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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteAmbidextrous leadership means combining behaviors that open up exploration with behaviors that help a team focus, refine, and implement what it learns. In an AI-driven organization, that can mean making room to test where AI might improve a service, then setting the priorities and controls needed to turn a validated use into dependable work. It is a useful way to think about balancing innovation and execution—not a proven formula for making AI projects succeed.
What ambidextrous leadership means
The idea joins two kinds of leadership behavior. Opening behaviors invite new ideas, experimentation, autonomy, and learning. Closing behaviors clarify priorities, set boundaries, monitor execution, and help turn useful ideas into repeatable practice. The framework links opening with exploration and closing with exploitation: using and improving what is already known.
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Exploration seeks novelty and learning; exploitation emphasizes efficiency, reliability, and implementation. They are complementary demands, not mutually exclusive leadership styles. A team may need room to discover possibilities and, once it has evidence, the discipline to decide what is worth adopting.
How the balance applies to AI work
For AI-related work, exploration could involve asking where AI might help customers or solve a problem in a new way, then allowing bounded trials to reveal what is feasible. Exploitation begins when a use case has been validated: leaders can prioritize it, define constraints, monitor how it performs, and integrate it into a dependable workflow.
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#1 Best Overall
| Exploration and opening | Exploitation and closing |
|---|---|
| Generate options and learn what might work | Select promising options and implement them |
| Allow experimentation within appropriate boundaries | Set clear priorities and constraints |
| Value novelty and learning | Value efficiency and reliability |
| Run temporary trials | Build validated uses into repeatable practice |
This is a practical application of the exploration–exploitation distinction, not an AI-specific leadership recipe established by research. A 2026 Academy of Management Proceedings abstract examined AI adoption and dynamic ambidexterity at the firm level, but it did not test whether ambidextrous leadership causes better outcomes in AI-driven organizations. A separate 2026 preprint proposes a framework for measuring leadership behaviors in AI-enabled work; it is not an established ambidextrous-leadership measure.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the evidence says—and what it does not
Findings on ambidextrous leadership are promising but not conclusive. In a 2023 registered report in The Leadership Quarterly, Florian E. Klonek, Fabiola H. Gerpott, and Sharon K. Parker reported: “We only found partial support for the hypotheses from ambidextrous leadership theory.” The work included two randomized experiments, with 395 participants in Study 1 and 229 in Study 2. The result cautions against treating the framework as a reliably proven cause of innovation. Read the 2023 registered report.
Other studies report findings consistent with the framework, but each has limits. A 2016 employee-level study by Hannes Zacher, Alecia J. Robinson, and Kathrin Rosing used self-report data from 388 employees and reported links between leaders’ opening and closing behaviors, employees’ exploration and exploitation behaviors, and innovative performance. Its sample is not a workforce-wide estimate. Read the 2016 study abstract.
A 2020 study of 98 high-technology small and medium-sized enterprises in the UK reported associations between opening and closing leadership behaviors and employee innovation behaviors. It also reported that adaptive or flexible leadership mediated the relationship with employees’ ambidextrous innovation behaviors. These are findings from a specific study context, not proof that the same pattern will hold in every organization. Read the Bangor University research record.
Rank #3
AI-specific findings should be kept distinct from leadership evidence. A 2026 Academy of Management Proceedings abstract reports a longitudinal analysis of 922 Chinese listed firms with AI patents: AI adoption enhanced dynamic ambidexterity in that sample, interaction capability strengthened the positive relationship, and learning capability weakened it. This is a conference proceedings finding about firms and AI adoption, not a demonstration that a particular leadership style produces better AI outcomes. Read the proceedings abstract.
Akben and Coyne’s 2026 preprint proposes an AI Leadership Battery with 36 behaviorally specific subdimensions across 11 theory-specified content families. That proposal concerns a measurement framework for AI-enabled work; it is neither an established standard nor a measure of ambidextrous leadership. Read the preprint.
Quick Recap
What leaders can take from the framework
- Make space for exploration without implying that every idea will become an operating practice.
- Use clear priorities and constraints to help teams assess experiments rather than letting experimentation become an end in itself.
- When a use proves valuable, shift attention toward implementation, monitoring, and reliable execution.
- Do not assume there is a universal schedule for switching between opening and closing behaviors; the studies do not establish one timing rule or one balance for every team.
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