There’s a stark difference in success rates between companies that purchase AI tools from vendors and those that build them internally.
  • Zerush@lemmy.ml
    210·
    3 days ago

    Wrong Title, what fails isn’t the AI, but a bad management of the AI by pure company interests of people which don’t have any tecnical skills (apart of the poor reliability of some of the employed AIs)

    Summary by Andi

    A new MIT report reveals that 95% of enterprise generative AI pilot programs are failing to deliver meaningful financial impact in 2025, with only 5% achieving rapid revenue acceleration[1].

    The research, titled “The GenAI Divide: State of AI in Business 2025” from MIT’s NANDA initiative, analyzed 150 leadership interviews, surveyed 350 employees, and examined 300 public AI deployments. The core problem isn’t the AI models themselves, but rather a “learning gap” between tools and organizations[1:1].

    “Some large companies’ pilots and younger startups are really excelling with generative AI,” said Aditya Challapally, the report’s lead author. “Startups led by 19- or 20-year-olds have seen revenues jump from zero to $20 million in a year. It’s because they pick one pain point, execute well, and partner smartly with companies who use their tools”[1:2].

    Key findings include:

    • Vendor-purchased AI tools succeed 67% of the time, while internal builds succeed only one-third as often[1:3]
    • Over half of AI budgets go to sales and marketing tools, yet the highest ROI comes from back-office automation[1:4]
    • Companies are reducing headcount through attrition rather than layoffs, particularly in customer support and administrative roles[1:5]
    • “Shadow AI” - unauthorized use of tools like ChatGPT - is widespread in enterprises[1:6]

    The report identifies several critical success factors:

    • Empowering line managers, not just central AI labs, to drive adoption
    • Selecting tools that can integrate deeply with existing workflows
    • Focusing on specialized vendor solutions rather than building in-house
    • Targeting back-office automation for highest returns[1:7]

    Looking ahead, pioneering organizations are testing agentic AI systems that can learn, remember, and operate independently within defined parameters, pointing to the next evolution in enterprise AI[1:8].

    1. Fortune - MIT report: 95% of generative AI pilots at companies are failing ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎ ↩︎