Companies that fail to keep up with advances in hardware, software, or technology platforms could … More
If you don’t think that relying on outdated technology can lead to a crisis, then ask the Federal Aviation Administration. In April, air traffic controllers lost radar contact with a United Airlines plane that was approaching New Jersey’s Newark Liberty International Airport.
The temporary blackout was soon determined to be caused by decades-old telecommunications and other systems. In May, the FAA announced plans to upgrade those technologies, according to Forbes.
In the corporate world, companies that fail to keep up with advances in hardware, software or technology platforms could face a different type of crisis: losing their competitive edge in a challenging and demanding marketplace. That, in turn, could lead to a loss of customers, revenue, and profits.
- An overwhelming majority (88%) said they are concerned how their old systems are making it harder to keep up with more innovative competitors.
- More than half (57%) of surveyed companies acknowledge that their reliance on old technologies ‘likely’ or ‘highly likely’ causes customers to defect because of the resulting poor experiences.
- Ironically, 68% said that it was the old technology that’s preventing their organizations from adopting modern technologies.
That’s according to the results of research that was released last month by Pega. More than 500 IT decision makers were surveyed in North America, the United Kingdom, France, Australia, and Germany by research firm Sevanta in April and May 2025.
My informal survey of technology experts and business leaders yielded several more reasons why companies have not been quick to embrace the newest and rapidly evolving technology: AI.
The Biggest Barrier
“The biggest barrier to adopting AI isn’t the tech—it’s fear and confusion. Leaders can’t measure ROI past the hype, middle managers worry automation will expose inefficiencies, and employees fear being left behind without a clear path to reskill. Without trust and a practical roadmap, even the flashiest AI investments collect dust,” Patrice Williams-Lindo, a former management consultant at Deloitte and KPMG, told me in an email interview.
“I’ve seen financial and healthcare organizations pour millions into AI pilots that never leave the sandbox because leaders underestimate the complexity of aligning AI with messy legacy systems. One claims-processing AI tool sat idle for 18 months because business units and IT couldn’t agree on data governance. Gridlock—not tech—kills momentum,” she noted.
Concerns about legal-related risks and vulnerabilities can also cause companies to put the brakes on fully embracing AI and other cutting-edge technologies. “As an employment attorney representing workers across California, I’ve seen how labor concerns can become a key hurdle to the adoption of more recent technologies such as AI. Possibly the biggest hurdle is legal uncertainty, namely how automation and AI will impact employment rights, wage enforcement, discrimination, and work monitoring,” Eric Kingsley, a partner with the law firm Kingsley and Zstema, observed in an email message to me.
Tech’s Interaction With Labor Laws
“Companies are hesitant to embrace new technology without understanding how it might interact with existing labor laws. For example, AI used to make hiring decisions or analyze workers’ performance might inadvertently bring bias, which might subject companies to anti-discrimination laws. Similarly, if AI programs are used to monitor workers’ activities, companies must deal with privacy law and how it would impact unionized workers,” Kingsley noted.
“There is also hesitation due to the lack of in-house expertise and potential regulatory focus. Until more specific legal guidelines and best practices are forged, at least in jurisdictions like California, most firms will stay at arm’s length on [introducing]
newer technologies in the workplace,” he predicted.
Sometimes it’s the lack of time, training, money or resources that gets in the way of embracing new systems
“We tried out a case management system to cut down on administrative work, but the real bottleneck was training. Our team was already stretched thin, and the idea of blocking off hours to learn a system felt impossible. The software sat unused because we didn’t have the time or money to use it, and our staff went back to doing things the old way,” Emily Ruby, an attorney and owner of the Greenberg and Ruby law firm.
“After that, digital adoption stalled. Our lawyers didn’t want the extra stress of having to learn new systems in the middle of trial season. Even the best tools can’t change how things work without structured integration time,” she noted.
What It Takes To Succeed
To succeed with AI, it’s not necessary that businesses get everything right the first time they use it. “The companies that win with AI aren’t the ones with perfect systems. They’re the ones willing to start small, make mistakes, and learn fast,” Max Letek, an AI expert and digital marketing consultant, told me via email.
The longer that businesses wait to start using new technologies, the longer it will take for them to catch up with those who are not afraid to switch to them as soon as they can. “We already [are] seeing a gap forming between companies that are AI-native and those that are stuck in pilot projects. If you’re not building internal muscle now, you’re going to be chasing the competition later. The message is clear: AI isn’t just a future trend—it’s a leadership test. And the companies willing to rethink how they work today will be the ones leading tomorrow,” he concluded.
The reluctance or refusal to switch to new and beneficial hardware, software, and technology platforms could become the next avoidable self-inflicted crisis for companies and organizations.
