As companies rush to adopt AI to increase productivity and reduce costs, they may find themselves facing a new problem: losing what sets them apart.
Mehdi Paryavi, CEO of the International Data Center Authority, said widespread use of the same system AI tools This risks flattening competitive advantage across industries as companies increasingly rely on identical systems to think, write and decide for them.
Paryavi said that as AI tools become cheaper, more powerful and more widely deployed, companies risk outsourcing the very thinking that once differentiated them.
While AI can improve short-term efficiency, he said, relying on shared models and standardized systems could leave companies competing solely on cost and speed, eroding originality, strategic depth and long-term advantage.
“If you and your competitor are all using the same service, you have no advantage over each other,” Paryavi told Business Insider.
“Their AI and yours against each other – I don’t know who’s going to win.”
When everyone uses the same brain
As generative AI becomes integrated into every workplace, Paryavi warned that the biggest risk is not automation, but uniformity.
When businesses rely on the same large language models trained on the same data, decision-making, writing, and problem-solving can begin to converge, reducing the space for creative divergence.
This concern echoes warnings from researchers and academics who say AI can produce refined results at scale, but also subverts human thought by providing fluid answers before understanding, by creating a illusion of expertise it weakens judgment and depth.
When everyone relies on the same models trained on the same data, Paryavi said, creative divergence diminishes.
“The beauty of our world is that we have different choices because we think differently,” he said. “That’s where innovation comes from.”
Efficiency today, dependence tomorrow
It’s not just a matter of companies all thinking the same thing: Paryavi warned that treating AI as a shortcut to efficiency can quietly backfire. human judgmentexpertise and control, leaving businesses faster in the short term but more fragile over time.
Over time, Paryavi said, this change can erode internal expertise and decision-making capacity.
“What they don’t think about is that initially it might seem more efficient, more productive and less expensive,” he said. “But it’s going to be very expensive in the long run.”
One risk, Paryavi said, is addiction. As companies replace their employees with AI subscriptions, they are increasingly dependent on external providers to operate effectively.
Paryavi likened the AI boom to the cloud computing rush of the early 2000s, when many companies initially adopted third-party infrastructure but then brought their workloads in-house as costs, complexity and vendor lock-in became concerns – a trend commonly referred to in the tech industry as cloud repatriation.
The same dynamic could happen with AI, Paryavi said – but with even higher stakes. As companies reduce their human teams, they also lose institutional knowledge and their ability to operate without automation, he said.
“You have destroyed all your chances of ever becoming independent as an organization,” he said. “You have laid off your workforce. You have made them useless.”
AI, he said, is not inherently harmful. In fields such as medicine, scientific research and disaster prediction, it can significantly accelerate progress.
But without clear safeguards, businesses risk trading long-term resilience for short-term speed.
“It’s a very powerful tool,” Paryavi said, comparing AI to an atomic bomb. “If this (an atomic bomb) can eliminate an entire population physically, this (AI) can eliminate humanity cognitively.”