As companies rush to adopt AI to increase productivity and reduce costs, they may be facing a new challenge: losing what sets them apart.
Mehdi Paryavi, CEO of the International Data Center Authority, said widespread reliance on the same AI tools risks flattening competitive advantage across industries, as companies increasingly rely on the same systems to think, write and make decisions.
Paryavi said that as AI tools become cheaper, more powerful and more widely deployed, companies are at risk of outsourcing the very thinking that once differentiated them.
He said that while AI can increase efficiency in the short term, relying on shared models and standardized systems can force companies to compete solely on cost and speed, at the expense of uniqueness, strategic depth and long-term advantage.
“If you and your competitors are all using the same service, you have no advantage over each other,” Paryavi told Business Insider.
“Their AI vs. your AI – you never know who’s going to win.”
If everyone uses the same brain
As generative AI becomes embedded throughout the workplace, Pallavi warned that the biggest risk is not automation, but uniformity.
When companies rely on the same large language models trained on the same data, decision-making, writing, and problem-solving can begin to become centralized, reducing room for creative divergence.
This concern reflects warnings from researchers and academics that while AI can produce sophisticated results at scale, it can subvert human thinking by providing fluent answers before understanding, creating an illusion of expertise that weakens judgment and depth.
When everyone relies on the same model trained on the same data, Pallavi says, creative variance diminishes.
“The beauty of our world is that we think differently and therefore have different choices,” he said. “That’s where innovation comes from.”
Efficient today, dependent tomorrow
It’s not just a matter of all companies thinking the same thing. Pallavi warned that treating AI as a shortcut to efficiency could quietly hollow out human judgment, expertise and control, making businesses faster in the short term but more vulnerable over time.
Over time, Paryavi said, the changes could undermine the company’s internal expertise and decision-making ability.
“What they don’t think about is that at first it might sound like it’s more efficient, more productive and cheaper,” he said. “But this will become very expensive in the future.”
One of the risks, according to Paryavi, is dependence. As companies replace their employees with AI subscriptions, they are increasingly relying on external vendors to function effectively.
Paryavi compared the AI boom to the rush to cloud computing in the early 2000s. At the time, many companies initially adopted third-party infrastructure, but later brought workloads back in-house due to concerns about cost, complexity, and vendor lock-in. This trend is commonly referred to in the technology industry as cloud regression.
Paryavi said the same dynamic could play out with AI. However, it is different when higher stakes are required. As companies reduce their human teams, they also lose organizational knowledge and the ability to operate without automation, he said.
“We have destroyed any possibility of becoming independent as an organization,” he said. “You fired people. You made them useless.”
He said AI is not inherently harmful. Progress can be greatly accelerated in areas such as medicine, scientific research, and disaster prediction.
But without clear guardrails, companies risk sacrificing short-term speed for long-term resilience.
“This is a very powerful tool,” Pallavi said, likening AI to an atomic bomb. “Then [an atomic bomb] Entire populations can be physically eliminated. [AI] Humanity can be cognitively eliminated. ”
