For the artificial intelligence (AI) economy, we propose a principal worker model where each knowledge worker is both a task architect and an AI agent orchestrator. As task architect, the worker divides each task into subtasks and delegates some to AI agents. As agent orchestrator, the worker optimizes outputs from AI agents and synthesizes all outputs into a coherent deliverable. Workers who augment themselves with AI agents produce more and earn more. To reap productivity gains, organizations must implement policy changes on how they develop workers and incentivize them to use AI effectively.
AI competition is widely framed as a winner-take-all race. Mobile consumer data for the AI assistant category from 2023 through 2025 suggests otherwise: three strategies coexist, and all are growing. Scale (ChatGPT), adjacency (Gemini), and premium specialization (Claude) capture value in strategically distinct ways. Major launches reward the launcher without measurably harming rivals. These archetypes are not unique to AI; they recur whenever a disruptive technology opens a market before competition settles. For managers, the most important question is which strategy their distribution, economics, and customer base can sustain.
Addressing environmental crises requires firms to pursue sustainability transformation rather than incremental change. Drawing on socioemotional wealth theory and the ability-willingness paradox, this article examines how family involvement shapes the transformation of family businesses toward circular business models. Using a mixed-methods design that combines survey data from 1,400 Swiss firms with case studies, we identify control-value alignment as a mechanism through which family businesses overcome willingness constraints and enable circular transformation. The findings challenge prevailing assumptions by showing that family involvement can facilitate transformative sustainability change and offer actionable guidance for leveraging governance, long-term orientation, and collaboration.
A core promise of Open Strategy is that strategic transparency translates into superior strategic outcomes. Yet this depends on a fundamental premise: organizational members must actively engage with the information provided. It can be conceptualized as engaged transparency, or the social processes through which transparency is collectively made meaningful. This article shows that engaged transparency rests on four conditions—accessibility, attention, applicability, and authenticity—that can be established through a combination of material and social enablers. Engaged transparency enhances strategic understanding and leads to the formation of informed strategic judgments which should not be confused with strategic alignment.
Dynamic capabilities are foundational to competitive advantage, particularly in business environments characterized by deep uncertainty due to rapid technological change and geopolitical disturbances. Chinese firms are not just good imitators but also powerful innovators. Stereotypes must change, and American (and European) firms have much to learn from Chinese management: their speed of decision making, the commitment to innovation, and steadfast attachment to winning. Chinese government support should not be underestimated, and it has helped reinforce an ecosystem-building mentality of leading Chinese companies, which are emerging as more-than-a-match for many leading US tech firms. There are sobering lessons for Western executives and policy makers alike.
How often does your innovation portfolio (your budgeted innovation projects) fail to deliver strategic change because it consists of incremental initiatives or serves partisan objectives? Senior leaders often think the problem lies in weak strategy or weak organizational creativity. But, based on feedback from seventy CEOs and CTOs of large organizations, this article shows that something else is going on. The problem is often the result of how innovation portfolios are assembled. The standardized nature of the most widely used innovation portfolio methods leads to portfolio choices that don’t align with the strategy. This study shows how management can take back strategic control.
Managing innovation ecosystems requires firms to balance collaboration and competition while maintaining strategic differentiation. Inspired by the natural phenomenon of crown shyness-where trees create structured gaps to optimize resource sharing-this article introduces a governance framework for structuring interfirm boundaries and resource allocation. Through an analysis of real-world business ecosystems, five principles emerge: boundary modulation, structural adaptation, competitive insulation, resource partitioning, and dynamic role orchestration. This framework extends existing theories by offering practical strategies for firms navigating co-opetition, digital transformation, and platform economies. It provides business leaders with actionable insights to foster resilient, high-performing innovation ecosystems.
Brand collaborations are widely used to generate attention, yet many fail to create lasting value. This is because brands focus too much on who to partner with rather than on how to design the collaboration. Using the Omega/Swatch collaboration and drawing on interviews and search data, this article develops a playbook for designing effective collaborations. Successful collaborations require each brand to contribute something unique, brand identities to remain distinct, and added value for both consumer bases. They also need to balance similarity and differentiation to avoid substitution and shift focus from short-term hype to sustained cross-brand spillovers.
Once considered rare, unicorn start-ups are now a global phenomenon. This article identifies the key motives for acquisition in unicorns and extends David Teece's dynamic capabilities framework (CMR, Winter issue 2026) to demonstrate how founders sense, seize, and transform acquisitions to successfully scale in a winner-takes-all platform market. In this context, acquisitions serve a three-pronged purpose: one, to achieve market dominance by growing market share, by diversifying into new markets, and by matching, mitigating, or eliminating rivals; two, to access strategic resources; and three, to resolve complex, idiosyncratic, and temporal trigger points in the scaling process. In terms of organizational scaling, external stakeholders, including rival firms, business partners, and particularly investors, are essential to developing the dynamic capabilities of sensing and seizing acquisitions that drive market expansion. However, it is the founding team that is crucial to transforming the resources acquired through acquisitions to resolve trigger points. They do this by reconfiguring and recombining resources, particularly technology and know-how, and by empowering entrepreneurial teams to create unicorns with unicorns, facilitating autonomous, innovation-driven growth.
In times of radical uncertainty marked by geopolitical conflict, technological disruptions, societal transformations, and climate risk, scenario planning is critical for strategists. In this introduction to the special issue on scenario planning, we showcase scenario planning as a dynamic, integrative approach for strengthening strategic decision-making, facilitating organizational learning, and enhancing management amidst uncertainty without trying to predict the future. We highlight what we see as the collective contributions and managerial takeaways of this special issue that underscore the relevance of scenario planning for organizations seeking adaptability, resilience and success in turbulent environments, and suggest directions for future research.
Merging scenario planning's broad view of alternative futures with the analytical structure of option game models offers a powerful tool for strategic decision making-clarifying when to commit (game theory) to secure advantage and when to remain flexible (option theory) under uncertainty. This is especially relevant in sectors with high growth opportunities under competitive pressure-such as AI infrastructure, semiconductors, mining, and major acquisitions-where few players compete on scale, technology, and speed. A step-by-step scenario framework and two illustrative applications demonstrate its practical use. Strengthening narratives with quantifiable elements-such as growth options and competitive dynamics-shifts valuation from static cash-flow projections to strategic trajectories.
Scenario planning is often promoted as a way to challenge assumptions and prepare organizations for uncertainty. Yet little is known about what happens when scenarios confront leadership bias and internal power dynamics. Drawing on an autoethnographic study of a 2006 scenario planning effort at NASA's Johnson Space Center, this article reveals how strategic persistence and organizational politics initially limited leadership's acceptance of scenarios developed outside the senior team. Despite this resistance, elements of these scenarios influenced strategy over time through parallel initiatives, partnerships, and innovation efforts. The article highlights how leaders can use scenario planning not only to imagine alternative futures but also to navigate resistance and embed strategic change in complex organizations.
For almost two decades, digital leaders grew as asset-light firms, scaling on software, data, and talent. The arrival of generative AI changed that logic. Compute and energy are now production inputs, not background utilities. They demand chips, cooling, sites, grids, and permits, and therefore massive capital and operating capabilities. Yet ownership of those assets is not a one-size-fits-all solution. Firms can choose from a continuum: on-demand cloud, committed cloud capacity, dedicated servers, leased data center space, hybrid core-plus-cloud, or full ownership. In this new landscape, how should AI-driven firms, from mid-sized adopters to hyperscalers, secure capacity and what must leaders do next?
well as generative and agentic Al tools. While market growth forecasts are optimistic, organizations face significant adoption challenges. Through several years of fie research across 33 European organizations, this article identifies 70 key automation challenges and provides analysis of the most critical. Practice-oriented research maps these challenges to specific project phases and organizational perspectives, at the same time providing actionable mitigation strategies. The article reveals how organizational context (size, industry, regulatory environment, culture) shapes automation outcomes and offers tailored guidance on issues such as sourcing external expertise versus building internal capabilities, and governing decentralized development models. This practical guide serves organizations currently automating processes, or planning to do so, helping them navigate complexity for more effective digital transformation.
Intuitive logics is a prominent scenario planning method of strategic foresight that organizations use to plan in the context of uncertain future operating environments. Designed to counter linear forecasting approaches, intuitive logics is a method for envisioning and embracing multiple futures. Rooted in the works of Herman Kahn and Pierre Wack in military and corporate contexts, intuitive logics values gut feeling and tacit knowledge to foster creativity and challenge conventional thinking. Despite the name, and the importance of intuition in intuitive logics intuition remains poorly defined and operationalized in scenario practice. This article addresses this by integrating insights from psychology and management intuition research with the intuitive logics literature. Seven key themes, found in both disciplinary settings, offer practical recommendations to advance the use of intuition in the intuitive logics method thereby enriching strategic dialogue and enhancing organizational adaptability in uncertain contexts. In practical terms, bringing intuition research into scenario planning could lead to the development of scenarios that better capture and make actionable the experiences and tacit knowledge of managers as they work to navigate their organizations toward unknown futures.
In response to the climate crisis, companies are committing to net-zero greenhouse gas (GHG) emissions. Yet decarbonization remains challenging in globally dispersed supply chains, where upstream indirect emissions throughout the value chain (called Scope 3) can be up to 28 times higher than direct emissions. Drawing on data from twenty-five global firms, this article identifies five mechanisms companies use to engage suppliers: codes of conduct, financial instruments, digital platforms, supplier training, and co-innovation. It analyzes these mechanisms and explores the extent to which companies implement them beyond tier 1 suppliers to support the path toward net-zero GHG emissions.
Incumbent firms struggle to renew themselves. Structural ambidexterity balances the exploitation of existing business with the exploration of new opportunities. But these inconsistent strategic agendas generate intense emotional challenges: Senior team frustration over conflicting priorities, board-driven pressures, hostile inter-unit emotions between exploitative and exploratory units, and precarious dynamics within exploratory teams. These emotional challenges undermine renewal efforts and are an underappreciated cause of organizational decline. Senior teams can address them by fostering emotional engagement with the future, expanding organizational identity, instilling discipline in exploration, and embedding empathy and self-awareness. CEOs can transform emotional hurdles into sources of innovation and renewal.
Generative artificial intelligence (GenAI) is growing in popularity, yet insights on its application to business model innovation (BMI) are scarce. Drawing on a qualitative, multiphase study involving interviews, focus groups, and digital diaries with strategy consultants, we explore how professionals engage with GenAI during BMI. Our findings suggest strategy professionals engage with GenAI through what we term reflexive augmentation, which represents the deliberate, critical engagement with GenAI to decide which tasks should and should not involve GenAI and which tasks to automate or augment through GenAI. We show how this process is shaped by four tensions related to trust, skills, value-add, and client disclosure. We offer actionable insights for managing human-AI collaboration, advancing debate on augmentation and automation at the micro-level, and suggest how organizations can support effective GenAI integration in innovation contexts.
The authors combine scholarship from social entrepreneurship and systems literature to identify two dominant pathways used by mission-driven organizations to achieve large-scale social impact. The scaling impact approach expands the reach or depth of a proven solution by unit-level expansion. The impact at scale approach, by contrast, works at a population level to address the problem at scale. Four original case studies illustrate how organizations translate these approaches into strategies to address large-scale social problems. The four strategies are: (1) expanding through scale, (2) expanding through scope, (3) growing through systems optimization, and (4) growing through systems reinvention.
