Article · Professional Services

Could everyday AI use help BD teams win more work?

Deidentified and aggregated at firm level, the way teams already use AI could show what wins work, and where coaching would lift win rates.

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Most firms now have some view of how their people use AI tools day to day: which prompts get written, which documents get summarised, which pitches get drafted with help. Almost none of them have asked whether that data, deidentified and aggregated at firm level, could tell them something about how work gets won.

The hypothesis is simple. Teams that win more work probably use these tools differently from teams that win less. They may research the client more deeply before a meeting, test a pitch against a sceptical reader, or spend more time on the problem and less on the formatting. If that pattern exists, it is coaching material. It would show a BD leader where a lift in win rate is available and what it would take.

It has to be built the right way: lawful from the start, privacy and privilege protected, confidential client material kept out, and never used to assess individual employees. That last point is not a nicety. The moment people believe the data is being used to judge them, the behaviour changes and the signal is gone. Done properly, this is about firms learning, not monitoring.

There is also a hiring angle. The BD people who are already working this way, who treat the tools as a research and drafting partner rather than a shortcut, are visible in interview. They talk about the client’s problem first and the pitch second. They are the ones firms should be competing for.

Nobody has built this properly yet in Australian professional services, as far as I can see. The firm that does will learn more about its own BD function in a quarter than most learn in a decade.

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