Want To Get The Most From Your AI Investments? Start Engineering For AI
Techstrong.ai, Friday, January 9th, 2026
By now, we've all seen the findings from the recent MIT report: 95 percent of AI pilots are failing to generate real value. This may come as a surprise to some, given the hype surrounding AI and the amount of talent, time, and money companies are pouring into the technology.
But personally? This stat didn't shock me in the slightest. The reality is, when AI doesn't have context around the information it's processing, it tends to generate a lot of garbage.
I experienced this recently when I used a large language model (LLM) to conduct deep research into how to improve the product at our startup. The answers it provided read with conviction, but the hallucinations were so extreme that acting on the output could have been detrimental.
The LLM confidently described fantastical product features that didn't exist and imagined capabilities that were illogical and unnecessary. And other AI tools weren't any better; they generally cap out at around 50 sources and present incomplete information.