizen AI developers”. While these users can tackle basic AI projects, AI specialists are still essential for handling more complex patterns such as autonomous vehicles or hyperpersonalization. Traditional AI project development teams consist of data scientists, machine learning engineers, and data engineers, along with teams responsible for operationalization.

The scope of the AI team has expanded to include AI project management roles and Trustworthy AI teams. These teams are crucial for managing privacy, compliance, risk, ethics, and governance related to AI projects. The modern AI team is more diverse and complex than before, involving a collaborative effort from everyone at the organization. AI project managers play a vital role in keeping AI projects on track and following best practices methodologies such as CPMAI to ensure project success.

As AI becomes integral to organizations, having skilled AI project managers and adopting best practices methodologies is essential for success. The role of technology in AI projects is just one part of the equation, with people and processes playing a more significant role in project outcomes. By leveling up everyone within the organization and effectively managing AI projects, the organization as a whole benefits from the advancements in AI technology. The future of AI teams lies in creating a cohesive and collaborative environment where everyone is considered a valuable member of the AI team.

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