In 1980, when John Opel called IBM’s growth “as big as digital itself”, it was a pivotal moment in tech history. Unfortunately, this was not because it demonstrated innovative thinking – in hindsight, it showed complacency, organizational inertia and a denial of the personal computing revolution that was shaping the market.

By 1993, IBM – once the most profitable company in the world – reported a quarterly loss of US$8 billion. Though IBM remarkably bounced back from this ‘near-death’ experience, it does tell us that digital disruption doesn’t discriminate. The graveyard of corporate history is filled with firms that failed to revive.

Today, AI presents a much more exponential disruption. As famous historian and thinker Yuval Noah Harari notes, never in history have we been exposed to a technology that could make decisions on our behalf. AI is fundamentally redesigning how a firm creates value and competes in the marketplace. By now, we should have all read about how this requires us to rethink the operating design, leadership mindset and culture of a firm to make it work.

However, during my research for Reimagine Finance, I found three silent killers impeding such organizational redesign: management inertia, technology solutionism and profitable configuration.

Management inertia

Inertia, the tendency of an object to stay within its default state, is highly relevant when applied to the management behaviors of incumbent firms. Inertia arises when leaders, satisfied by past success, settle into legacy routines, defer tough decisions and avoid challenging established processes.

The ‘Kodak moment’ when inventor Steve Sasson created the first digital camera and was told by Kodak executives, “That’s cute – but don’t tell anyone about it,” is a classic case of management inertia.

On the other hand, DBS Bank of Singapore overcame its organizational inertia, characterized by long ATM lines and complex customer journeys, earning it the nickname the ‘Damn Bloody Slow’ Bank. Former CEO Piyush Gupta responded, moving away from a culture of traditional banking to a startup-like approach with a ‘What would (Jeff) Bezos do?’ mindset.

By revamping performance management, empowering cross-functional teams and investing deeply in cloud, AI and data analytics, DBS shed its sluggish reputation and emerged as a global digital banking leader – clinching the World’s Best Digital Bank award multiple times.

Technology solutionism

Traditional firms often fall prey to technology solutionism – the belief that the right code and tools alone can fix all business problems. The idea, criticized by Evgeny Morozov in To Save Everything, Click Here, results in a mindset that oversimplifies complex challenges.

This results in years of point solutions and digital patchwork, forcing companies into hasty shortcuts and siloed tool additions, creating a spaghetti of tech systems, eventually piling up massive technical debt due to the ongoing costs of fixing complex legacy systems.

Companies can incur 10–20 percent on top of the cost of any project to address technology debt, stifling not just innovation but also delaying decision-making and slowing down speed-to-market.

Now, starting with a one big bang approach and mothballing the entire tech system is also not advisable. The best approach is to introduce a middleware in between the current tech stack and the business problems you are trying to solve. Once these middleware or bridging applications prove value, you can start to retire legacy systems in a phased approach.

Profitable configuration

A common paradox firms face is configuring the current portfolio of strong legacy assets and strengths versus digital. It is often seen as an either/or choice. This creates what can be called a profitable configuration challenge, where firms struggle to leverage their existing strengths with the promise of new technology.

Global fashion brand Burberry’s turnaround demonstrates this well. One of their core strengths was a global network of physical stores. To digitally configure the physical world, they reimagined the in-store customer experience.

For example, customers could watch live runway streams in-store and use staff iPads for ordering. This, along with several other profitable configurations, enabled Burberry’s revenue to jump from US$2.05 billion to US$3.42 billion within four years.

In addition, a profitable configuration requires leadership to overcome the cognitive barriers they face in the form of deep-seated limitations in understanding how technology reshapes business models and markets.

For example, many firms mistakenly choose complex AI over simple, cost-effective automation like RPA due to misplaced assumptions. This misalignment stems from an insufficient understanding of technology’s role and how it can capture and deliver value to customers, leading to failed initiatives.

In August 2024, ThinkTank RAND issued a report citing this as one of the major reasons for the high AI failure rate.

Therefore, success hinges on elevating leadership cognition to see how digital and legacy can be blended strategically, rather than competing. Without this, organizations risk chasing digital for its own sake and missing opportunities to configure technology profitably with their core business realities.

From IBM’s close encounter with corporate demise to DBS’s digital dominance, history rewards firms that act decisively and quickly. Overcoming management inertia, technology solutionism and cognitive traps is the key to turning AI disruption into reinventing how traditional firms capture and deliver value.

Unfortunately, standing on the sidelines is no longer an option because, in reality, there are no sidelines. You are either in the game or out of it.

Opinions expressed by The CEO Magazine contributors are their own.