Artificial intelligence has become one of the most discussed business topics in recent years.
Across industries, companies are investing heavily in AI tools, automation platforms, and digital transformation initiatives. Executives are under growing pressure to demonstrate that their organizations are keeping pace with technological change.
Yet despite the excitement surrounding artificial intelligence, not every company is benefiting equally.
Some organizations are finding practical ways to improve productivity and strengthen competitiveness. Others are spending significant amounts of money with little to show for it.
Why does this happen?
In a recent interview with Financial Adviser PH, Professor Ian McLoughlin of the Singapore Institute of Technology suggested that one of the biggest problems may be that businesses fundamentally misunderstand the nature of AI itself.
The Problem with Predicting AI
According to McLoughlin, many organizations approach artificial intelligence the same way they would approach a traditional technology investment.
That may be a mistake.
“The biggest misconception is that companies think they can predict how good the AI of the future will be,” he said.
The challenge, he argues, is that AI capability is improving at an extraordinary pace.
“Humans aren’t very skilled at understanding exponential growth.”
As a result, many business leaders evaluate AI based on what it can do today rather than what it may be capable of doing six months or a year from now. That can lead to costly strategic errors.
When Companies Dismiss AI Too Early
One common mistake occurs when organizations experiment with AI, achieve disappointing results, and conclude that the technology is overhyped.
McLoughlin believes this reaction can be shortsighted.
“We tried AI and it didn’t work.”
He notes that many companies use the wrong models, apply them to unsuitable tasks, or fail to integrate them properly into business processes.
Even more importantly, AI systems continue to improve at a remarkable rate.
A tool that produces mediocre results today may become significantly more capable in the near future.
Businesses that dismiss AI too quickly may therefore find themselves caught off guard as competitors adopt more advanced systems.
The Danger of Standing Still
Ironically, companies that invest heavily in AI can also encounter problems.
Many executives assume that once an AI solution has been implemented, the hard work is complete.
McLoughlin disagrees.
“AI is not a one-time investment.”
Unlike traditional equipment that may remain useful for years, AI systems evolve continuously. New models emerge, capabilities improve, costs change, and competitors gain access to increasingly powerful tools.
A company that invests heavily in a particular AI solution today may discover that its system has become outdated far sooner than expected.
As McLoughlin explained, businesses should focus less on buying a particular AI product and more on building organizational readiness.
The goal is not simply acquiring technology. The goal is developing the ability to adapt as technology changes.
Why Internal Capability Matters
When asked why some organizations succeed with AI while others struggle, McLoughlin pointed to a factor that is often overlooked.
People.
Successful AI adoption is not simply a technology project. It is also a talent and leadership challenge.
He believes companies need people who understand AI well enough to evaluate opportunities, identify limitations, and integrate solutions into existing business processes.
Technology alone rarely creates competitive advantage.
Organizations must also understand how to redesign workflows, establish safeguards, and ensure that employees can effectively use new tools.
In many cases, the difference between success and failure may have less to do with software and more to do with organizational capability.
Preparing for an Uncertain Future
For business leaders, the challenge is complicated by the speed of change.
Unlike previous technological transitions, AI is evolving rapidly and unpredictably.
Many of today’s assumptions may prove inaccurate within a relatively short period of time.
This is one reason McLoughlin encourages leaders to focus on building internal expertise rather than relying entirely on external vendors.
Organizations that develop their own understanding of AI may be better positioned to evaluate new opportunities and respond to changing conditions.
Those that depend entirely on outside providers may find themselves struggling to keep pace.
Thinking Beyond Technology
McLoughlin also argues that business leaders should consider questions beyond efficiency and profitability.
Part of investing in AI, he says, involves understanding its limitations and its broader consequences.
Technology decisions increasingly involve questions about ethics, governance, and organizational values.
As AI becomes more deeply integrated into business operations, leaders may need to think not only about what technology can do, but also about what it should do.
This requires a level of judgment that extends beyond technical expertise.
A Different Kind of Competitive Advantage
Many executives continue to view artificial intelligence primarily as a software problem. McLoughlin sees it differently.
The companies most likely to succeed may not be those that spend the most money or adopt the newest tools first.
Instead, success may belong to organizations that build the internal capabilities needed to adapt continuously as technology evolves.
In an environment characterized by rapid change, flexibility may become more valuable than certainty.
And in a world where AI capabilities continue to advance at an exponential pace, the greatest competitive advantage may not be a particular technology at all.
It may be an organization’s ability to keep learning.
