Strategic Thinking Cannot be Divorced from Strategic Doing
Why Henry Mintzberg’s Emergent Strategy Is the Antidote to Your AI Roadmap
Henry Mintzberg spent fifty years watching traditional linear approaches to strategy fail. While other management thinkers described how strategy should work, Mintzberg studied how it actually works. His conclusion was radical and remains uncomfortable: strategy is not a plan you design in a boardroom. It is a pattern that emerges from the daily decisions of the people doing the work. If you are leading AI transformation by enforcing a roadmap, Mintzberg has bad news.
His ten “schools” of strategy formation represent the most comprehensive taxonomy of strategic thought ever produced. He has been criticised for descriptive bias (telling us what happens without prescribing what should), for underweighting the value of analytical planning, and for a romantic attachment to craft that can tip into anti-intellectualism.
1. The Fallacy of Separation: Thinking Cannot Be Divorced from Doing
Mintzberg’s most vivid metaphor is the potter at the wheel. The potter does not begin with a detailed blueprint. She begins with a lump of clay, an intention, and the skill of her hands. As the wheel turns, the clay responds; sometimes cooperating, sometimes resisting, sometimes suggesting possibilities she had not imagined.
The final (strategic) product is a combination of intention and emergence: what she planned to make, what the clay allowed, and what she discovered along the way.
Strategy formation is the same. The separation of formulation from implementation is the core error. If strategy is a craft, then the person who formulates cannot be different from the person who implements, because implementation generates the information that shapes formulation. The MBA-trained strategic planner who arrives with analytical frameworks but no intimate knowledge of the business is the potter who has studied chemistry but never touched clay.
In the AI era, we can repeat this error precisely. We separate the “thinkers” (AI Strategists, Enterprise Architects) from the “doers” (Developers, Prompt Engineers, the people who actually write specifications and watch what the AI generates). Mintzberg would recognise this as fatal. If your AI strategist is not touching the clay, if they are not writing specifications, seeing what the AI actually produces, and adjusting their understanding based on what they discover, they are hallucinating a strategy. You cannot formulate a viable AI transformation plan from a PowerPoint deck. You can only find it by getting your hands dirty.
This connects directly to Peter Drucker’s reunification of thinking and doing. Where Drucker argued that the knowledge worker must define the task, Mintzberg goes further: defining the task is doing the work, because the act of defining reveals information that changes what you are trying to define. The specification is not a document you write before the work begins. It is the work. Ron Heifetz arrives at the same conclusion from leadership theory: adaptive challenges cannot be solved by experts in a back room. They require the people with the problem to do the learning. The AI strategist who formulates the plan without touching the clay is doing precisely what Heifetz warns against; taking back the work that belongs to the people who must live with its consequences.
2. Strategy as Pattern, Not Plan
Mintzberg defined strategy as “a pattern in a stream of decisions.” He distinguished between Intended Strategy (what you wrote in the document), Deliberate Strategy (what you planned and actually executed), and Emergent Strategy (the successful patterns that formed without being intended). His key insight, drawn from decades of empirical research: most realised strategy is emergent, not deliberate.
This does not mean planning is useless. It means planning is one input to strategy, not the mechanism by which strategy is created. The plan is valuable as a starting gesture; its primary value is in the conversations it forces and the alignment it creates, but it is not a blueprint.
Your job is not to enforce the roadmap. It is to detect the successful patterns emerging from the teams and amplify them. This echoes Weick’s insight that understanding follows action: people act, patterns form, and retrospective sensemaking gives those patterns meaning. Mintzberg provides the organisational evidence for what Weick describes as a cognitive process. Stacey provides the theoretical explanation: plans are not blueprints but gestures that call forth responses. The forty-seven-page AI roadmap is an intended strategy whose actual effect will be determined by thousands of responses the planners cannot predict. The emergent patterns are not noise in the signal. They are the signal.
Richard Normann extends this with a spatial metaphor: the map (your mental model of how value is created) shapes what you can see in the landscape (the actual configuration of actors and resources). When leaders fight emergent AI usage, they are defending an obsolete map. The teams experimenting with AI tools are not violating the map. They are exploring a landscape that the map cannot yet represent. Leadership, in Normann’s terms, is the willingness to let the landscape redraw the map.
3. The Craft of Management
Mintzberg argued that management is not a science (despite what the MBA programmes teach), nor a profession, but a craft. It is learned through experience, context, and intimate knowledge of the material, not through abstract analysis. He was deeply critical of management education that separates learning from practice, producing graduates who can analyse but cannot manage.
This applies directly to something like specification-driven development in AI. Writing a specification for an AI agent is not a bureaucratic exercise. It is a craft in exactly Mintzberg’s sense. It requires what Anthony Giddens would call “practical consciousness”: the tacit, embodied knowledge of how the domain works that cannot be fully articulated but can be expressed through skilled practice. The domain expert who has spent fifteen years understanding how insurance claims are adjudicated carries knowledge that no requirements template can capture. But they can learn to express that knowledge as a specification, if they are given the right tools and the psychological safety to experiment.
Bandura adds the psychological precondition: people will not attempt the craft unless they believe they can learn it. Self-efficacy, the domain-specific belief in one’s capability to perform a particular task, predicts whether someone will persist through the inevitable early failures of learning a new craft or interpret those failures as confirmation that the craft is beyond them. The first specification exercise must be designed to produce a mastery experience, not a performance test.
If you treat AI adoption as the scientific implementation of a vendor tool (select, configure, deploy, measure) you will fail. You must treat it as the cultivation of a new craft: the ability to articulate intent with precision. And like all crafts, it is learned by doing, not by reading the manual.
4. Configuration Determines Transformation
Mintzberg identified that organisations fall into distinct configurations, each with a dominant coordinating mechanism and a characteristic set of resistance patterns. You cannot transform them all the same way.
Machine Bureaucracy coordinates through standardisation of work processes: rules, procedures, governance frameworks define how work is done. AI here threatens the “Technostructure,” the middle-management layer whose power derives from defining and controlling those processes. Expect, with certainty, that this layer will create AI governance frameworks, AI risk assessments, and AI development standards that add procedural burden without enabling capability. This is not malice; it is the Technostructure doing exactly what it was designed to do. Weber diagnosed this with unsettling precision a century ago: the rational-legal system works perfectly for the problems it was designed to solve. AI transformation is not one of those problems. Mintzberg’s machine bureaucracy is Weber’s ideal type of bureaucracy; one configuration among several, not the inevitable form of all organisation.
Professional Bureaucracy coordinates through standardisation of skills. Professionals (developers, architects, engineers, lawyers, doctors) are hired, trained, and trusted to exercise judgment within their domain. They resist any attempt to standardise their processes or outputs. Most enterprise technology organisations are Professional Bureaucracies. The developers hold the power because they hold the knowledge.
If you try to transform a Professional Bureaucracy using Machine Bureaucracy tactics (mandates, process charts, top-down governance) the professionals will reject it. This is not bloody-mindedness; it is the defining characteristic of professional work. Bourdieu explains the mechanism: each configuration is a field with its own forms of capital. In a Professional Bureaucracy, the professionals’ capital (their embodied skill, their technical judgment, their peer recognition) is the dominant currency. Transformation that devalues this capital without providing a credible path to new capital will be met with rational resistance, not irrational stubbornness.
Transformation in a Professional Bureaucracy requires convincing the professionals that the new tool enhances their craft rather than replacing their judgment. The specification must be positioned as a professional instrument, not a management control mechanism.
An Adhocracy coordinates through mutual adjustment: direct, informal communication between experts working on novel problems. Transformation here is easier to start (the culture supports innovation) but harder to sustain (adhocracies resist the standardisation needed to scale). Expect enthusiastic but unsustainable adoption.
The diagnostic question is: which configuration currently dominates your organisation, and what configuration is the transformation moving toward? Because the resistance patterns, coordination challenges, and leadership requirements differ fundamentally across configurations.
Applying Seligman’s lens, the learned helplessness that accumulates from failed change programmes manifests differently in each configuration, and must be addressed differently.
5. The Manager’s Reality: Brevity, Variety, Fragmentation
Mintzberg’s earliest research exploded the myth of the reflective, strategic manager. He found that managers work in short bursts, are interrupted constantly, prefer verbal communication to written reports, and spend almost no time in the kind of reflective analysis that management textbooks assume is their primary activity. There is no flow. There is only fragmentation.
If your transformation governance relies on long written reports and formal steering committees, you are designing for a manager who does not exist. Real coordination happens in the hallway conversations, the Slack threads, the five-minute stand-ups; what Henri Fayol called the “bridge” and what Mintzberg demonstrated empirically. An effective AI transformation injects guidance into the fast-paced flow of work rather than waiting for the monthly committee that nobody reads the papers for.
Kahneman explains why: the fragmented manager is operating in System 1, fast, intuitive, pattern-matching. The strategic report is written for System 2, slow, analytical, deliberate. You are communicating in the wrong cognitive register.
This has a practical design implication. If you want to change how your organisation adopts AI, change the conversations that happen every day, not the strategy document that sits on SharePoint. Change the language, and you change the thinking. Change the thinking, and the patterns shift. And when the patterns shift, that is the strategy.
(An Organisational Prompt is something you can do now...)
Organisational Prompt
Look at the last three months of decisions your teams have made about AI: the tools they adopted, the experiments they ran, the workarounds they built. Do not consult the roadmap. Consult the commit logs, the Teams channels and the procurement requests. Map what actually happened, not what was supposed to happen.
Ask: “What pattern do these decisions reveal about what we actually value?” Then ask the harder question: “Am I amplifying that pattern, or fighting it?”
Further Reading
Henry Mintzberg: The Rise and Fall of Strategic Planning - The definitive demolition of the idea that strategy can be formalised. If you read one Mintzberg book, read this one.
Henry Mintzberg: Mintzberg on Management - The best single-volume overview of his thinking on configurations, coordination, and the craft of management.
Henry Mintzberg: Managers Not MBAs - His critique of management education as divorced from practice. Uncomfortable reading for anyone with an MBA.
Henry Mintzberg, Bruce Ahlstrand, and Joseph Lampel: Strategy Safari - The ten schools of strategic thought, and why none of them alone is adequate.
Disclaimer
I write about the industry and its approach in general. None of the opinions or examples in my articles necessarily relate to present or past employers. I draw on conversations with many practitioners and all views are my own.