According to Inc, an MIT report from August revealed that custom AI solutions are being “quietly rejected” by businesses, with only 20% of surveyed organizations having piloted enterprise-grade AI systems and a mere 5% having fully deployed solutions. Impel, which develops AI merchandising software for auto dealerships, has exploded since pivoting to AI and now generates around $200 million in annual recurring revenue with clients including General Motors, Hyundai, and Honda. Forethought creates AI customer support solutions that help companies overcome “AI jitters” through gradual implementation. Grammarly, launched in 2018, now serves 50,000 organizations and 40 million daily users, with one client Databricks saving $1.4 million annually and reducing editing time by 50%.
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The brutal truth about AI adoption
Here‘s the thing about that MIT report – it’s not really surprising when you think about it. Most businesses aren’t tech companies. They’re car dealerships, retailers, manufacturers who just want to sell their products. The AI hype train has been moving at light speed while most organizations are still figuring out their basic digital transformation.
And honestly, can you blame them? The landscape changes every month. What was cutting-edge AI six months ago is practically ancient history today. So businesses do what humans naturally do when overwhelmed – they stick with what they know. They carry on with business as usual while the technology world zooms past them.
Why gradual adoption actually works
What’s fascinating about these success stories is how they’re overcoming resistance. Impel doesn’t force-feed AI to skeptical car salespeople. They start by only using AI responses outside work hours. Forethought begins “at a crawl” and increases sophistication as comfort grows.
Basically, they’re treating AI adoption like introducing someone to swimming – you don’t throw them in the deep end. You let them get comfortable in the shallow water first. And once people realize this technology can handle the “soul-crushing, mind-numbing work,” as Impel’s founder puts it, the resistance melts away.
Moving beyond AI hype to real value
The Grammarly example with Databricks is particularly telling. This wasn’t about chasing the latest AI trend – it was about solving a real business problem. A near-miss with a customer email error led them to seek a solution, and Grammarly delivered measurable results: 50% less editing time, 10-15% more support cases resolved, and $1.4 million in annual savings.
That’s the key difference between successful AI implementation and failed experiments. When employees start saying “Please don’t take this tool away from me, I can’t live without it,” you know you’ve moved beyond novelty into genuine utility. At that point, as Grammarly’s head of enterprise product notes, it becomes “a loss aversion strategy” rather than just another tech toy.
What this means for the rest of us
So if your company is part of that 95% that hasn’t fully deployed AI, what should you take from this? First, you’re not alone – the majority of businesses are in the same boat. Second, the successful implementations share common traits: they start small, solve specific pain points, and focus on user comfort rather than technological sophistication.
The companies helping others catch up aren’t selling magic AI wands. They’re providing tailored solutions that integrate with existing workflows and demonstrate immediate value. And maybe that’s the real lesson here – successful AI adoption isn’t about being on the cutting edge. It’s about finding tools that make people’s jobs easier and then letting the results speak for themselves.
