This browser is not actively supported anymore. For the best passle experience, we strongly recommend you upgrade your browser.

The Buzz

Stay informed with the latest research, ideas, news, and more

| 1 minute read

Where Do AI Productivity Gains Actually Go?

McKinsey’s latest survey exposes a gap that business leaders cannot solve by buying more licences. Eighty per cent of respondents who use AI in their roles said it improved their individual productivity. Only 37 percent of respondents attributed any positive EBIT impact to AI.
 
The practical question is no longer simply whether AI saves time. It is what the organization deliberately does with the capacity created. 
 
That decision matters especially in professional services. Boston Consulting Group (BCG) found that 66 percent of surveyed employees received limited or no guidance about what to do with AI-created time, while more than half were not reinvesting it in more strategic work.
 
Consider M&A due diligence. AI may accelerate the first-pass review, comparison and synthesis of transaction materials. But the opportunity should not be limited to finishing the same review sooner.
 
Depending on the transaction, the capacity could instead be used to:
  • examine a broader set of records or contracts;
  • investigate exceptions and inconsistencies more deeply;
  • test assumptions against the underlying documents;
  • consider additional scenarios and transaction risks;
  • prepare earlier for negotiations; or
  • spend more time helping the client understand what the findings mean.
These are not automatic benefits. They require designing the workflow around them. Legal and business leaders therefore need a better scorecard. 
 
Did cycle time improve without reducing quality? Were significant exceptions identified earlier? Was saved capacity consciously redirected? Did professionals spend more time on judgment, negotiation and client advice? Can the work product still be verified and explained?

At BD&P, this is the direction of our AI Enablement work. We are approaching AI as a legal-service-delivery question rather than simply a technology rollout. We are working from specific legal and business problems, designing repeatable workflows with appropriate oversight, and considering how to redirect capacity toward better analysis, stronger execution, and more useful client advice. 
 
Organizations are deploying agentic coding tools and coming to grips with the costs of AI while still seeking to capture more of the benefits that their workers are deriving from their individual use of AI.

Tags

ai strategy, legal technology, m&a