February 26, 2026 Some Thoughts on the AI Divide

AI is a transformation project, not a software install. Companies that miss this may miss the ROI too.

There’s a great divide in the world of AI right now. On one side is the technology: the large language models, the AI agents, and the mega corporations promoting them. The other side hosts the businesses being sold on the promise of AI. Caught somewhere in the middle are the working people being told they have to use the technology.

The problem is that communication just rolls downhill. The AI evangelists don’t explain how it can provide value to a company—and the companies don’t explain how it provides value to their people/workers. It’s also why AI is so often falling short for so many companies. It’s so often sold to organizations as a straightforward path to efficiency and growth. But the real product is far messier. It should come as no surprise, then, that AI initiatives generate ROI less than 25% of the time.

But AI doesn’t fail because of the technology itself, AI fails because companies are too focused on the technology and not the people using it. In fact, most of the time AI fails at a company is because at least 50% of the people being asked to use it never wanted it in the first place.

Why Large Enterprises Struggle With AI

I’m not here to debate whether AI has incredible, outsized potential, because I believe that it does. The point I’m trying to make is that it’s no magic bullet, and its success comes down to the rank-and-file people using it every day.

AI works from training, from properly calibrated algorithms, from persistent and sustained corrective use. It’s not at all a plug-and-play technology – it’s something you have to nourish and tinker with. This can be a difficult undertaking for even the largest, most advanced companies. In fact, enterprise companies struggle with it most of all. It’s difficult to perpetually calibrate and adjust such tools when no one is bought in on it in the first place.

Strong Technology, Weak Adoption

I like using the example of a manufacturing company that thought they were doing everything right, and instead inadvertently did the opposite.

Fearing they were falling behind the competition, they built an incredible AI quality-control system for the production line. It was technically exceptional, detecting defects with 95% accuracy, eons better than the old manual method. Yet within six short months, “less than 10% of quality issues were being routed through the AI system” (1). The implementation relied on tech and ignored its people, added extra steps to workflows, and provided little explanation for its decisions. The workers didn’t like or understand it, so they chose to work around it. Another one of the 75% of AI pilots that failed.

Technology and Transformation

AI is not a technology project, it’s a transformation process. Every successful transformation starts with defining a strategy to reach an end state, communicating that strategy to your people, creating a roadmap or plan, and then managing and executing the plan.

I’ve found that if people are involved early, if they’re allowed to give their opinion, if the strategy is explained to them, adoption not only skyrockets, but so does the likelihood of success.

The next thing that increases the probability of achieving ROI, is getting small wins fast. If people can immediately experience success with AI, they’re much more likely to adopt bigger projects.

Wins Don’t Just Add Up, They Get the Change Started

A recent case study comes to mind. A well-known mattress giant wanted to better utilize their skillset. Rather than attempting the loftier goals all at once – they started with just a smaller section of the plan. This entailed using an AI tool called SleepExpert.AI, a platform that improved the efficiency and experience of the store associates.

The utilization is perhaps the story in and of itself. This new suite of tools wasn’t just forced down employees throats. It was pitched as a win-win tool for the everyday staff and leadership alike.

The AI platform had relevant, applicable tools for all*, the most popular of which was a training tool called Drill Mode. It allowed them to freely ask questions and practice different sales scenarios with thousands of combinations and scenarios. People loved it, and this buy-in translated to increased usage for the other tools, including AI inventory management, demand forecasting, store and distribution center (DC) replenishment, and merchandise financial planning (MFP).

They made the rollout a two-way street. Rather than just demanding (and hoping) employees change their toolkit, they gave them easy reason to. In the grand scheme of things, ‘Drill Mode’ and the other employee-centered apps had narrow implications. It was a mere piece of their larger AI plan. But the success paid lasting dividends. What started as a few localized successes quickly turned into widescale adoption.

The Cost of ROI

AI is a transformative technology, but that’s just a small part of it. Companies must keep the principles of transformation and change management at the forefront if they want lasting success. The ROI is there for the taking, but it won’t come from shortcuts, especially if you shortcut your people.

If you want to be part of the merry few, don’t start and end with the model. Start with your people, your leaders, your data, and your willingness to treat your AI journey as a process you constantly shape.

About the Author:
Rob Lowe is an Associate Director of Digital and AI Services with alliant, where he manages daily operations. Rob is a leading digital consultant who has managed developers across three continents and overseen projects for companies like Samsung, Microsoft, Toshiba, and AB InvBev. Prior to this role, Rob was a consultant for the alliant group of companies’ UK operation, Forrest Brown, in addition to serving as Head of Digital at Harte Hanks. Today, Rob’s work has been instrumental in creating alliant’s suite of digital products, including its next-gen AI chatbot and automations.

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