Leading Through Disruption: Board and Executive Strategies in the Agentic AI Era

How are Boards and Executive teams staying ahead of AI-driven disruption? In this post, we highlight core insights from our webinar featuring experts from Harbinger Group, i3 Talent LLC, and Change Management Specialists, LLC. Discover how leadership roles are shifting, which frameworks support balanced decision-making, and what it takes to embed a forward-thinking culture in the face of agentic AI.

Artificial Intelligence (AI) is transforming organizations at an unprecedented pace. For Boards and Executive leaders, AI’s disruptive potential is no longer an abstract concept—it’s a pressing strategic priority. In the third episode of the “Tech CXO Roundtable” webinar series—hosted by Marilyn Pearson Hendricks (MPH) of WorkTech Advisory—a panel of industry experts reveals how leaders can approach agentic AI to balance innovation, risk, and operational excellence. Speakers include Dr. Vikas Joshi (Founder & CEO, Harbinger Group), Dr. Steven Hunt (Founder, i3 Talent LLC), and Tim Juergensen (Founder & CEO, Change Management Specialists, LLC).

Whether you’re charged with shaping enterprise strategy or ensuring solid oversight at the Board level, the insights below offer practical and forward-thinking guidance. Read on for key takeaways, real-world quotes, and high-impact strategies your leadership team can implement.

1. The Expanding Board Mandate in an AI-Driven World

We’re peeling back the onion on how Boards and Executives can navigate technological disruption while maintaining strategic alignment. Never in our world have we had as much change as we do today—and maybe it’s the least amount of change we’ll ever have again. The only way we know how to do this is to put our heads together.”
– Marilyn Pearson Hendricks (MPH)

What We Heard

Leading organizations recognize that Boards must assume a wider range of responsibilities in the AI era, from anticipating market upheavals to guiding ethical considerations. The panel underlined how AI has become a core component of corporate strategy rather than a peripheral tech concern.

• Boards Are Shifting Focus: AI’s breakthrough capabilities have become a board-level issue, merging innovation oversight with the usual governance role.
• Forward-Looking Mandates: Dr. Vikas Joshi reminded us that “change is a fact of life,” requiring consistent vigilance rather than a short-term crisis response.

What We Understood

When AI disruptions emerge, Boards can no longer limit themselves to standard risk management. Instead, they must proactively evaluate how AI intersects with long-term objectives and stakeholder expectations.

• This expanded role pushes Boards to integrate technology considerations directly into strategic direction rather than simply reviewing them at year-end.
• The board's regular review of AI’s impact on organizational purpose, culture, and market standing positions it as a trusted innovator and guardian.

What Is Required

Below are suggested actions or initiatives to keep Board mandates relevant and effective in fast-changing market conditions.

1. Strategic Review: Schedule frequent AI-themed discussions, assessing risk, competitive shifts, and enterprise readiness.
2. Ongoing Education: Engage in AI-focused workshops or executive briefings, so governance keeps pace with rapid technological shifts.
3. Vision & Values: Ensure AI-driven projects align with core principles, preserving a sense of mission even as you embrace advanced capabilities.

2. Balancing Innovation with Oversight

“We found when we didn’t have a structured process for innovation, decisions became haphazard and lacked consistency. With intentional frameworks, Boards and Executive teams could weigh risks and benefits more effectively—creating a stable path to innovate and move forward.”
– Tim Juergensen

What We Heard

The panel revealed that truly effective innovation takes shape when bold initiatives meet rigorous scrutiny. A well-defined process that includes risk assessment and near-term operational needs ensures that visionary projects remain stable.

• Innovation vs. Caution: While leaders see the value of pursuing cutting-edge AI solutions, they recognize that “throwing caution to the wind” jeopardizes stability.
• Intentional Models: Panelists highlighted the importance of established frameworks, preventing an ad-hoc or purely reactive approach.

What We Understood

Mature organizations treat AI adoption like any other significant investment: it should be ambitious enough to create new value, yet measured enough to protect core operations.

• Finding equilibrium between short-term demands and long-term vision prevents over-correction—either stifling new ideas or pursuing them blindly.
• A transparent chain of accountability gives senior leaders confidence that innovative ideas won’t derail financial or reputational standing.

What Is Required

Below are practical measures for how Boards and Executives can maintain agility and control in AI-heavy environments.

1. Innovation Framework: Document guidelines for moving AI projects from concept to pilot to full implementation.
2. Risk Mapping: Create a living risk register detailing operational, legal, and ethical challenges, ensuring both Boards and Executives remain informed.
3. Transparent Communication: Build cross-functional collaborations so finance, HR, IT, and legal have an ongoing seat at the table, shaping balanced decisions.

3. Prioritizing People in the Face of Technological Disruption

“We reduced nurse turnover from 38% to 8% in about eight months. The key wasn’t just cost-savings—it was patient satisfaction and valuing our staff. That focus on the employee experience drove better engagement and operational outcomes.”
– Tim Juergensen

What We Heard:

The discussion emphasized that people remain the cornerstone of sustainable innovation. Even the most advanced AI programs fall short if employees don’t trust, understand, or see the benefits in them.

• Employee Experience: According to Dr. Steven Hunt, organizations often underestimate the intangible but critical gains from an empowered workforce.
• Real-Time Feedback: Leaders suggested ongoing conversations or “stay interviews” to surface immediate challenges rather than relying solely on annual reviews.

What We Understood

True AI-driven transformation isn’t strictly about cutting costs or automating tasks—it’s about enabling people to do better work, often in new ways.

• When employees feel supported, they’re more likely to embrace AI technologies that streamline repetitive functions or improve scheduling flexibility.
• Retaining top talent and enhancing customer or patient satisfaction often go hand in hand, linking employee-centric policies to bottom-line outcomes.

What Is Required

Below are steps for maintaining a high-trust, people-focused environment amid sweeping technological changes.

1. Human-Centric Design: Involve actual end-users early in AI pilots, shaping tools around practical needs.
2. Workforce Metrics: Track not just headcount and costs, but also engagement, retention, and satisfaction scores.
3. Continuous Learning: Offer hands-on training and transparent AI deployment updates so employees understand the ‘why’ behind new systems.

4. Skills Needed at the Board and Executive Levels

“Boards and Executives have unique dispositions shaped by their roles. The friction between the two can actually be healthy—so long as it drives thoughtful decisions, especially in the face of rapid AI innovations.”
– Dr. Vikas Joshi

What We Heard:

Today’s senior leaders must cultivate a balanced skill set—strategic foresight and operational awareness—to navigate AI’s ever-expanding influence. This includes understanding technical concepts enough to evaluate both hype and opportunity.

• Personal AI Familiarity: If leaders haven’t explored generative AI in their own workflows, they risk underestimating or misjudging its organizational impact.
• Strategic Mindset: An “innovation-first” approach demands an ability to see beyond quarterly gains, ensuring AI aligns with broader corporate objectives.

What We Understood

Siloed leadership—where Boards only check financials and Executives only run day-to-day operations—can cause missed chances or abrupt course corrections.

• Bridging knowledge gaps fosters mutual respect and clarity.
• Leaders who understand AI’s strengths and limitations can steer initiatives that are both ambitious and pragmatically feasible.

What Is Required

Here are action items for building the right capabilities across both Boards and C-suites.

1. Hands-On Testing: Challenge Directors and senior leaders to incorporate a generative AI tool into their daily tasks for a set period.
2. Focused Competency Profiles: Revisit hiring and performance standards to emphasize AI literacy and collaborative innovation history.
3. Cross-Pollination: Host internal “demo days” where technical teams and business units regularly showcase successes, failures, and prototypes.

5. The Future of Governance in AI-Driven Organizations

“Fast, agile change management is crucial for adopting AI. In many cases, large-scale ‘launches’ are replaced by iterative rollouts and weekly check-ins—because the old annual survey or top-down approach is just too slow.”
– Audience Q&A / Paraphrased Summary

What We Heard:

Panelists and participants alike emphasized that governance systems must keep pace with AI’s high velocity. Traditional timelines and annual planning cycles often lag behind the realities of AI-driven transformation.

• Role of Change Management: Shifting from monolithic rollouts to agile experimentation ensures organizations can pivot quickly if needed.
• Keeping Your True North: Core mission and values anchor teams amid uncertainty, preventing tech solutions from misaligning with the organization’s purpose.

What We Understood

Accelerated adoption doesn't mean compromising diligence. Instead, governance should evolve to handle multiple pilot projects, iterative learning, and real-time course corrections.

• Without centralized oversight, fragmentation can breed duplicative efforts or potential liabilities.
• By uniting under a shared vision, teams become more open to ongoing evaluation of AI’s impact.

What Is Required

Summarized below are methods that boards and execs can employ for agile yet principled governance.

1. Mission Alignment: Confirm that each AI proposal resonates with the organization’s broader purpose—be it customer care, social impact, or revenue growth.
2. Scalable Change Strategies: Deploy pilot groups and gather immediate feedback, rolling out success stories methodically while containing risks.
3. Empowered Teams: Form cross-functional committees with clear mandates around compliance, data ethics, and workforce culture, ensuring shared accountability.

Summary & FAQ

Summary

In an era where agentic AI can reshape entire business models overnight, leadership must move beyond check-the-box governance. Board and Executive teams now share a greater responsibility to spot opportunities, manage risks, and shape ethical, sustainable tech adoption strategies. By embracing a people-focused mindset, structured innovation frameworks, and continuous upskilling, organizations can confidently harness AI for both operational efficiency and transformative growth.

FAQ

1. Q: Must Board members master AI technologies?
   A: Deep expertise isn’t necessary, but familiarity with AI’s capabilities is key. Informed leadership fosters balanced oversight and strategic thinking.

2. Q: How can we balance cost reduction with employee morale?
   A: Aim for both. AI that streamlines tasks can also free employees for higher-value work, thereby boosting engagement.

3. Q: What’s a recommended way to handle AI risks?
   A: Embed AI considerations into your existing governance. Identify data security, compliance, or workforce concerns early, then update your risk register as needed.

4. Q: Is large-scale training always required for AI rollouts?
   A: Not necessarily. Modular pilots or micro-training can be more effective than a massive, one-time program.

By taking these insights to heart, Board and Executive leaders can forge a more dynamic governance approach—one that meets evolving market demands while preserving the organization’s core values.