AI is developing very fast, with new tools coming out all the time. Companies are excited to use them and are starting many pilot projects. But here’s something I see too often, AI pilots stop working, not because the AI itself is bad, but because nobody thought about how it fits into the actual workday.

Testing AI on simple tasks is one thing, but using it in business is often more complex. Success isn’t just about whether the AI is accurate, it’s about whether people find it useful and actually use it day-to-day. I’ve seen the same pattern in different industries like construction, logistics, and finance, AI tools look good in demos but don’t get used in the real world.

Let’s look closely at an example: An AI Report-Writing Assistant

Imagine a company rolls out an AI tool meant to help employees write complex business reports faster.

• The AI Tech: The tool itself is impressive. It can pull data when directed, summarize articles, and draft report sections based on simple prompts. In testing, it generates relevant content quickly and accurately.
• How It’s Used: The AI assistant lives on its own separate app. It’s a classic island solution, it doesn’t plug directly into the tools the employees actually use for writing (like Word or Google Docs), nor does it seamlessly access live company data or files.
• What Really Happens: Because the tool is separate, using it adds extra steps and breaks the natural writing flow: An employee is working on their report in Word To use the AI for a specific section (e.g., summarize market trends), they have to stop writing Open a browser and log into the AI tool Type in their request, maybe needing to manually upload relevant source files or copy-paste context Wait for the AI to generate the text Manually copy the generated text Switch back to Word Paste the text, which often loses its formatting Spend time reformatting the pasted section Merge the AI-generated text into their own narrative. Double-check any facts or sources provided by the AI (which might require going back to the AI portal or original sources, as they aren’t linked in the Word doc).

This constant back-and-forth, the copy-paste-reformat cycle, adds significant friction. It interrupts the thinking and writing process. Instead of a time-saver, it often feels like more tedious work than writing the section manually, especially for integrating complex information.

The Result: After trying it a few times, employees often revert to their old methods. The potentially powerful AI tool gets ignored because the “Workflow Tax”, the extra effort required by its island nature, is simply too high.

This isn’t just one story, it’s a common problem when AI tools are just tacked on as separate “islands”, instead of being built into the actual work process itself. Think of it like having brilliant writing suggestions (the AI insight) but only being able to access them via a slow, clunky interface that interrupts you (the clumsy workflow).

How to Make AI Pilots Succeed: Focus on the Flow

The real benefit comes when AI automates or makes tasks much easier within the way people already work. The best AI tools often don’t even feel like a separate “AI tool” to the user, they integrate seamlessly.

So, when checking if an AI pilot project might work, ask these kinds of questions:

• Instead of: “Is the AI accurate?” Ask: “What exact work step (like formatting, summarizing, finding data) does this automate or make much faster inside our current process (e.g., directly within Word/Google Docs)?”
• Instead of: “Does it generate good text?” Ask: “How many manual steps (like copy-pasting, reformatting, searching separately) does this get rid of?”
• Instead of: “Who is the target user?” Ask: “How does this fit smoothly into the tools (like Word, Teams, shared drives) this person already uses every single day?”

In Short

The best way to tell if AI is really working for a company isn’t just how advanced the tech is. It’s how much it makes the existing work easier and becomes an unseen, essential part of how things get done. The future impact of AI won’t just be better tech, but smarter ways to build it right into our workflows. We need fewer new dashboards and more intelligence built into the tools we already have or we need to build tools from scratch, that replace our current ones but are created with an AI-first mindset.