Intensifying geopolitical rivalries, particularly between the US and China, are impacting strategies and supply chains as countries and companies look to align themselves with jurisdictions perceived as “friendly.” Meanwhile, the war in Ukraine and concerns over Russia’s future territorial ambitions are driving European countries to increase spending on defense (see Prism article “Tariffs, Geopolitics, and Supply Chains”).

And it is not just the threat of a major conflict fueling uncertainty, either. A broader sense of unease is being driven by several key developments: sweeping changes to the US tariff regime, which are reshaping the global trade landscape; the growing momentum of populist political movements in many countries; soaring levels of sovereign debt, which are stifling economic growth and increasing the risk of financial crisis; and the ongoing shift toward a more sustainable economy.

Simultaneously, the rise of AI is creating technology-related uncertainty. On one hand, it looks like the world is about to be transformed by AI technologies, with widespread implications for how we live, work, and communicate. On the other, markets are fearful that companies may not generate adequate returns from their vast AI investments, with AI seen as a bubble on the verge of bursting.

In light of all this, few would deny that leaders are navigating a volatile, uncertain, complex, and ambiguous (VUCA) world. What’s more, as Arthur D. Little (ADL) Chairman and CEO Ignacio García Alves highlights, they must navigate this VUCA world while balancing two “ambidextrous” priorities. “Leaders must deliver today and build for tomorrow, while continuously adapting to accelerating VUCA events,” he says.

“VUCA” was first coined nearly 40 years ago by the US Army War College to define the challenges of operating in the post-Cold War world. Although it remains relevant in today’s business landscape, the concept has limitations and, on its own, is not a sufficient framework for strategizing in the near term or beyond.

“We’re not just working in a volatile, uncertain, complex, and ambiguous world,” explains Sally Menassa, Partner in ADL’s Growth practice. “We are also working in a much more intricate world.”

A key limitation of the VUCA framework is that it predates the era of digital disruption — an era that has accelerated significantly with the rise of AI technologies, particularly since the launch of ChatGPT in 2022. “AI is a big uncertainty, and it’s not yet clear which organizations it will affect and in which ways,” says Michael Kolk, Global Practice Leader of Innovation at ADL. “What’s happening in AI now is complex and will affect many business processes” (see ADL report “Moving Innovation Forward”).

VUCA neither addresses the root causes of uncertainty nor offers strategic responses to it. What’s more, it has major blind spots (e.g., overlooking the convergence of global crises), and it fragments reality into four components that are actually tightly entangled and interdependent. Uncertainty largely results from complexity, for instance. For these reasons, García Alves cautions that VUCA is just one tool for viewing today’s challenges. “There are many lenses you can use, and VUCA is one of them,” he says. “But you might not see everything through VUCA. You also need to look at other frameworks.”

The interconnected nature of today’s uncertainties underscores the need to examine them through multiple lenses. “Today, we’re not just talking about separate disruptions,” argues Menassa. “We are also talking about how these disruptions converge and amplify each other. The sustainability crisis, geopolitical fragmentation, and competition for resources are all making it harder for leaders to manage volatility the way they used to.”

Business models must shift in response to the speed of change, as well as the interconnected nature of disruptions, Menassa believes. “Past operating models were built around predictability and efficiency, which made sense because the world was much slower,” she says. “Now, the premium is on how fast you can adapt. To win, organizations must shift from a static operating model to an adaptive one. They need to learn how to configure, reconfigure, and pivot” (see ADL Viewpoint “Developing Resilience for Global Supply Chains in Crisis”).

Some of today’s most successful organizations already prioritize rapid learning and sensing mechanisms that can be quickly reconfigured. For example, to improve its vehicles, Tesla proactively seeks customer feedback on defects. Netflix continually experiments, using A/B testing to inform product decisions. Microsoft has consciously shifted from a “know it all” culture to a “learn it all” one. (For a practical blueprint to make sensing measurable and reconfigurable, see ADL Viewpoint “Resilience Through Transparency.”)

Menassa, based in the Middle East, sees the principle of “learning through uncertainty” play out firsthand. New cities, such as The Line in Saudi Arabia, are being developed amid constantly shifting financial, regulatory, and technological landscapes. “I hear my clients say, ‘Let’s build the plane while we’re flying it,’” she notes.

Kolk also believes that new ways of thinking and operating are critical to success. “With innovation, for example, the traditional way of thinking is ‘We invest in R&D and other types of innovation to protect our current business and expand it,’” he says. “The strategy is to produce a new product or an improved product, but what if we instead focused on generating data that is worth more than the product itself?”