Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
5 Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes AI is in trouble. Both...
This Simple Arithmetic Can Optimize Your Main Business Operations
 Originally published in Forbes Deep down, we all know that...
Predictive AI Usually Fails Because It’s Not Usually Valuated
 Originally published in Forbes Why in the world would the...
Panic Over DeepSeek Exposes AI’s Weak Foundation On Hype
 Originally published in Forbes The story about DeepSeek has disrupted...
SHARE THIS:

3 weeks ago
Companies Are Struggling to Drive a Return on AI. It Doesn’t Have to Be That Way.

 

Originally published on The Wall Street Journal, April 26, 2025.

Successful AI adoption begins with a targeted approach, and proceeds with careful orchestration and scaling across the organization

AI adoption among companies is stunningly high, but most of them are struggling to put it to good use. They intuit that AI is essential to their future. Yet intuition alone won’t unlock the promise of AI, and it isn’t clear to them which key will do the trick.

As of last year, 78% of companies said they used artificial intelligence in at least one function, up from 55% in 2023, according to global management consulting firm McKinsey’s State of AI survey, released in March. From these efforts, companies claimed to typically find cost savings of less than 10% and revenue increases of less than 5%.

While the measurable financial return is limited, business is nonetheless all-in on AI, according to the 2025 AI Index report released in April by the Stanford Institute for Human-Centered Artificial Intelligence. Last year, private generative AI investment alone hit $33.9 billion globally, up 18.7% from 2023.

The numbers reflect a “productivity paradox,” in which massive improvements in AI capabilities haven’t led to a corresponding surge in national-level productivity, according to Stanford University economist and professor Erik Brynjolfsson, who worked on the AI Index. While some specific projects have been enormously productive, “many companies are disappointed with their AI projects.”

To continue reading this article, click here.

Comments are closed.