New skills to focus on

Traditionally, business analysts are responsible for gathering the data as well as processing it for analysis. This comes with a lot of drudgery that can be eased by implementing AI tools into the workflow. Tasks such as routine documentation, formatting, and data crunching can be automated, while analysts provide the human context around that data, as well as a critical eye to the final output.

“Business analysts are often in the mix to make sure that data is accurate and that the requirements are in line with expected outcomes. They can also help ensure AI projects include the appropriate level of human oversight, comply with internal policies and industry regulations, and use data responsibly. While they aren’t solely responsible for AI governance, they often play an important role in raising questions about data sources, bias, whether the outputs make sense, and potential business risks early in a project,” says Slabinski.

BAs will need to develop AI literacy skills to better understand how models are trained and designed as well as data reasoning skills to interpret and validate AI outputs. Prompt-framing skills will also become valuable as analysts will need to know how to properly structure inputs for quality outputs. There will also be a growing emphasis on ethical analysis to identify compliance, bias, and overall fairness of algorithms, and qualified candidates will require strong change management skills to help oversee the adoption of AI-driven workflows.