That disconnect may explain why so many organizations are investing heavily in artificial intelligence without seeing measurable business results.
According to
McKinsey & Company, nearly 80 percent of organizations report using
generative AI in at least one business function. Yet roughly the same percentage report no significant impact on revenue or operating profit from those investments. That gap has become one of AI’s biggest business mysteries.
For Kaz Hassan, principal of product strategy and market intelligence at
Unily, the world’s first AI-native employee experience platform, the explanation is surprisingly simple.
“Organizations are optimizing for personal
productivity instead of business transformation,” Hassan explains.
That distinction changes everything.
Faster doesn’t always mean better
Most AI conversations focus on speed. Write proposals faster. Summarize meetings faster. Respond to emails faster.
Those are useful improvements, but Hassan argues they rarely change how a business actually operates. He described it as the “hamster wheel” effect.
“People are moving faster,” Hassan says. “They’re just moving faster around the same wheel.”
Instead of redesigning work, organizations often use AI to accelerate existing processes, even when those processes should have been redesigned altogether.
The result is more activity without significantly better outcomes.
AI can accidentally create more work
One of the more surprising consequences Hassan has observed is that AI doesn’t always reduce workload. Sometimes it increases it. Employees generate content in seconds, but then spend additional time validating facts, checking accuracy, editing tone, and confirming compliance.
The time saved generating content is partially offset by the time required to verify it. AI becomes another step in the workflow rather than eliminating steps altogether.
That isn’t necessarily a technology problem. It’s a design problem.
The biggest mistake leaders are making
Hassan believes many organizations are asking AI to make decisions it was never intended to make. “AI should inform decisions,” he says. “It shouldn’t replace human judgment.”
Organizations that hand critical thinking entirely to AI risk introducing errors, weakening accountability, and reducing employee confidence.
Instead, Hassan argued the most effective companies use AI to augment expertise rather than substitute for it. The technology handles repetitive work. People remain responsible for decisions.
Transformation happens inside the workflow
One example stood out. Hassan points to his company’s
work with British Airways, where AI wasn’t introduced as another application employees needed to learn. Instead, technology was embedded directly into existing moments in the cabin crew workflow, making information available exactly when employees needed it.
Rather than asking employees to change how they worked, the technology supported the way they already worked. That distinction mattered.
When AI becomes invisible inside the workflow, adoption becomes easier, employee experience improves, and the technology begins delivering operational value instead of simply adding another screen to manage.
The companies pulling ahead are buying fewer tools
Many organizations continue what Hassan describes as a “digital shopping spree.” Every new challenge is met with another platform, another chatbot, another AI assistant, and another dashboard. The result is fragmented technology that forces employees to navigate disconnected systems throughout the day.
The companies separating themselves, Hassan believes, are taking the opposite approach. Instead of accumulating tools, they’re connecting them. Consumer platforms like Uber succeed because users experience one seamless journey despite multiple technologies working behind the scenes.
Hassan believes enterprise technology is heading in the same direction. The winners won’t necessarily be the companies with the most AI. They’ll be the ones that design the simplest employee experience.
Because AI alone won’t transform a business. Purposefully redesigning how work gets done will.
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