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View corpus contextOrganizational agility is not one thing: CEOs, executive teams and frontline operations require distinct capabilities and measures. Treating agility as a single score risks misinterpreting AI adoption and productivity effects and undermines targeted policy and firm-level interventions.
Strategic leadership and agility in organizations
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review_meta
low evidence
7/10 relevance
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Strategic agility is multi-dimensional and varies across organizational levels, functions, and contexts, so researchers and practitioners should measure and intervene on level-specific forms of agility rather than using a single aggregate construct.
Citation observations
Cumulative provider counts captured on specific dates; providers are never combined.
Purpose This paper explores the use of agile responses in organizations at three different management levels: CEO, executive team and enterprise wide. The authors compare and contrast three different case examples to highlight that each organizational level involves different goals, processes, skill sets, challenges and solutions. These cases underscore the need to define agility more precisely across different levels, business functions and contexts. Design/methodology/approach The authors examined the growing literature on strategic agility and developed a bespoke agility survey via an executive program with supply chain managers in Asia, as fully shown in the Appendix. The survey itself, plus the pilot data that the authors collected and summarized, underscore the need to customize survey-based agility measures to specific organizational or functional settings. The authors’ three main business cases illustrate this further at different levels in an enterprise. Findings The authors’ analysis shows that strategic agility can differ greatly from operational agility and that each type can vary markedly across situations and organizational levels. The lack of clear definitions of agility in the academic literature complicates attempts at general taxonomies or prescriptive guidance that is invariant across cases. Research limitations/implications The three cases the authors selected for comparison and contrast were based on their own familiarity with the respective situations. Each was also widely covered in general business news when the authors wrote this paper. In the absence of an agreed taxonomy for business situations involving agility, these practice-based cases helped to illustrate the conceptual points the authors wanted to make. Practical implications The best remedy in practice would be for leaders to examine how agility is currently defined in their own organization across level and functions, by means of surveys, interviews or external benchmarks. With that in hand, agility alignments can be better tailored and improved. Originality/value This paper contributes to the agility literature by highlighting its weak conceptual foundations in theory and by highlighting the contextual nature of agility in practice. By separating agility into CEO, executive-team and enterprise-wide levels, the authors offer a framework for resolving the concept’s persistent definitional ambiguity. This multi-level perspective also helps practitioners clarify which type of agility they are trying to deploy. It also helps avoid one-size-fits-all prescriptions and improve the practical value of agility oriented initiatives.
Summary
Main Finding
Strategic agility is not a single, uniform capability: it differs substantially across organizational levels (CEO, executive team, enterprise-wide), across functions, and across contexts. Because academic definitions of “agility” are weak and inconsistent, both research and practice benefit from treating agility as a multi-level, context-specific construct and from developing tailored measurement and alignment approaches.
Key Points
- Agility varies by level:
- CEO-level agility emphasizes strategic judgment, vision-setting and boundary-spanning decisions.
- Executive-team agility focuses on coordination, decision speed among senior leaders, and translating strategy into prioritized initiatives.
- Enterprise-wide (operational) agility centers on process flexibility, rapid execution, and frontline capabilities.
- Goals, processes, skills, challenges and solutions differ at each level; one-size-fits-all prescriptions are ineffective.
- The literature lacks a consistent taxonomy or clear operational definitions of agility, complicating comparative research and theory-building.
- Practical remedy: organizations should explicitly map how “agility” is defined across levels and functions (via surveys, interviews, benchmarks) and then design level-appropriate interventions.
- Original contribution: framing agility as multi-level clarifies definitional ambiguity and guides both practitioners and researchers to more useful, context-sensitive measures and prescriptions.
Data & Methods
- Literature review: synthesis of growing literature on strategic agility to identify conceptual gaps.
- Empirical instrument: bespoke agility survey developed through an executive program with supply chain managers in Asia; details and pilot data summarized in the paper’s Appendix.
- Case-method: three practice-based business cases (selected from situations familiar to the authors and widely covered in business media) illustrate differences in agility at CEO, executive-team and enterprise-wide levels.
- Limitations acknowledged:
- Case selection driven by authors’ familiarity and news coverage, limiting generalizability.
- Absence of an agreed taxonomy constrains ability to produce invariant prescriptive guidance.
- Pilot survey illustrates need for customization rather than offering a universal measure.
Implications for AI Economics
- Measurement matters for causal inference: empirical studies of AI adoption and productivity should measure firm agility at the appropriate organizational level(s). Aggregating a single “agility” score risks misattributing AI impacts that are actually mediated by level-specific capabilities.
- Heterogeneity in adoption and returns: multi-level agility helps explain why some firms realize large productivity gains from AI while others do not. Models of AI diffusion and firm investment should include heterogeneity in CEO strategic orientation, executive-team coordination, and operational flexibility.
- Endogeneity and complementarities: agility is a potential complement to AI capital (tools, data, algorithms). Econometric work should consider interaction effects between AI investments and level-specific agility (e.g., AI tools may yield returns only where operational processes and frontline skills are agile).
- Policy design and targeting: policies promoting AI diffusion (skills training, subsidies) should be tailored. For example, enterprise-level retraining may be ineffective without executive-team capability to reconfigure workflows or CEO willingness to change strategy.
- Microdata collection: researchers should incorporate bespoke survey modules (modeled on the paper’s approach) into firm-level AI surveys, distinguishing CEO, executive-team and operational agility to improve identification and external validity.
- Labor-market implications: differential agility across levels affects the speed and distribution of workforce transitions caused by AI—firms with strong operational agility may reskill faster; those lacking executive-team agility may delay adoption and prolong structural adjustment.
- Market structure and competition: multi-level agility can be a source of competitive advantage that amplifies the market power of early AI adopters; antitrust and industrial policy analyses should account for organizational agility as a persistent firm-level moat.
Assessment
Paper Typereview_meta
Evidence Strengthlow — The paper is primarily a conceptual literature synthesis supplemented by a small, pilot survey and three illustrative case studies; there is no systematic empirical identification or causal estimation, and the empirical components are limited, non-representative, and exploratory.
Methods Rigorlow — Methods consist of a narrative literature review, a bespoke pilot survey developed in an executive program (limited detail and likely non-random sample of supply-chain managers in Asia), and three practice-selected cases; measurement development and sampling are preliminary and there is no formal causal identification, robustness checks, or broad validation.
SampleNarrative synthesis of prior literature (sources not enumerated here); a bespoke agility survey piloted with supply-chain managers participating in an executive program in Asia (pilot data summarized in Appendix); three illustrative business cases selected by the authors based on familiarity and media coverage.
Themesorg_design adoption productivity skills_training labor_markets
GeneralizabilityCase studies selected for familiarity and media prominence rather than representativeness, limiting external validity, Pilot survey sample limited to supply-chain managers in Asia and likely non-random, constraining cross-sector and cross-region generalization, No validated, standardized agility taxonomy presented, reducing comparability across studies, Findings are conceptual and descriptive rather than causally established, so applicability to causal claims about AI impacts is limited
Claims (12)
| Claim | Direction | Outcome | Confidence & Evidence | Details |
|---|---|---|---|---|
| Strategic agility is not a single, uniform capability; it varies substantially across organizational levels, functions, and contexts. Organizational Efficiency | mixed | Variation in strategic agility across organizational levels, functions, and contexts |
Reading fidelity
high
Study strength
medium
|
n=3
|
| CEO-level agility emphasizes strategic judgment, vision-setting, and boundary-spanning decisions. Decision Quality | positive | CEO-level strategic judgment, vision-setting, and boundary-spanning decision capability |
Reading fidelity
high
Study strength
low
|
n=3
|
| Executive-team agility focuses on coordination, decision speed among senior leaders, and translating strategy into prioritized initiatives. Team Performance | positive | Executive-team coordination, senior-leader decision speed, and strategic prioritization |
Reading fidelity
high
Study strength
low
|
n=3
|
| Enterprise-wide operational agility centers on process flexibility, rapid execution, and frontline capabilities. Organizational Efficiency | positive | Operational process flexibility, execution speed, and frontline capability |
Reading fidelity
high
Study strength
low
|
n=3
|
| Goals, processes, skills, challenges, and solutions differ across organizational levels, making one-size-fits-all agility prescriptions ineffective. Organizational Efficiency | negative | Effectiveness of uniform versus level-specific agility interventions |
Reading fidelity
high
Study strength
low
|
n=3
|
| The literature lacks a consistent taxonomy and clear operational definitions of agility, which complicates comparative research and theory-building. Governance And Regulation | negative | Consistency and operational clarity of strategic-agility concepts in the literature |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Organizations should map how agility is defined across levels and functions and use the resulting distinctions to design level-appropriate interventions. Organizational Efficiency | positive | Alignment of agility definitions, measurement, and interventions across organizational levels |
Reading fidelity
high
Study strength
low
|
not reported
|
| A bespoke agility survey was developed through an executive program involving supply chain managers in Asia, with pilot data used to illustrate the need for customization rather than a universal measure. Organizational Efficiency | mixed | Validity and applicability of a customized strategic-agility measurement instrument |
Reading fidelity
high
Study strength
low
|
not reported
|
| The paper uses three practice-based business cases to illustrate differences in agility at the CEO, executive-team, and enterprise-wide levels. Organizational Efficiency | mixed | Cross-level differences in strategic agility |
Reading fidelity
high
Study strength
low
|
n=3
|
| The generalizability of the case evidence is limited because case selection was driven by the authors’ familiarity with the situations and their coverage in business media. Other | negative | External validity and generalizability of the case evidence |
Reading fidelity
high
Study strength
high
|
n=3
|
| AI-adoption and productivity research should measure agility at the appropriate organizational levels because aggregating agility into a single score may misattribute effects that are mediated by level-specific capabilities. Firm Productivity | negative | Accuracy of causal attribution in studies of AI adoption and productivity |
Reading fidelity
high
Study strength
speculative
|
not reported
|
| Level-specific organizational agility may complement AI capital, so empirical models should consider interactions between AI investments and CEO, executive-team, and operational agility. Firm Productivity | positive | Returns to AI investment conditional on organizational agility |
Reading fidelity
high
Study strength
speculative
|
not reported
|