What is Enterprise AI Adoption?
Suddenly, change management is the most exciting topic in the world of enterprise artificial intelligence.
Why? Because despite how easily we use AI in our day-to-day lives, using it consistently across teams is still very hard to do. Reports from leading firms such as McKinsey and Gartner show that when AI tries to go beyond personal use, something breaks down.
And to be clear, this breakdown is not limited to hallucinations or instances where the AI gives a seemingly wrong answer. In many cases, the issue is not the AI itself, but human error in how the technology is used. What I'm talking about is the real story, the emotional side, the push back, and the hidden forces that seem to resist change even though on paper it should all work great.
As the hype around Enterprise AI begins to shrink in the face of mounting token costs and frustration, a crisis of indecision and project abandonment often follows.
The Real Cost of Adoption
Given the stakes and how drastic the change from Enterprise AI can be, more organizations are suddenly becoming painfully aware of the real cost. Sure, AI may be faster, but it also must be checked. Data must be maintained, along with security, training, and on and on.
Adoption does not end simply because a leader forces staff to use a new toy. And this ongoing adoption story is catching many leaders off guard and unprepared for what comes next.
Think this is overblown? Consider the actual cost of adoption in real dollars and cents when users are not properly trained on how to interact with AI.
Prompt engineering costs. Simply understanding how to speak to AI can make a huge difference, and the run-up in token costs is just the beginning.
Tools designed for engagement. Tech companies often design AI tools to play to our weaknesses. Being polite to a bot incentivized to keep the conversation going can unintentionally increase usage and cost.
IPO-driven price pressure. Costs will only get worse with IPOs and the pressure to exceed investor expectations, translating into higher costs for consumers and an underwater value proposition.
Workforce trade-offs. Even if businesses use AI as an excuse to reduce headcount, the impact does not go away. You now have fewer people doing the job, which means an even greater reliance on a technology you don't control.
Carefully. Consistently. Clearly.
Leading organizations understand that AI adoption must be managed carefully, consistently, and clearly.
Carefully
Enterprise AI adoption includes how we work and why. These data are extremely sensitive and must be handled by professionals who understand and manage the risks.
Consistently
AI adoption is ongoing. Understanding trends and how they correlate to business impacts over time enables better forecasting and corrective action.
Clearly
Adoption is not static, and neither is the data. Ideas like token costs and their connection to usage are as central to adoption as training.
Taken together, adoption is not a soft skill. It is a foundational element of the entire AI experience, one that can be costly and dramatically impede success.
The Rise of the "Kinsultants"
The best organizations understand this, which is why you are suddenly seeing an explosion in deployment partners and forward-deployed engineers. Or, as Kelechi from our team coined back in 2023, "Kinsultants."
These highly adaptable people are the air traffic controllers working behind the scenes to build and implement the products synonymous with the AI generation. They understand both the technical and human sides of things and can put that knowledge into practice with measurable precision.
“How ironic that it is once again the people who seem to be saving technology.”
At the same time, technologies like our own KTA are becoming increasingly important. As a transformation management platform, KTA is designed to work with the user to mobilize data and convert it into actions, agents, or whatever is needed to get the job done.
An independent place to cultivate data, test, and learn alongside technology
With adoption so costly and that persistent "70% challenge"—a phrase I use to describe the long-standing claim that 70% of change initiatives fail—always top of mind, it's no wonder expertise and infrastructure are back on the menu.
So, What Is Enterprise AI Adoption?
It is the continuous work needed to optimize AI use in an organization.
AI adoption is a collective term encompassing how you manage costs, benefits, and ongoing efforts to get people and technology working in tandem to achieve desired goals.
How you approach adoption matters. And in today's AI economy, it is the edge you need to stay ahead of the pack.
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Nathan Gampel
CEO, Transformation Insights · Managing Partner, Simpel & Associates
For more than two decades, Nathan has advised Fortune 500s, PE portfolio companies, and startups on complex change initiatives, from M&A integrations to bringing new AI products to market.
Nathan is the author of 2 patents and 3 books on Transformation Sciences, a multidisciplinary approach to understanding change and how to get more value from the experience.
He holds an MBA with dual concentrations in Finance and Law from Rutgers University and an MA in Organizational Psychology from Columbia University.
Ready to make AI adoption work across your organization?
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