My 13 Insights from Reading "The State of AI in Business 2025" MIT Report
Picture this. Warm Saturday morning. A hot coffee. And 26 pages of what the heck is going on with AI in business.
The 26 pages of MIT's "State of AI in Business 2025" took me an hour.
Honestly, best use of my time in a while. And here are my personal highlights (marked with pen to the paper!), not AI-generated ones ha!
GenAI Implementations are Failing, and Why...
Despite $30–40 billion in enterprise investment into GenAI...95% of organizations are getting zero return [no impact on P&L].
...only 5% of custom enterprise AI tools reach production
The paper coined gap between the 95% and 5% the GenAI Divide. Reasons for failing is...
...due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations.
The top barriers reflect the fundamental learning gap that defines the GenAI Divide: users resist tools that don't adapt, model quality fails without context
The biggest thing holding back AI isn't model quality, legal, data or risk...
What's really holding it back is that most AI tools don't learn and don’t integrate well into workflows.
Where Companies Have Been Successful
External parties were praised for their higher success rates in supporting GenAI implementations finding that...
External partnerships see twice the success rate of internal builds
The core barrier to scaling is not infrastructure, regulation, or talent. It is learning.
The article found that partners who truly understand their business workflows have the most success.
Enter the Shadow AI Economy
While only 40% of companies say they purchased an official LLM subscription, workers from over 90% of the companies we surveyed reported regular use of personal AI tools
This "shadow AI" often delivers better ROI than formal initiatives
Personally, I thought this somewhat comical.
Personally created meme for just this!
There are a lot of jokes about how turning on CoPilot isn't an AI strategy... but technically just turning on ChatGPT or CoPilot for staff is actually worthwhile.
Personally created meme for just this!
However, the paper also highlights this is also the reason a lot of projects are failing due to comfort in known tools.
What Does it Say About The Workforce?
While most implementations don't drive headcount reduction, organizations that have crossed the GenAI Divide are beginning to see selective workforce impacts in customer support, software engineering, and administrative functions.
Three areas: customer support, software engineering and admin are being impacted.
Research found limited layoffs from GenAI, and only in industries that are already affected significantly by AI. There is no consensus among executives as to hiring levels over the next 3-5 years
Great news, we are safe for the next 3-5 years 😉
GenAI is already starting to have workforce impact and it is manifesting through selective displacement of previously outsourced functions and constrained hiring patterns, but not through broad-based layoffs
...adoption creates divergent hiring strategies across organizations. While executives demonstrate no consensus regarding entry-level or general hiring volumes, they consistently emphasize AI literacy as a fundamental capability requirement.
This answers the questions about how do you future-proof yourself against AI?
Become AI literate and learn the tools of the modern economy.
And that may start with reading this report. I highly recommend it.
All comments in this article are directly from the Report. They are not my own work. Comments of my own are in the standard text writing. The meme is of course created by yours truly.
