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This webcast will demonstrate “The Connected Enterprise” framework through real-world Cyber and AI proof points, showing what happens when business strategy and risk management are not aligned, when undisciplined innovation cultures suppress risk discussions, when narrow thinking hamper enterprise risk exposure assessments, and when metrics fail to drive strategic action. 

We will show you where the Pillar failures occur, why the interconnection matters, and how organizations with mature Connected Enterprise architectures gain strategic resilience when it matters most.

For Board members, CEOs, General Counsels, CROs, CISOs, and risk leaders responsible for turning risk intelligence into strategic agility. 

About the Presenter:
Astrid Yee-Sobraques, FRM, CISSP is the senior risk executive Fortune 100 financial institutions call when complex risk and regulatory challenges bring previous efforts to a standstill. Over 25 years at GE Capital, AIG, Citibank, and PwC, she has honed expertise across Enterprise Risk Management, Strategic Advisory, Regulatory Compliance, Digital Transformation, and Cyber Security spanning Banking, Asset Management, and P&C Insurance globally. As the Risk Sherpa, she is known for her “risk connectivity” approach—integrating people, processes, and data to strengthen how organizations anticipate, manage, and respond to cascading risks. Astrid serves on GARP’s New York Chapter Advisory Committee and in October 2025, she released the Connected Enterprise framework—the first systematic approach to elevate ERM from foundational discipline to strategic engine.

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The answer lies in mastering four interconnected challenges that define the new leadership mandate for the AI age.

1. The Trust Calibration Challenge

AI doesn’t just make mistakes—it makes mistakes confidently.

I was initially skeptical about integrating AI into my process. What I didn’t expect was that somewhere in this process of testing, calibrating, and gradually expanding my use of AI tools, I would cross a crucial threshold: I had formed a working relationship with AI, and I couldn’t imagine operating without it now.

While my initial skepticism was personal, the dilemma it raises is systemic: how do you develop trust in a system that demands perpetual skepticism? This challenge is fundamental to cultural governance. Boards must ensure that Management actively fosters a culture of healthy skepticism and psychological safety necessary to challenge AI output and properly “calibrate trust.” 

The answer lies in what I call ‘strategic delegation’ – instructing AI to create output within defined parameters and subject to rigorous quality controls.

Perhaps most importantly, I’ve learned to watch for bias reinforcement. AI tends to build on the assumptions and frameworks that I provide rather than challenging them. This means that we, the human partners, must deliberately ask it to consider alternative perspectives or play devil’s advocate.

2. The Cognitive Dependency Risk

The ease of AI collaboration—perfectly patient, always responding thoughtfully—creates a new baseline for work interactions. This convenience presents two distinct risks to human capability:

Social Atrophy: If we become accustomed to streamlined, frictionless interaction, how will teams hone the essential skills we build through navigating the natural complexities of human relationships? Reading social cues, managing different communication styles, handling pushback, and working through disagreements remain foundational for team effectiveness.

Critical Thinking Dilution: There is a deeper concern about cognitive dependency—that regular AI collaboration might gradually weaken our ability to think through problems independently, analyze information critically, and generate original insights without technological assistance. For Boards, this is a talent risk. Boards must ensure AI deployment structures actively promote up-skilling to prevent the strategic risk of cognitive dependency in the workforce. AI must serve as an amplifier, not a cognitive crutch.

3. The Great Risk Expansion

AI fundamentally expands what we must govern—and transforms how we create value. Yes, AI can amplify our work through pattern recognition, policy drafts, and enhanced analysis. But AI cannot be held accountable, think critically about context, or own the outcome.

The risk function isn’t shrinking; it is evolving into something more critical. As risk professionals, we now must govern AI use itself, manage new attack surfaces, address model risk, and oversee digital workers (AI agents). AI agents making autonomous decisions require robust governance, accountability frameworks, and rigorous oversight mechanisms. This expanded scope is the new baseline for organizational risk.

4. Navigating the AI Paradox

AI’s greatest strength—its velocity and scale—also represents its greatest risk without human oversight.

To manage the risks defined above, Boards must focus on oversight risk. Oversight is required to enforce critical human review and human checkpoints where context, judgment, or ethics are material. With global frameworks developing, here’s a 6-point navigation system for Board discussions and implementation:

1. Assume Dual-Use and Red Team Relentlessly – Assume adversaries will weaponize every AI capability you deploy.
2. Human-AI Partnerships: Critical Thinking Required – Design a clear scope of authority: AI for pattern recognition and speed; humans for context, judgment, and accountability.
3. Strategic Human Checkpoints – Define the materiality of decisions requiring human-in-the-loop oversight.
4. Velocity Governors – Build in intentional friction at critical junctures where human oversight is non-negotiable.
5. Transparency as Security – Make AI decision-making visible and auditable.
6. Cross-Functional AI Governance – Security ensures agent and identity guardrails; Privacy and Compliance review training data lineage and model risk; Data Owners approve AI use on datasets; IT enforce technical controls; Business Units own outcomes and risk appetite.

The Path Forward

As with any emerging risk, the key is conscious navigation rather than unconscious drift. The AI paradox is a permanent condition to manage. Success lies not in eliminating the risk, but in building organizations that can manage the paradox while maintaining human agency.

AI adoption is about amplifying human expertise while maintaining the human elements essential for complex decision-making and teamwork. That’s the practical expression of AI leadership that Boards and C-suite executives must champion throughout their organizations.

The evolution of purposeful leadership and ethical risk management is underway.

About the Author:

Astrid Yee-Sobraques, FRM, CISSP is the senior risk executive Fortune 100 financial institutions call when complex risk and regulatory challenges bring previous efforts to a standstill. Over 25 years at GE Capital, AIG, Citibank, and PwC, she has honed expertise across Enterprise Risk Management, Strategic Advisory, Regulatory Compliance, Digital Transformation, and Cyber Security spanning Banking, Asset Management, and P&C Insurance globally. As the Risk Sherpa, she is known for her “risk connectivity” approach—integrating people, processes, and data to strengthen how organizations anticipate, manage, and respond to cascading risks. Astrid serves on GARP’s New York Chapter Advisory Committee and in October 2025, she released the Connected Enterprise framework—the first systematic approach to elevate ERM from foundational discipline to strategic engine.

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• Natural Conflict Zones – Transforming tensions around documentation, risk-based decisions, and standardization into strategic choices rather than buried dysfunction
• The Quality-Risk Revelation – How the EU AI Act’s Quality Management System is a blueprint for mature ERM—and why regulations worldwide now mandate demonstrated integration
• Governance Mechanisms That Work – Five Board-level interventions that make alignment mandatory and dysfunction visible

Drawing on Astrid’s signature risk connectivity approach, this session provides both a diagnostic lens for assessing governance alignment and a practical architecture for enabling these functions to support strategic growth.

About Astrid Yee-Sobraquès, FRM, CISSP

Astrid is a senior risk executive Fortune 100 financial institutions call when complex risk and regulatory challenges bring previous efforts to a standstill.

Over 25 years at GE Capital, AIG, Citibank, and PwC, she’s developed expertise across Enterprise Risk Management, Strategic Advisory, Regulatory Compliance, Digital Transformation, and Cyber Security spanning Banking, Asset Management, and P&C Insurance globally.

As the Risk Sherpa, she’s known for her “risk connectivity” approach—integrating people, processes, and data to strengthen how organizations anticipate, manage, and respond to cascading risks.

She serves on GARP’s New York Chapter Advisory Committee and in October 2025 released the Connected Enterprise framework—the first systematic approach to elevate ERM into the CEO’s strategic intelligence engine.

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The greatest challenge facing boards and corporate management today is not the technology of AI itself, but the human capital transformation required to harness its potential responsibly and purposefully. Harvard Business School’s Karim K. Lakhani summarizes the paradigm shift succinctly: “AI won’t replace humans—but humans with AI will replace humans without AI”. This axiom should guide purposeful leadership in every high-performing company determined to thrive in an AI-driven economy.

Democratizing AI: Leadership as the Differentiator

AI is no longer an exclusive enterprise edge—any company can now access powerful tools and capabilities. The only true differentiator is leadership: the ability of boards and management to foster responsible adoption, develop AI literacy, and set an ethical tone for how technology augments human performance. As the technology continues to democratize, boards must move beyond transactional oversight to transformational leadership, prioritizing ethical growth, adaptability, and bold experimentation.

HR and the Human Firewall: Mitigating AI Risk

With mounting cases of AI-driven workforce disruption, the role of human resources has shifted from administrative support to central risk mitigator. Companies like Moderna have merged IT and HR leadership to foster collaboration and manage risk holistically. HR must now become the “human firewall,” upskilling talent, reinforcing psychological safety, and ensuring high-trust environments. This approach not only reduces AI-related burnout—which could decrease productivity by up to 15% in the coming years—but also increases retention and engagement when AI is deployed strategically.

The Mindset Shift: Transactional to Transformational

Boards and management must champion a mindset shift: moving from transactional control to transformational stewardship. This means fostering cultures where AI is seen as a partner in advancing  a growth mindset alongside an ethical one, amplifying core values and driving adaptation. AI can mimic and amplify both positive and negative values, so a strong, performance-driven culture built on trust and psychological safety is paramount. Shareholders and other stakeholders increasingly demand that corporate values reflect broader societal interests—boards must ensure these values are both real and resilient.

Organizing for the New Nature of Work

The rise of internal talent marketplaces and gig-style project staffing is radically reshaping work. Companies like Standard Chartered Bank are leveraging flexible, project-based models powered by AI to access both internal and external talent as needed. HR and IT leaders must guide this transition, proactively addressing issues of identity, liability, and inclusion for non-human agents and gig workers alike. ​

Responsible AI for Long-Term Success

Pilot projects suggest most “agentic” AI systems fail without human-centric oversight. For boards and management, long-term success depends on purposeful AI stewardship: nurturing healthy cultures, ensuring ethical fluency, and deepening board-level expertise in AI risk and opportunity. Companies need targeted board education, ongoing audits, and a focus on continuous learning—demonstrating that in the AI era, resilience and responsibility begin at the top.

In summary: As AI transforms every aspect of business, purposeful leadership, not raw technology, is the decisive edge. The boardroom’s greatest challenge is not to fear AI, but to harness it collaboratively, setting the stage for humans with AI to redefine high performance and responsible management in the years ahead.

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At the core of this transformation lies purpose. Not as a branding exercise or CSR initiative, but as a strategic imperative. Purpose-driven leadership is no longer a luxury; it’s essential for navigating the complexity, accountability, and opportunity that AI present

Why Corporate Consciousness Matters

Corporate consciousness is an organization’s capacity to act with awareness of its broader impact—on people, society, and the planet—while remaining agile and competitive. In the age of AI, this means understanding not just what technologies can do, but what they should do.

Equally vital is the obligation to generate revenue. Without it, innovation stalls, commitments falter, and the ability to serve customers and communities diminishes. Ethical purpose and financial performance are not opposing forces—they are interdependent drivers of long-term success.

The imperative to use AI to drive innovation and efficiency must be embedded in corporate consciousness. When purpose and performance align, AI becomes a catalyst for inclusive innovation, responsible growth, and sustainable competitive advantage.

Embedding Purpose into Strategy

Strategic decisions must now account for more than market share and operational efficiency. They must consider the ethical implications of data usage, algorithmic transparency, and the societal impact of automation. Boards and C-Suite leaders must ask deeper questions:

• Does our AI strategy reflect our core values?
• Are we designing systems that promote fairness and accountability?
• How do we define success beyond profit?

Embedding purpose into strategy means integrating ethical foresight into every major decision. It’s a shift from reactive compliance to proactive stewardship—grounded in the recognition that revenue generation is a foundational enabler of all strategic goals.

Governance with Integrity

Governance structures must evolve to meet the complexity of AI. Traditional oversight models are often ill-equipped to manage the risks and opportunities posed by intelligent systems. Purpose-driven governance introduces new mechanisms:

• AI Ethics Committees to evaluate emerging technologies
• Cross-functional leadership to ensure diverse perspectives
• Transparent reporting on AI performance and impact

These structures foster accountability and build trust with stakeholders, regulators, and the public—while ensuring that AI investments deliver both ethical outcomes and financial returns.

Culture as a Catalyst

Culture is where purpose lives—or dies. A conscious enterprise nurtures a culture where ethical reflection is encouraged, and innovation is pursued responsibly. This means:

• Empowering employees to voice ethical concerns
• Training teams to understand the societal dimensions of AI
• Celebrating decisions that prioritize long-term value over short-term gain

When culture aligns with purpose and performance, organizations become more resilient, adaptive, and human-centered—even amid technological disruption.

The Role of Leadership

Ultimately, it is the Board and C-Suite who set the tone. Leaders must move beyond technical literacy and embrace ethical fluency. They must be equipped not only to understand AI, but to guide its integration with clarity, courage, and conscience.

This is where strategic advisory becomes essential. By partnering with high-performance companies, the Bonar Institute empowers leadership teams to align around purpose, embed ethical frameworks, and build governance models that support sustainable innovation and competitive advantage.

A Future Worth Leading

AI is not just a technological shift—it’s a leadership challenge. The companies that thrive will be those that lead with purpose, act with consciousness, and build cultures of integrity. The future demands more than intelligence; it demands wisdom—and a recognition that revenue generation is not a distraction from purpose, but a critical enabler of it.

Let’s build it together.

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The stakes could not be clearer. According to a recent MIT study, 95% of AI pilot projects fail to deliver meaningful ROI. That failure rate reflects not only the technical growing pains of a fast-moving field, but also a lack of governance, strategy, and leadership vision. AI experiments fail when they are not connected to the company’s strategic priorities and innovation priorities.

The Danger of Shadow AI

The European Business Review recently highlighted that employees are already integrating AI into their workflows, often without formal IT oversight. Shadow AI mirrors the earlier proliferation of shadow IT. While well-intentioned, it can expose companies to risks ranging from compliance failures to fragmented, unscalable tools. Left unchecked, Shadow AI also tends to reinforce the narrow view of AI as just an efficiency tool, ways to save time, automate email drafts, or summarize meetings.

Efficiency alone doesn’t drive growth. Leadership must establish governance guardrails while also signaling to employees that AI is not only a tool to save minutes but also a lever to rethink markets, services, and customer experiences.

Navigating the Trough of Disillusionment

Gartner’s most recent Hype Cycle for AI places generative AI in the trough of disillusionment. This is the phase where inflated expectations have deflated, and many organizations are confronting the difficulty of operationalizing AI at scale. For boards and senior executives, this moment is pivotal. Companies can either retreat, convinced that ROI is elusive, or they can double down on strategic guidance, recognizing that these technologies tend to deliver their greatest value after the hype has faded, when disciplined leaders steer them toward practical yet transformative use cases.

Efficiency and Innovation: A Dual Mandate

Leaders who succeed with AI balance two mandates:

• Efficiency for Today: Streamlining workflows, improving decision-making speed, and reducing repetitive workload. Early AI applications often shine here, delivering incremental wins that boost morale and free capacity.
• Innovation for Tomorrow: Redesigning business models, creating intelligent customer experiences, and opening new lines of revenue. This requires leadership vision. Employees will rarely stumble into such breakthroughs without structured encouragement and alignment with company strategy.

The difference is cultural and directional. Executives should frame AI as both an efficiency enabler and an innovation engine for market differentiation.

Leadership as the Differentiator

AI is now in everyone’s hands. What distinguishes the organizations that thrive will not be technology access but purposeful leadership. Boards and CEOs should ask themselves:

• Have we set a clear narrative for how AI supports our growth strategy?
• Do we have policies to minimize Shadow AI risks without stifling experimentation?
• Are our pilots tied to measurable business outcomes, or are we chasing hype?
• Are we allocating resources equally toward operational gains and innovation initiatives?

AI is at an inflection point. ROI will not materialize without leadership that frames AI as a catalyst, not just an efficiency and cost-cutting tool.

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Dominique Shelton is the CEO of Global Data Innovation, a legal advisory firm guiding CEOs and Boards to exponential data-driven growth while minimizing risks. With 30 + years in Big Law, she has trained 50,000+ professionals in AI, privacy, and cyber governance. Her insights have benefited companies with a combined market cap of over $3 trillion.

Dominique’s fourth book, Trust: Responsible AI, Innovation, Privacy & Data Leadership won the 2024 getAbstract Business Impact Award. Dominique’s TEDx talk was the fifth highest viewed in 2024, with over 1.6 M+ views. She is the creator of the patent-pending TRUST AI governance framework.

An ADWEEK AI Trailblazer Power 100, a Forbes ‘50 Over 50 Innovator.” a Diligent Modern Governance 100, and an LA Times “Legal Visionary,” Dominique has received 38 awards over her 34 year career. She is the founder of the Digital Trust Summit. She is certified in AI and board governance. Her appearances include Bloomberg TV and CBS News. She sits on the board of directors of Harris & Associates.

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Opening Keynote: “The Rise of the Digital Vanguard”

The opening keynote was titled “The Rise of the Digital Vanguard: Leading in the Age of Innovation.” Moderated by security expert James McQuiggan, the panel featured distinguished voices including Bill Kloster, Wells Larsen, and John Barker himself. The panel explored challenges and opportunities in leadership as organizations grapple with rapid technological transformation, particularly of agentic AI—self-directed AI agents that increasingly shape organizational strategy, workflows, and risk profiles.

John contributed insights as an enterprise governance strategist and legal advisor. He noted the necessity for board and C-suite oversight of agentic AI, warning that ambiguity around definitions and responsibilities creates risk. Few executives fully grasp its implications or requirements for effective governance.

Closing Keynote: “Agentic AI and AI Agents: Governing Cultural, Legal, Regulatory, and Technical Risks”

Barker’s closing keynote urged leaders to engage deeply with the governance of AI agents and agentic AI systems. He articulated highlights and best practices for board and C-suite involvement:

• Definitional Clarity: Organizations must move beyond buzzwords and establish clear, enterprise-wide definitions for agentic AI to ensure consistent governance, risk, and compliance approaches. International standards like ISO/IEC 22989:2022 and frameworks from NIST and OWASP were cited as benchmarks.
• Oversight Structures: Barker advocated for robust human oversight models, distinguishing between “human-in-the-loop,” “human-on-the-loop,” and “human-out-of-the-loop” approaches. For boards and executive teams, this means instituting lines of defense and clear accountability for AI oversight. 
• Risk Mitigation: Barker detailed emerging threat models—memory poisoning, tool misuse, privilege compromise, cascading hallucination attacks, and more. Boards must allocate adequate resources for compliance programs and establish incident response protocols tailored to AI risks.
• Culture and Ethics: Culture creates the “human firewall” for AI adoption. Barker highlighted findings from recent enterprise surveys showing tensions and even active internal resistance to generative AI adoption. Senior leadership must promote healthy, ethical cultures that balance innovation with compliance.
• Legal and Regulatory Vigilance: Agentic AI multiplies exposure to legal and regulatory scrutiny. Boards must anticipate issues stemming from agency law, consumer protection, contract breaches, intellectual property disputes, privacy violations, and product liability. Board education and legal oversight are essential to avoid missteps as legislation like the Colorado AI Act and the EU AI Act come online.

Looking Ahead: Executive Leadership in the AI Era

John Barker’s sessions emphasized that as agentic AI transforms the enterprise landscape, boards and C-suites cannot afford passive engagement. Leadership must proactively address definitional, technical, legal, and cultural challenges—building governance frameworks that adapt to the pace of AI innovation.

For executives and directors, the imperative is clear: embrace continuing education, foster cross-functional collaboration, and institute controls that blend resilience with ethical purpose. 

For more on the Minneapolis Technology Summit 2025, visit the official event page at https://eitevents.com/event_pages/minneapolis-technology-summit-2025/.

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Too often, the conversation around AI is dominated by hype or fear. But what we need, urgently, is practical, values-based guidance for those in leadership.

Boards and executives must understand not just the risks AI presents, but the opportunities, responsibilities and long-term implications of integrating these technologies.

In this session I’ll be joined by James (de Gaspé) Bonar, and John Barker, of the Bonar Institute, where we’ll discuss;

• How to govern AI responsibly
• What ethical AI leadership looks like
• Strategic approaches to these systems in the boardroom

If you’re a board member, executive leader or governance professional, I encourage you to join us.

AI is about to leave the station. Governance needs to get on board!”

Marc Morley

Head of Education and Training Good Governance Academy

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