Everyone in private equity can now see the AI opportunity across the portfolio. Now the real work is choosing the right workflow, getting access to the right systems, redesigning the process, measuring the output, and getting the team to adopt a new way of operating.
This is where a lot of AI initiatives get stuck. A portfolio company might have 20 plausible use cases: engineering velocity, customer support, finance operations, professional services automation, compliance, reporting, product modernization. But not all of them are good first projects. Some are commercially irrelevant.