If AI development were a sport, it’d be closer to baseball than boxing. Headlines might make it seem like AI breakthroughs happen with a big knockout punch, but the reality is more akin to a baseball team grinding through a 162-game season. It’s a process that involves having the right people in place over a long stretch, and fielding the best team is essential for success.
The root cause for this can be found in the data. As AI continues to mature and new technologies are introduced, they are only as good as the datasets that feed them. This translates into workers spending a combined hundreds or even thousands of hours cleaning, structuring and organizing the data used to develop and train AI systems.
Given the challenges of hiring and managing a team of people to complete this arduous data work, many development and operations leaders turn to outside help to recruit and manage this workforce. And, much like a baseball team trying to make a World Series push, some approaches to building the right team can yield better results than others.