The Domino Effect: Why AI Disruption Is Faster Than You Think
Dvorah Graeser
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Consider this: it took 16 years for Kodak to fall from industry titan to bankruptcy, but only 6 years for Boeing to plummet from its peak to potential junk bond status. Why are corporate giants falling faster than ever before? The answer lies in understanding how technological disruption—particularly AI—creates rapid, cascading changes throughout entire business ecosystems. Using systems thinking as our lens, I'll explore how feedback loops between companies, customers, and competitors are speeding up, why many CEOs feel overwhelmed by the pace of change, and what leaders must do to avoid becoming the next cautionary tale in the age of AI disruption.
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Systems Thinking and Disruption
Systems thinking is an approach to problem-solving that looks at how different parts of a system interact with and influence each other over time, rather than viewing each part in isolation. Like ripples in a pond, changes in one part of a system can create cascading effects throughout the entire system. These interactions often create feedback loops, where the output of one process influences the input of another, leading to patterns of behavior that might not be obvious when looking at individual components alone.
Systems thinking can explain many of the rapid changes in the business environment. These changes have become so fast that many CEOs complain of feeling overwhelmed or left behind by the pace of change. In 2023, Accenture reported that that 52% of CEOs said they did not feel fully prepared to respond to the changes they expected to face in 2024. Plus, 47% felt overwhelmed by technological change.
So how can systems thinking explain the overwhelming pace of change?
First, feedback loops exist between companies and their customers. As customers buy more of a product (or service), the company creates more of that product or service. And of course, the opposite occurs – as customers buy less, the company makes less.
However, companies have competitors, who can take customers – and their purchases – away. This may cause our first company (Company A) to lose sales to another company (Company B). But this is also an example of a system with potentially complex behavior, as these feedback loops interact with each other.
And of course, this situation can get really complex, once you add in the potential of substitutions (purchases of different products/services that fulfil the same or similar need of the customer), and many different types of competitors.
Furthermore, when these feedback loop changes happen really rapidly, you can end up with increasingly wild oscillations in sales – one quarter your sales soar, the next quarter they crater. Why could this happen? Suppose Company A and Company B have product that is identical in the minds of consumers. The only difference between them is price. If Company A cuts the price of its product, customers will buy more from Company A. Conversely if Company B cuts the price of its product, customers will buy more from Company B. As Company A and Company B frantically change their prices, customers change their buying habits even faster – leading to wildly changing sales.
Companies of course do everything possible to avoid this situation of identical-looking products. One way that they compete is on satisfying customer needs. Some of these needs may be associated with the brand itself – the reputation of a luxury brand as expensive, for example. Other needs are likely to satisfiable with technology.
I don’t just mean that high tech brands, like electronics for example, will satisfy these needs. Services can also be provided faster and more efficiently through faster delivery at higher quality, for example – which can definitely be accomplished with technology.
An example that I like to use relates to lighting your home. Before the advent of electricity, we would often have a single light in a room – maybe even only a candle. Once electricity became widespread, we demanded excellent lighting all over our homes. A candle just wouldn’t cut it.
AI will have the same effect on satisfying customer needs. Companies that successfully integrate AI will able to make more products and services, of higher quality, that are delivered faster and at lower cost to customers. Companies that fail to successfully integrate AI into their business processes will fall further and further behind.
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From Candles to Kodak Cameras
Think about Kodak Camera, which made film cameras for a very long time. For a while it was very successful. By 1996, Kodak had over two-thirds of global market share. The company's revenues peaked at nearly $16 billion, its stock exceeded $90, and it was worth over $31 billion. The Kodak brand was the fifth most valuable brand in the world.
But by 2012, Kodak was bankrupt. Not because another film camera manufacturer was able to compete away all of Kodak’s business.
Kodak failed because of digital cameras – first as standalone products, then built into our smartphones. Suddenly everyone was taking many pictures, all of the time, everywhere. Because these pictures were already digital, we could share them online through social media. Completely new business models sprang up to serve customers who flocked to the new technology, because it served their needs better than film cameras.
The global film camera market was estimated to be worth between $277-278 million in 2023. By contrast, the global digital camera market was valued at $6-10 billion that same year – over thirty times as much, even though many of these cameras are now embedded in our smartphones (and hence are less expensive than stand-alone cameras).
The real kicker is that Kodak invented one of the first digital cameras – back in 1975 – but was afraid to ruin its film business. Kodak actually made more money from the film itself than from manufacturing cameras. Kodak sowed the seeds of its long decline 37 years before it actually failed, through fear of adopting new technology.
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Boeing: Example of Feedback Loops Getting Faster
It took 16 years for Kodak to go from its peak to bankruptcy. Boeing's stock price reached its all-time high on March 01, 2019, when it closed at $430.35 – and while it isn’t yet bankrupt, Boeing’s bonds may be degraded soon to junk bond status. That’s less than 6 years from peak to fall.
Boeing certainly hasn’t met customer needs recently – with planes crashing, doors being blown out in mid-flight, and astronauts being stuck on the International Space Station. While Kodak has had a slow decline, Boeing has had a far faster crash.
In fact, the story of Boeing shows what can happen when a company takes technological short cuts – using the easiest technological solution, rather than the most appropriate one. The Boeing 737 MAX crisis shows how technological compromises can spiral into catastrophic failures. Rather than designing a new aircraft to compete with Airbus, Boeing modified its existing 737 design by adding larger engines mounted further forward on the wings. This hardware change altered the plane's aerodynamics, leading Boeing to implement a software solution called MCAS (Maneuvering Characteristics Augmentation System) to automatically adjust the aircraft's angle and prevent stalls.
However, this software fix introduced new complexities and risks that Boeing failed to adequately address. The MCAS relied on a single sensor without redundancy, wasn't fully disclosed to pilots or regulators, and contained flaws that could cause it to repeatedly activate. Combined with insufficient pilot training and weakened regulatory oversight, these issues contributed to two tragic crashes - Lion Air Flight 610 and Ethiopian Airlines Flight 302 - claiming 346 lives.
The consequences of these cascading failures have been severe and long-lasting. Boeing suffered a worldwide grounding of the 737 MAX for 20 months, costing billions in losses and damaging its market position against Airbus. The company's initial response of blaming pilot error further eroded trust, and even after the MAX's return to service, Boeing continues to face quality control and manufacturing issues across its aircraft line. This decline exemplifies how rapidly a company's fortunes can change when technological complexity, corporate culture, and safety considerations become misaligned.
Many other well-known companies have declared bankruptcy recently, from Tupperware – which failed to satisfy customer needs with its materials, price and business model – to Red Lobster, which seems to have died from endless shrimp (and a 30% decline in customers since 2019).
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As market forces accelerate more and more rapidly, businesses are either changing and succeeding – or failing – more rapidly as well. Customers become used to faster satisfaction of their needs. If they don’t get quick satisfaction from one company, they’ll just go to another one.
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AI Accelerates Disruption
Just as electricity fundamentally changed customer expectations about lighting, AI is transforming customer expectations across every industry. Especially Generative AI.
Generative AI disrupts everything faster. The rate of change reported by business leaders increased by 183% over the past four years, with a 33% increase in just the past year. Many CEOs attribute this rapid change to generative AI in particular. CEOs also near unanimously expect the rate of change to increase even faster in the coming years – again due to Generative AI.
On the bright side, CEOs expect Generative AI to increase growth opportunities (52%) and to increase efficiency in their organizations (79%).
However, even these bright spots come at a cost. Last year, IBM CEO Arvind Krishna predicted that about 10 percent of the company’s total workforce would be replaced through attrition, due to Generative AI. However, the rate of replacement may not be very fast – at least at this moment. But it is likely to accelerate in the next few years.
CEOs are preparing by first understanding the best use cases for how Generative AI can be integrated with their employees. They are then preparing a roll-out program with cross-functional teams: not just IT, but users across many departments. ?Major training and upskilling initiatives are underway at many large companies – and nimble smaller companies, too.
Some CEOs are raising more money for these new Generative AI initiatives (23%) or are reallocating existing resources away from other projects (69%). New training, new data infrastructure – and even new acquisitions – are all on the menu for the coming years.
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Ready to Make AI Work for You?
The acceleration of change we've discussed isn't slowing down—but you can get ahead of it. In my upcoming book, "The AI Process Playbook for Business" (December 10, 2024), I provide the practical roadmap that business leaders need to thrive in this era of rapid disruption. Just as Kodak's decline showed us the cost of hesitating to embrace new technology, today's businesses face a similar inflection point with AI. But unlike Kodak, you don't have to navigate this transformation alone.
Whether you're looking to streamline complex tasks, boost creativity, or maximize team efficiency, "The AI Process Playbook" provides the practical framework you need to succeed.
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