Urgent.News

What's breaking now, across thousands of outlets.

AI

The companies getting the most from AI are rethinking how work gets done

AI adoption is nearly universal, but McKinsey finds only 37% of companies have seen it move the bottom line.

The companies getting the most from AI are rethinking how work gets done

As companies allocate increasing budgets to artificial intelligence, a surprising paradox emerges: while employees tout AI as a productivity booster, tangible gains in operating profit remain elusive for most firms. A McKinsey survey of 1,719 professionals worldwide reveals that 44% of respondents are expanding AI usage across their organizations, yet only 37% believe AI is significantly impacting earnings before interest and taxes (EBIT), a figure unchanged from last year.

Despite these mixed results, the financial champions of AI - the 6% of organizations attributing at least 5% of EBIT to AI - are reshaping their workflows. Nearly three-quarters of these "AI high performers" have fundamentally redesigned their processes, up from 55% last year. This shift is more pronounced in larger companies, with 54% of firms with annual revenue exceeding $1 billion scaling AI enterprise-wide, compared to just 33% of smaller firms.

For finance executives, the data suggests that while adding more AI is relatively straightforward, the real challenge lies in reimagining workflows to fully capitalize on the technology's potential. The next round of AI investment may need to be as much about restructuring processes as it is about acquiring new technology.

Written by urgent.news from Fortune's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at fortune.com →

More in AI

Accountable Generation: Intent as the Artifact of Record

Every serious engineering organization has spent decades building governance around one artifact: source code. Code gets version control. Code gets review. Code gets sign-off before it ships.

  • Intent becomes the scarce artifact in AI-assisted code generation.
  • Code volume grows faster than review capacity, errors result from wrong decisions.
  • Governance should shift to intent layer before AI advances make it crucial.

More from Wednesday 2 September →