RAJESH MAHAPATRA · STRATEGY MEMOCEO AI THESIS · PAPER 062 / 630

Research Essays

The CEO’s AI Thesis

Rajesh Ranjan Mahapatra

A falsifiable CEO AI thesis that connects structural change, chosen advantage, commitments, stakeholder settlement and contradiction.

© 2026 Rajesh Ranjan Mahapatra. 21 min read

Executive and board leadership · Board AI governance

The CEO’s AI Thesis

A coherent enterprise claim about what changed, where the firm will play, how it will win, what it will commit, and which contradiction will make it change course.

By Rajesh Mahapatra · Reviewed portfolio draft · 2 September 2026

TLDR

  1. State a falsifiable connection between cheaper machine intelligence and a chosen source of enterprise value.
  2. Concentrate on an arena and activity system; name attractive work the firm will deliberately not pursue.
  3. Build advantage from distribution, context, workflow position, decision rights and learning loops, not a temporary model lead.
  4. Join platform, capital, talent, workforce settlement and risk boundaries in one commitment architecture.
  5. Protect contradictions with owners, dates and adaptation thresholds so conviction can guide action without becoming prophecy.

The CEO announces that every function will become AI-first. Business units add their existing projects to a new portfolio. Technology selects a common platform. Finance counts potential hours saved. Six months later, almost any proposal still fits the slogan, no meaningful activity has been refused, and teams disagree about whether the enterprise is pursuing cost, service, growth or risk reduction. The announcement created motion without strategic direction.

A CEO’s AI thesis is not an ambition, use-case catalogue or forecast of model capability. It is a falsifiable enterprise claim: an external structural change will alter a chosen arena through a specified production mechanism; the firm can compound a particular advantage; and a staged set of organisational commitments is justified before every uncertainty is resolved. It tells executives what must fit, what may probe, what will not receive shared capital, and what observation would make leadership revise the claim.

The thesis does not predict one technological path. Model costs, capability, regulation, supplier structure and customer behaviour may move differently across time. Its work is to coordinate choices while preserving the right to learn. Ten linked claims make that possible. Each carries an owner, evidence date, range rather than false precision, dependency and contradiction. Coherence lies in the connections, not in a single score.

An AI ambition cloud collapsing into a falsifiable enterprise thesisVague words such as transform, automate and lead converge into a compact thesis card containing arena, mechanism, advantage and contradiction.AI-FIRSTAUTOMATETRANSFORMLEADEVERYWHEREARENAMECHANISMADVANTAGECOMMITMENTCONTRADICTION
Figure 1. An ambition permits interpretation. A thesis constrains it with a mechanism, commitment and condition for revision.

Direction under uncertaintyA thesis is a coordinating claim, not a corporate belief

Strategy requires choice and fit across activities. Porter’s formulation is useful because an AI initiative does not become strategic merely by using a capable technology. It matters when it reinforces a distinct value proposition and a system of activities that competitors cannot reproduce by buying the same component. If access to a model becomes broadly available, advantage must sit elsewhere: customer access, trusted distribution, proprietary context rights, an embedded workflow, a physical network, a difficult operating integration or a faster learning loop.

The strong rival is emergent strategy. Mintzberg and Waters describe deliberate and emergent strategy as ends of a continuum rather than mutually exclusive camps. Under high uncertainty, many cheap local experiments can reveal customer demand, operational constraints and unexpected combinations. That is defensible. It becomes costly when scattered commitments produce incompatible platforms, duplicated controls, fragmented customer journeys, supplier lock-in or irreversible workforce changes before leadership says what kind of company those choices should create.

The answer is not to centralise every experiment. The CEO thesis supplies direction and common boundaries; local teams supply variation and evidence. Experiments may inherit the thesis, test an assumption inside it, or explicitly challenge it. Contradictory results are not disloyal. They are strategic information. What leadership must prevent is an experiment silently creating enterprise infrastructure or customer promises that narrow future choice without an acknowledged commitment.

March’s exploration and exploitation tension sharpens the resource question. The company needs enough exploration to discover a changed opportunity and enough exploitation to compound what works. Capital allocation, executive attention and shared platforms turn the rhetorical balance into actual strategy. Bower and Gilbert’s resource-allocation lens warns that realised strategy appears in funded positions, approved vendors, operating targets and leadership time, not only in the annual narrative.

Failure boundary. An explicit thesis fails when conviction hardens into prophecy, weak signals are classified as confirmation, contradictory teams lose resources, or the claim is broad enough to bless every project. Emergence fails when local option-making quietly commits the enterprise before anyone owns the direction.

Thesis syntaxWrite one enterprise sentence that exposes its assumptions

A useful draft can follow a demanding syntax: because a defined form of intelligence has changed within a stated horizon, the firm will concentrate on a chosen customer decision or workflow; it expects a specified value mechanism; it will compound named distribution, context, rights or learning advantages; it will commit a bounded set of capabilities, capital and role changes; and it will revise when a stated contradiction crosses a dated threshold. The sentence will be long. Its purpose is diagnostic. Any vague clause points to a claim the leadership team has not resolved.

The CEO can then separate the sentence into the ten register entries without losing the connections. This matters because functions naturally translate the thesis into their own nouns. Technology sees architecture, finance sees return, HR sees roles, product sees customers and risk sees exposure. The syntax keeps them attached to one mechanism. A context platform is not strategic if it does not serve the chosen arena. A cost case is not complete if the stakeholder settlement changes adoption. A risk limit is not effective if the adaptation rule allows dependent commitments to continue.

Use ranges where the evidence supports ranges. A horizon can be “within the next two planning cycles” rather than an invented month. A value mechanism can carry a downside and a break-even adoption boundary. The register should preserve which statements are observation, theory, modelling and management judgement. Confidence language is useful inside each claim, but aggregating it into one thesis confidence score would hide which dependency can overturn the whole system.

The enterprise thesis also needs a short list of non-choices. These may include refusing to build a proprietary foundation model, declining high-consequence autonomous action until takeover evidence exists, avoiding shared capital for disconnected personal-productivity tools, or postponing a market entry that lacks distribution rights. A non-choice is not permanent. It is the current consequence of the thesis and should change only when the contradiction register supplies a reason.

Structural change flowing through arena and production mechanism to company valueA chain connects a change in intelligence economics to a chosen arena, a production mechanism, an advantage and company value.STRUCTURALCHANGEARENAPRODUCTIONMECHANISMADVANTAGECOMPANYVALUE
Figure 2. The thesis must explain the middle. A technology trend does not cause enterprise value without a chosen arena, mechanism and advantage.

Claims 1–4From structural change to chosen advantage

1Structural change: what became cheaper, faster, available or possible?

Describe the external shift at the level that can be observed. Perhaps useful language transformation is cheaper, multimodal interaction is more accessible, autonomous tool use is reliable within bounded workflows, or customers expect a different response time. Add a time horizon and range. “AI will transform the industry” cannot be contradicted; “routine document interpretation will fall below our present unit cost while verification remains the constraint” can.

Separate capability from adoption and economics. A model can perform a task while integration, control, data rights or customer behaviour prevent value. A cost curve can fall while complementary investment raises total cost in the near term. Brynjolfsson, Rock and Syverson’s productivity J-curve gives a reason to expect measured benefits to lag intangible investment, but it does not excuse indefinite delay. The thesis needs a dated view of both component change and system adoption.

Register entry
Observed change, horizon, range, source, owner, dependency and the observation that would show the change is weaker or slower.

2Strategic arena: which customers, decisions, workflows or positions matter?

Choose where changed intelligence matters to this firm. The arena can be a customer decision, a recurring service journey, a professional workflow, a risk boundary or a market position. It should be narrow enough to exclude plausible investments. An insurer might concentrate on the claims evidence-to-settlement chain rather than “all insurance work”. A business-services firm might choose recurring client decision support rather than every document task.

State what will not be pursued through shared enterprise capital. Attractive local productivity uses may continue within common controls, but they should not borrow the strategic label unless they reinforce the chosen activity system. Local strategies can inherit the arena or submit an explicit challenge. They should not multiply into unrelated enterprise theses whose platform and talent requirements compete without a common choice.

Register entry
Chosen population, consequential decision, workflow boundary, excluded arenas, customer problem and reason this position fits the firm.

3Value mechanism: how does intelligence change revenue, service, risk, cost, speed or option value?

Trace cause and counterfactual. If the claim is cost reduction, show which work disappears, which verification and exception work appears, what adoption is required and how capacity becomes cash or growth. If the claim is service, show which customer outcome changes and why competitors cannot match it merely by purchasing a model. If the claim is risk, show the action boundary, loss route and cost of control. Acemoglu’s macroeconomic analysis is a warning against moving directly from task savings to broad productivity claims.

A rival explanation belongs beside the mechanism. Performance may improve because process standardisation, management attention, data cleaning or training accompanied the deployment. Those changes can still be valuable, but attributing them to the model distorts the next investment. The thesis should identify what comparison or staged rollout can distinguish the claimed mechanism from the rival.

Register entry
Value route, counterfactual, capture action, full cost, causal rival, expected timing and failure signal.

4Chosen advantage: what can the firm compound when models commoditise?

Do not anchor the thesis to a model lead that suppliers and competitors can erase. The chosen advantage might combine trusted distribution, contractual data rights, workflow access, context accumulated through service, physical assets, decision authority and a feedback loop competitors cannot lawfully or practically reproduce. Rivkin’s model of complex strategies explains how interacting choices can impede imitation, although complexity also makes internal search and learning harder.

The rights in the learning loop are as important as the data. Can the firm observe outcomes, correct errors, retain context, reuse evaluations and improve the system? Does the customer receive enough value and protection to continue contributing? Can the loop operate if the current supplier changes? A commodity model can strengthen a non-commodity activity system, but only when the firm has named and funded that system.

Register entry
Advantage bundle, imitation route, distribution and context rights, feedback ownership, supplier portability and erosion signal.

Activity-system fitTest whether the claims reinforce one another

Read the first four claims as a causal set. If the structural change is cheaper document generation but the arena is a trust-sensitive advisory decision, cost may not be the binding value mechanism. If the chosen advantage is proprietary context but customers will not grant reuse rights, the feedback loop is assumed rather than available. If the arena spans every function, no coherent activity system can guide capital. The register should flag such incompatibilities before executives negotiate them into vague wording.

Fit also appears across time. A reversible probe can rely on manual context preparation, but a scale thesis may require a governed context service. A temporary model lead can test demand, but it cannot remain the long-term advantage claim. A workforce settlement can be staged while task evidence develops, but customer promises should not expand faster than takeover and challenge capacity. Each stage must inherit the logic of the next without pretending the next commitment is already authorised.

Trade-offs make the fit visible. Choosing a deeply embedded workflow may sacrifice rapid horizontal expansion. Preserving supplier optionality may raise current integration cost. Building trusted distribution may require slower evidence and recourse design. Protecting apprenticeship may retain some independent practice that a narrow automation case would remove. These are not defects to edit out of a board paper. They are the costs of the chosen position and should be compared with the advantages they make possible.

Ten-claim thesis architecture with contradiction linksTen claim cards form two connected columns, while red contradiction links cross between structural, economic, workforce and risk claims.1 · STRUCTURAL CHANGE2 · STRATEGIC ARENA3 · VALUE MECHANISM4 · CHOSEN ADVANTAGE5 · SYSTEM COMMITMENT6 · CAPITAL + TALENT7 · STAKEHOLDER SETTLEMENT8 · RISK BOUNDARY9 · EVIDENCE + CONTRADICTION10 · ADAPTATION RULE
Figure 3. Coherence is relational. A contradiction in one claim can invalidate the capital, risk or adaptation claim linked to it.
Chosen-advantage flywheelA rotating flywheel connects distribution, context rights, embedded decisions and learning rights around a central customer settlement.DISTRIBUTIONCONTEXTDECISIONSLEARNINGCUSTOMERSETTLEMENT
Figure 4. Advantage compounds when distribution, context, decision access and learning rights reinforce each other while customers keep receiving acceptable value and protection.

Claims 5–7Translate direction into capability, capital and settlement

5System commitment: what platform, operating model, governance and product capabilities must exist?

The thesis should name shared capabilities without assuming one central product. Reusable identity, context services, evaluation, observability, tool control, incident response and decision records may lower the cost of many local systems. Product capabilities may differ by arena. The operating model must show which choices are enterprise standards, which are delegated and how local contradictions reach leadership.

Adner’s ecosystem-as-structure lens reminds the CEO that the value proposition may depend on actors the firm does not control. Suppliers, distributors, customers, professional reviewers and regulators must align sufficiently for the mechanism to work. A platform is not a capability if the organisation lacks integration skill, adoption rights or a viable partner settlement.

Register entry
Required capabilities, build or buy boundary, activity owners, ecosystem dependencies, sequencing and capability test.

6Capital and talent commitment: what must be funded, led and redesigned?

State the complementary investment that sits around model access: data and context preparation, workflow redesign, evaluation, control, change, skills, product discovery and decommissioning. Assign leadership attention as a scarce resource. A thesis that asks every unit to experiment while funding no shared evaluation or role redesign is a wish transferred down the hierarchy.

Use a commitment ladder. Cheap reversible probes can explore demand or technical feasibility. Shared context infrastructure, role architecture, supplier contracts and customer promises are harder to reverse. Discovery-driven planning makes assumptions and learning milestones visible before the hard commitments. Effectuation adds another useful view: under genuine uncertainty, executives can constrain affordable loss and build commitments with partners rather than claim a forecast they do not possess.

Register entry
Capital by stage, talent and role changes, executive attention, complementary assets, affordable loss and release gates.

7Stakeholder settlement: who receives gains, carries transition and remains protected?

Productivity is not a settlement. The thesis should state how customers share faster service or lower friction, how workers move into redesigned roles, who owns reskilling, which affected parties receive recourse and how accountability survives delegation. Gains may fund growth, price, service quality, resilience or returns. Leadership should make the choice visible rather than allow local budgets to decide it implicitly.

A workforce settlement is strategic because knowledge, adoption and legitimacy affect the mechanism. Removing routine work can weaken apprenticeship or concentrate expert review. Keeping every manual step can erase the value. The design needs task change, learning routes, capacity, incentives and a fair account of whose workload rises. It must also state which red lines protect people even when the economic case is strong.

Register entry
Gain distribution, customer promise, role redesign, skill transition, affected-party consequence, recourse and accountable executive.
Commitment ladderFive ascending steps move from a reversible observation and probe through shared capability to operating-model and capital commitments that are harder to reverse.OBSERVEPROBECAPABILITYOPERATINGMODELCAPITAL +CUSTOMERPROMISEREVERSIBILITY DECREASES →
Figure 5. Evidence should mature before the least reversible commitments. A probe does not authorise an operating-model or customer promise by implication.

Claims 8–10Bound loss, protect contradiction and specify adaptation

8Risk boundary: what is the maximum credible loss, the red line and the residual-risk owner?

The thesis needs an enterprise boundary, not only project controls. Define maximum credible loss across customers, workers, capital, rights, resilience and strategic option. State red lines the value case cannot override, how exposure is capped during learning, which commitments are reversible and who may accept what remains. NIST’s lifecycle governance is useful here, but management must translate broad functions into decision rights and thresholds for its chosen arena.

Supplier dependence is a thesis risk when context, evaluations or tool authority cannot move. Technical optionality is not established by a second model name on a slide. Management should test which artefacts migrate, how long an alternative takes and what customer or operating obligations persist. A portability failure may stage the commitment, force a different architecture or contradict the chosen advantage.

Register entry
Consequence bound, red lines, reversible state, concentration, residual-risk authority, intervention and exit condition.

9Evidence and contradiction: what observation would weaken the thesis or support a rival?

Confirmation is abundant when a claim is broad. The register should privilege observations that can change resource allocation. Record primary evidence, its date and boundary, a rival explanation and a disconfirming observation. Assign contradiction ownership to an executive or team with access and standing. Evidence should be able to travel upward without being rewritten as a delivery issue.

Gavetti’s behavioural theory of strategy places cognition and representation near strategic action. The CEO’s picture of the opportunity shapes search, so the company needs mechanisms that challenge the picture, not only implementation. A red team, a differently designed probe, customer research or an independent financial reconciliation can do this. Contradiction is protected when it has a forum, an adaptation threshold and capital consequences.

Register entry
Leading evidence, observation date, confidence range, rival mechanism, disconfirming signal, contradiction owner and decision effect.

10Adaptation rule: when will leadership commit, stage, probe, redirect or stop?

A thesis earns persistence by saying when persistence ends. Set dates and thresholds before signals arrive. Commit when the mechanism, advantage and operating capability cohere. Stage when the direction is plausible but a named evidence or settlement condition remains. Probe when a contradiction can be resolved with bounded exposure. Reframe when evidence points to a different source of advantage. Withdraw when the mechanism fails full-cost, adoption, control or causal review.

The rule should specify which dependent commitments freeze while the thesis is under review. Otherwise a narrative may be questioned while contracts, recruitment and platform integration continue to harden it. Revision is not a loss of credibility when it follows an announced rule. Refusing to revise after the contradiction threshold is crossed is.

Register entry
Review date, thresholds, route, frozen dependencies, decision forum, accountable CEO and communication obligation.
Emergent-strategy option field converging with deliberate directionMany bounded experiment dots move through a field toward a deliberate strategic corridor, while one contradictory opportunity redirects the corridor.BOUNDED OPTIONSDELIBERATE CORRIDORCONTRADICTORY OPPORTUNITY
Figure 6. Direction gives experiments a corridor. A sufficiently strong contradiction can redirect the corridor rather than being forced back into it.

Negative controlsWhat the register must do when the story breaks

AI-first fog

No arena, mechanism or exclusion is specified. Withdraw the thesis and stop dependent enterprise commitments until leadership makes a strategic claim that evidence can challenge.

Use-case emergence

Local experiments reveal customers will pay for a new service, contradicting the cost thesis. Reframe around the service advantage after testing whether the pattern travels beyond the local context.

Commodity trap

The model lead disappears, but distribution, workflow position and proprietary feedback rights remain. Reframe the thesis around that activity system instead of defending a temporary component advantage.

Supplier dependency

Context, evaluations and tool authority cannot move. Stage the commitment behind a portability condition or redesign before a larger customer or capital promise hardens the dependency.

Workforce settlement

Productivity gains have no role transition, learning path or distribution of gains. Stage wider exposure behind a named settlement rather than asking local managers to absorb the change.

Rival explanation

Process standardisation and management attention may explain the improvement. Run a bounded probe that can distinguish their effect from the model mechanism before scaling the claim.

Bounded commitment

Invest in reusable context and evaluation capability now, while placing the product bet behind dated customer evidence. This preserves option value without pretending the market is proved.

Stop case

The mechanism fails adoption, full-cost, control and causal review. Withdraw the thesis and stop contracts or role changes that depend on it.

Worked business-services thesis with contradiction forcing reframingAn original cost-reduction thesis encounters customer demand evidence and redirects toward a service-growth thesis based on context and distribution.ORIGINAL THESISAutomate document workReduce delivery costScale a model advantageREFRAMED THESISEmbed decision serviceGrow recurring revenueCompound context rightsand trusted distributionCUSTOMERDEMAND
Figure 7. The contradiction does not merely cancel the first thesis. It reveals a stronger source of advantage and changes the commitment architecture.

Worked thesisFrom document cost to recurring decision service

Consider a business-services firm whose first claim is that generative AI will reduce document-production cost. It funds reusable context, document evaluation and a staged delivery assistant. Early evidence shows modest cost improvement after verification, but clients repeatedly ask for the reasoning context, ongoing monitoring and decision follow-up. The local experiments reveal willingness to pay for a recurring decision service rather than cheaper documents.

The contradiction register prevents leadership from classifying the requests as feature demand inside the old thesis. The strategic arena moves from document workflow to recurring client decisions. The value mechanism moves from labour substitution to service growth and retention. The advantage moves from model quality to trusted distribution, embedded workflow, proprietary context rights and outcome feedback. Capital shifts from document automation alone to product, account integration, evaluation and service operations.

Reframing still needs evidence. Customer requests may reflect novelty or sales attention. A staged product test should compare willingness to pay, adoption, delivery economics and outcome quality. Workforce design changes too: experts may spend less time producing routine documents and more time framing decisions, challenging evidence and governing the feedback loop. The thesis becomes stronger because the contradiction changes both the advantage and the commitments, not because executives tell a better story.

Contradiction protocolGive inconvenient evidence a route to resource allocation

A register becomes ceremonial if contradictions are merely logged. Each material signal needs an owner who is not rewarded only for delivering the current thesis, a forum with authority, a review date and a pre-agreed consequence. The consequence might release a bounded probe, freeze a supplier commitment, move product capital, revise a workforce plan or withdraw a customer promise. Without a resource effect, leaders can acknowledge the evidence while realised strategy continues unchanged.

Classify contradictions by what they attack. A boundary contradiction shows that the observed evidence covers a different population or workflow. A mechanism contradiction shows that the claimed cause does not explain the outcome. An advantage contradiction shows that a rival can imitate or a supplier controls the learning loop. A commitment contradiction shows that capital, talent or stakeholder terms cannot support the direction. An adaptation contradiction shows that the organisation cannot reverse what the thesis calls reversible. Classification identifies which claims must be recompiled.

Weak signals should not trigger theatrical strategy changes. The adaptation rule can require replication, a threshold across customers or a bounded comparison. Yet leadership must avoid raising the evidence bar only after a threatening result appears. Pre-registering the observation, date and decision effect reduces that temptation. It also lets teams design experiments that are informative enough to matter rather than producing another favourable demonstration.

When the thesis changes, communicate the reason in the same architecture. State which structural assumption, mechanism or advantage changed; which commitments continue; which are frozen; how stakeholders are affected; and what the new contradiction would be. This maintains direction during revision. The organisation learns that strategic conviction and intellectual honesty are compatible because both operate through visible claims and decisions.

Interactive instrumentCEO AI Thesis Compiler

The Compiler stores an owner, dated evidence, dependency, contradiction and adaptation note for each of the ten claims, then tests cross-thesis signals. It returns a decision route and next evidence, never a confidence or maturity score.

Live strategy memo

THESIS ROUTE

Commit and scale the coherent thesis

The arena, value mechanism, advantage, capability and settlement cohere, while risk and adaptation boundaries remain usable.

Next evidence: reconcile realised customer value and full economics at the next dated stage gate.

Complete claim records: 0 of 10.

Figure 8. Ten claim records make the thesis inspectable. Cross-thesis signals choose one of five action routes without hiding contradiction in a score.

CEO operating cadenceUse conviction to allocate, and contradiction to adapt

The CEO should own the integrated thesis even when executives own individual claims. Strategy can prepare the architecture, technology can own system capability, finance can reconcile economics, HR can own workforce transition and risk can challenge boundaries. None should optimise its claim independently. A cheaper platform that traps context may weaken advantage. A faster workforce change without a learning path may weaken adoption and control. A strong customer signal may justify moving capital before every technical preference is settled.

Review cadence should follow the three clocks of capability, organisational change and governance rather than one quarterly rhythm. Fast technical observations may change a probe. Slower customer adoption may govern a product stage. Capital, role and risk-appetite changes need their own authority. The contradiction register links these clocks by stating which observation reaches which forum and which dependent commitment pauses.

The board receives the thesis as management’s falsifiable enterprise position and applies the proof questions from Paper 061. Directors should see the arena, mechanism, advantage, commitments, stakeholder settlement, risk boundary and adaptation rule. They do not need every local experiment. They do need material contradictions, changed exposure and resource movements that alter the original commitment.

A useful thesis makes saying no easier and changing course more credible. It refuses generic projects that borrow the AI label without reinforcing the chosen system. It funds shared capabilities that improve several aligned bets. It permits bounded probes that may overturn the claim. Leadership earns the right to persist not by sounding certain, but by specifying the evidence under which persistence remains rational and the threshold at which it will stop.

Strategy, economics and governance spineReferences

  1. Porter, M. E. (1996), “What Is Strategy?”, Harvard Business Review. hbr.org/1996/11/what-is-strategy.
  2. Mintzberg, H. and Waters, J. A. (1985), “Of Strategies, Deliberate and Emergent”, Strategic Management Journal. doi.org/10.1002/smj.4250060306.
  3. March, J. G. (1991), “Exploration and Exploitation in Organizational Learning”, Organization Science. doi.org/10.1287/orsc.2.1.71.
  4. Teece, D. J., Pisano, G. and Shuen, A. (1997), “Dynamic Capabilities and Strategic Management”, Strategic Management Journal. verified DOI record.
  5. McGrath, R. G. and MacMillan, I. C. (1995), “Discovery-Driven Planning”, Harvard Business Review. hbr.org/1995/07/discovery-driven-planning.
  6. Sarasvathy, S. D. (2001), “Causation and Effectuation”, Academy of Management Review. doi.org/10.5465/amr.2001.4378020.
  7. Gavetti, G. (2012), “Toward a Behavioral Theory of Strategy”, Organization Science. doi.org/10.1287/orsc.1110.0644.
  8. Rivkin, J. W. (2000), “Imitation of Complex Strategies”, Management Science. doi.org/10.1287/mnsc.46.6.824.11940.
  9. Adner, R. (2017), “Ecosystem as Structure”, Journal of Management. doi.org/10.1177/0149206316678451.
  10. Brynjolfsson, E., Rock, D. and Syverson, C. (2021), “The Productivity J-Curve”, American Economic Journal: Macroeconomics. doi.org/10.1257/mac.20180386.
  11. Acemoglu, D. (2024), “The Simple Macroeconomics of AI”, NBER Working Paper 32487. doi.org/10.3386/w32487.
  12. NIST (2023), AI RMF Core. airc.nist.gov AI RMF Core.
  13. OECD (2023), G20/OECD Principles of Corporate Governance 2023. doi.org/10.1787/ed750b30-en.
  14. ISO/IEC (2023), ISO/IEC 42001: Artificial intelligence management system. iso.org/standard/42001.
  15. Jensen, M. C. and Meckling, W. H. (1995), “Specific and General Knowledge, and Organizational Structure”. doi.org/10.1111/j.1745-6622.1995.tb00283.x.
  16. Bower, J. L. and Gilbert, C. G. (eds.) (2005), From Resource Allocation to Strategy. Harvard Business Review Press record.
  17. Rumelt, R. P. (2011), Good Strategy/Bad Strategy. Penguin Random House record.