By Amanda Fajak, Consulting Solutions' Global Culture Practice Leader

This article is the first of a three-part series exploring how AI, leadership, and culture intersect to shape organizational performance. In this series, we examine the human and organizational levers that determine whether AI becomes a tool, or a true performance multiplier.

Many organizations are investing heavily in AI to improve speed, insight, and productivity. At the same time, leaders are grappling with how to empower their people to make better decisions in more complex environments. Organizations tend to treat these as separate conversations, but they are the same one.

AI delivers its greatest value only in environments where employees have meaningful autonomy. Without decision authority, clarity, and trust, AI becomes another layer of tooling. With autonomy, it becomes a performance accelerator.

When organizations intentionally design for both, they create workplaces where people can act with confidence, experiment responsibly, and translate insight into impact.

The role of autonomy: Creating the conditions for good decisions

Autonomy isn’t about removing structure. It’s about giving people the authority to make decisions within clear boundaries. When employees understand expectations and feel trusted to act, they engage more deeply with their work and take greater ownership of outcomes.

In our work with clients, we consistently see autonomy show up as a differentiator in environments where change is constant and speed matters. Teams with decision authority move faster, surface issues earlier, and adapt more effectively than those waiting for approval at every step.

Key benefits of autonomy include:

• Increased engagement and ownership
• Faster, more informed decision-making
• Greater adaptability and creative problem-solving
• Stronger retention and satisfaction

AI as an enablement tool, not a replacement

AI changes how work gets done by reducing friction. It automates repetitive tasks, surfaces insights quickly, and supports better judgment at scale. But AI doesn’t make decisions: people do.

The organizations seeing the most value from AI are not simply deploying tools. They are enabling employees to use those tools thoughtfully in the context of their work. Access, literacy, and relevance matter far more than volume of technology.

When AI is positioned as an enablement tool, it helps employees:

• Spend less time on manual work and more on judgment-based tasks
• Access insights that improve decision quality
• Experiment and learn more quickly
• Collaborate across teams and geographies with shared data

Where autonomy and AI come together

The real shift happens when autonomy and AI reinforce one another. Autonomy creates permission to act. AI provides the insight to act. Together, they change how work moves through an organization.

1. Faster problem-solving: Autonomous teams equipped with AI can identify issues and respond without unnecessary escalation. AI provides context and pattern recognition; autonomy enables timely action.
2. Healthier experimentation: Autonomy encourages teams to test ideas responsibly. AI shortens feedback loops, helping teams learn quickly and adjust before small experiments become large risks.
3. More personalized ways of working: When employees can adapt AI tools to their roles, workflows improve. Productivity increases not because work speeds up, but because it fits better.
4. Scaled learning: As teams apply AI in different contexts, effective practices spread organically. Innovation scales through use, not mandate.

What this looks like in practice

We see this combination at work across industries:

• Spotify: Autonomous squads use AI-driven analytics to iterate quickly and respond to user behavior in real time.
• ‍GitLab: With a fully remote and highly autonomous model, teams use AIto support code review, workflow management, and collaboration at scale.
• ‍Salesforce: Teams apply AI-driven insights with flexibility, allowing them to refine customer engagement approaches continuously.

These examples share a common thread: AI is effective because people use AI as part of the decision-making toolkit and are trusted to use it.

A note of nuance

Autonomy without clarity can create inconsistency. AI without context can overwhelm teams. Not every role or organization is ready for the same level of empowerment at the same pace.

Successful adoption requires intentional design: clear goals, shared standards, and investment incapability-building. When those elements are in place, autonomy and AI reinforce one another rather than compete.

How leaders can move forward

For leaders, the path forward is less about choosing autonomy or AI and more about aligning them intentionally:

1. Build trust through clarity: Define outcomes and guardrails so employees understand where they can act independently.
2. Invest in AI literacy: Ensure teams understand how and when to use AI tools effectively.
3. Encourage responsibile experimentation: Create space to test, learn, and adjust without fear of failure.
4. Connect autonomy to purpose: Help employees see how their decisions support broader organizational goals.

Conclusion

Autonomy and AI are often discussed as separate levers. In practice, they work best together. When employees have both the authority to act and the insight to act wisely, organizations become more adaptable, resilient, and effective.

For leaders, the opportunity is to move beyond tool deployment and focus on how work actually gets done. By pairing autonomy with AI, organizations don’t just improve efficiency. They create environments where people can do their best work, consistently.

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Be sure to check back here for the second article in the series on how AI mirrors and amplifies your culture: strengths, gaps, and all.

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