Strategists are trained to decompose problems, build structured frameworks, and develop quantitative models upon which to build their game plan. But AI is rapidly commoditizing the analytical skills that have underpinned the strategy function, making them available to a far wider set of actors across the organization. If analysis is no longer the strategist’s scarce resource, what modes of thinking are? And how do strategists determine which to apply to a challenge their firm faces? The ability to select the right mode of thinking for the right problem is becoming more important than ever.
To explore this shift, we asked 175 chief strategy officers to identify “untamed issues”—areas where existing approaches and frameworks fall short. From these conversations, four kinds of challenges emerged: navigating rising complexity; reinventing advantage continuously amid rapid environmental change; balancing short-term pressures with long-term value creation; and harnessing AI effectively to design better strategies.
In this article, we describe the four modes of thinking required to address these untamed issues and to effectively navigate the new forces strategists face.
To Navigate Rising Complexity, Harness Systems Thinking
Increasing geopolitical fragmentation, regulatory volatility, and technological disruption interact in ways that generate nonlinear or self-reinforcing dynamics. For instance, policy decisions trigger corporate responses; those responses can spark action from customers or the public in general; and shifting social sentiment, amplified online, can influence
Contextual factors such as politics and geopolitics, technology, and climate now account for almost half of all variation in company profitability—while the traditional factors we think of as driving profitability (where you play and how you compete) explain
Traditional analytical thinking isolates variables and traces linear cause-and-effect chains, an approach that is ill-suited to complex systems. In a complex system, the variables reshape each other. Systems thinking addresses this by shifting the question from “How do we optimize this part?” to “How does the whole system behave?”—focusing on interactions, feedback loops, and emergent patterns.
Consider the difference in practice. A traditionally trained strategist who sees declining revenue might diagnose weak sales execution and respond with performance targets. A systems thinker would map the broader dynamic: perhaps declining investment in product updates led to negative customer reviews, which depressed revenue, which triggered budget cuts to R&D, creating a reinforcing downward loop. The intervention point in the second framing is entirely different from the first.
To make systems thinking durable, organizations need routines that force leaders beyond their own silos. Cross-unit strategy forums, where each business unit must identify not just its own priorities but two ways its decisions could affect other units, surface interdependencies that siloed planning misses. Regular audits of KPIs and incentives can ensure they reward enterprise-wide outcomes rather than local optimization. And before any major decision, a second-order effects exercise—mapping at least three downstream consequences beyond the intended one—can reveal dynamics that linear analysis would overlook.
Beyond the firm’s boundaries, companies can open the strategy process to a broader set of actors; for example, bringing in external experts like universities, government bodies, operational partners, and startups to strengthen their ability to anticipate and mitigate disruptions.
Companies can also move beyond traditional tools that assume stable variables and linear trends. Complex systems models, digital twins, and AI-enabled scenario-planning tools can simulate interactions among geopolitical, macroeconomic, regulatory, and technological dynamics.
To Reinvent Continuously, Foster Counterfactual Thinking
The second cluster of untamed issues centers on vitality: the challenge of continuously renewing the organization’s competitive edge. In a rapidly changing world, imagining what does not yet exist—always a vital part of a strategist’s toolkit—has become more imperative. Organizations must increasingly harness innovation to dynamically renew their advantage. There is a significant skills gap here: nearly 94% of respondents in our survey identified this function as critical, yet only 12% feel well prepared to meet it.
Counterfactual thinking addresses this by shifting the question from “How do we improve what we have?” to “What would we build if we started from scratch?”—systematically exploring how outcomes might differ if key assumptions, actions, or conditions were changed. This is precisely what separated Kodak from Fujifilm. When new digital technologies emerged, Kodak sought to adapt by optimizing within its existing model: managing the film-to-digital transition, protecting margins. Fujifilm, meanwhile, harnessed counterfactual thinking: It asked what its capabilities would be worth in a world without film, audited over 70 transferable technologies, and reinvented itself around healthcare, materials science, and cosmetics.
Counterfactual thinking shifts the question from “How do we improve what we have?” to “What would we build if we started from scratch?
One way to activate such thinking is to challenge the mental models organizations use to interpret the world. Entrenched mental models can limit strategic thinking; making these models explicit, questioning their assumptions, and experimenting with alternatives gives leaders a broader lens on viable strategic moves. Platforms such as Uber, Airbnb, and Shopify succeeded by overturning core assumptions about how people behave, who they trust, and what they value in their everyday experiences.
Another way to spark counterfactual thinking is to attend to anomalies and weak signals. Consider how entrepreneur Jack Dorsey put this idea to practice when Jim McKelvey, a glass artist, told him he had lost a sale because he couldn’t process a credit card payment. Dorsey asked a counterfactual question: What if accepting card payments were as easy for small merchants as for large ones? Instead of trying to improve existing merchant services, he imagined a world where anyone with a phone could become a merchant. This simple shift in perspective opened a new possibility, and Dorsey and McKelvey went on to create a new market by founding the Block (formerly Square) point of sale system.
To institutionalize counterfactual thinking, organizations can build routines that make it a regular practice. Scenario-based portfolio reviews force teams to evaluate strategic bets against multiple plausible futures rather than a single baseline forecast. Pre-mortems, where the team assumes that a strategy has already failed and generates plausible reasons why, can increase risk identification and trigger pivots. And requiring leaders to surface one surprising observation alongside standard metrics at each quarterly review ensures that weak signals reach decision makers before they’re smoothed away in aggregated data.
To Break Temporal Trade-Offs, Leverage Integrative Thinking
The third cluster of untamed issues involves conflicting priorities—most acutely, the tension between short-term performance and long-term investment. The timescales strategists operate in are stretching: On one end, AI enables real-time decision making; on the other, long-term societal, environmental, and demographic shifts demand planning horizons that extend further than ever before.
Too often, strategists assume that trade-offs are a given, forcing a choice between competing objectives rather than asking whether they can be redesigned to reinforce each other. Over three-quarters of the strategists surveyed acknowledged that managing this balance is a major part of their job, yet half were not confident of their skills in this area. Strikingly, only 2% of companies actually manage this trade-off well, outperforming on both growth and profitability in both good and bad times.
Integrative thinking shifts the question from “either/or” to “both/and”—holding two conflicting demands in tension and crafting a synthesis that transcends the apparent necessity for a trade-off. Kodak’s story illustrates the cost of failing to do this: in 2007, the company sold its profitable medical imaging division to focus on its floundering consumer digital business. It treated two strategic priorities as mutually exclusive when the real question was whether imaging, health care, and digital capabilities could reinforce each other—exactly the question Fujifilm answered by building a diversified portfolio around its core technologies.
A practical expression of integrative thinking is co-ambidexterity: the idea that every business unit should both execute on today’s model and learn its way into tomorrow’s. This embeds exploration directly into execution. For example, online gaming platform Roblox makes game creation simple and accessible for all its users. This allows players to build the experiences they most want in gaming while drawing inspiration from (and inspiring) others. The result is a cycle in which ideas spread and improve, producing more engaging gameplay and a broader range of games.
Every business unit should both execute on today’s model and learn its way into tomorrow’s.
To institutionalize integrative thinking, organizations need routines that keep both long- and short-term time horizons visible and resourced—in the same room, at the same time. Dual-horizon planning and budgeting processes, where investments in today’s and tomorrow’s business are evaluated together rather than in separate streams, prevent long-term bets from being quietly sacrificed to short-term pressure. Strategy scorecards that track forward-looking capability metrics—such as 3M’s new product vitality index, which measures the percentage of total sales generated from products introduced within the last five years; the number of experiments launched; or new partnerships formed—alongside financial results signal that exploration is not a distraction from performance but part of it. And joint financial-strategic governance, where the CFO and CSO co-own resource allocation decisions, can prevent the annual budget cycle from defaulting to incremental thinking.
Finally, strategists can use narratives to connect short-term actions to long-term purpose, keeping them aligned in people’s minds. Jeff Bezos exemplified this approach at Amazon. In a 2016 letter to shareholders, he repeatedly emphasized the importance of a “Day 1” mindset, which calls for executing with urgency to deliver a great customer experience today while simultaneously adopting the emerging trends that will reshape customer expectations tomorrow. By framing present performance and future discovery as two sides of the same commitment to customers, Bezos gave the organization a coherent way to pursue both time horizons at once.
To Harness Artificial Intelligence, Cultivate Critical Thinking
The fourth cluster of untamed issues concerns AI itself—not as a tool to aid decision making but as a force that is transforming what strategy work is. In our survey, nearly six in ten of our survey respondents said that considering the effects of AI is now central to their role, yet three-quarters admitted that they needed to develop their capabilities here.
As AI automates ever more of the analytical workflow, the role of human actors is shifting. As computation power becomes a new constrained strategic resource, the risk is that human judgment will atrophy. But as analyses, insights, and strategic options roll in, judgment calls must be made. These range from sense-checking analyses to evaluating trade-offs between options. The cost of being wrong increasingly outweighs the cost of being slow, so AI-generated recommendations must earn approval by surviving scrutiny of their assumptions, data, and logic.
As computation power becomes a new constrained strategic resource, the risk is that human judgment will atrophy.
Critical thinking about AI capabilities and output is the disciplined ability to assess the quality of machine-generated reasoning, detect shared blind spots across AI tools, and determine where human judgment must override algorithmic recommendation. New sources for strategic differentiation will rely on such skills as assessing validity and bias, designing decision processes, and weighing ethical
In practice, this means mastering two areas. First, the ability to ask the right question before running the analysis by engaging stakeholders, listening for inconsistencies, and probing what decision makers are truly aiming for. Second, triangulating rather than relying on a single output: framing questions in multiple ways, running analyses with different methodologies and assumptions, and paying attention to where outputs converge or diverge. Strategists should also ask how competitors might use similar tools and where advantage can emerge when multiple organizations are guided by comparable AI-generated recommendations.
To institutionalize critical thinking, organizations need routines that embed skepticism into the decision process. An assumption audit before any major AI-informed decision, where the team identifies the three hypotheses the model relies on most heavily and stress-tests each one, can catch blind spots before options become commitments. A red-team rotation—a small group that gets 48 hours to prepare the case against a recommended course of action and a dedicated slot in the decision meeting—ensures that recommendations are carefully judged rather than rubber-stamped. And clear rules for human override, specifying the categories of decisions where human judgment trumps algorithmic output, such as irreversible commitments or decisions with significant ethical stakes, give leaders both the permission and the obligation to exercise judgment when it matters most.
How to Choose the Right Mode
To identify which mode a given problem calls for, strategists can use a short set of trigger questions:
- Are the key variables in this problem reshaping each other? Could our action trigger responses that change the problem itself? If yes, use systems thinking.
- Does this problem require a solution that doesn’t exist yet? Does it challenge a core assumption our strategy is built on? If yes, use counterfactual thinking.
- Is this problem pressuring us to sacrifice one important goal for another? Does it span multiple time horizons? If yes, use integrative thinking.
- Could the available analysis give us false confidence in this decision? Does this decision involve consequences that go beyond what the data can capture? If yes, use critical thinking.
When multiple modes are triggered, this diagnostic signals that the decision needs several lenses, applied deliberately, rather than defaulting to whichever feels most familiar. When strategists apply the wrong kind of thinking to a problem, they create a false sense of rigor. The strategy function increasingly lies in recognizing which kind of issue the organization is facing, then activating the appropriate mode of thinking and organizational routines to plan effectively for the future.
