Generative Artificial Intelligence (Gen AI) is a transformative force that promises unprecedented opportunities for businesses. As board members and non-executive directors, understanding and preparing for generative AI is crucial. In this blog, we explore key considerations and actions that boards should take to navigate this emerging landscape.
1. Understanding Generative AI
Generative AI models, powered by deep learning and trained on vast unstructured data sets, have the potential to revolutionise industries. Unlike traditional AI models, generative AI can perform multiple functions—classifying, editing, summarizing, answering questions, and even drafting new content. As a board, your first step is to grasp how generative AI will impact your industry and company in both the short and long term1. Early applications are likely to emerge in software engineering, marketing, sales, customer service, and product development. Even if your industry doesn’t directly rely on these functions, assessing the value at stake is essential.
2. Risk and Opportunity Assessment
Generative AI introduces both risks and rewards. Boards must evaluate the potential benefits against the associated risks. Key questions to consider:
- Financial and Operational Risks
How might generative AI impact our financials and operations? What investments are required, and what are the potential returns? - Ethical and Legal Considerations
How can we ensure that our AI systems align with ethical and legal standards? What safeguards are in place to prevent unintended consequences? - Talent and Technology
Do we have the right talent to harness generative AI? How can we stay ahead of the technology curve?
3. Building a Trusted AI Framework
Our approach prioritises the incorporation of Trusted AI, laying out a strategic framework for the ethical and responsible design, development, deployment, and application of AI solutions. Here are the guiding principles:
- Ethical Alignment
Ensure that AI applications align with ethical and legal standards. This protects the organization from financial, operational, and reputational risks. - Innovative Enablement
Foster innovation by leveraging trustworthy AI. It gives your business a competitive edge. - Stakeholder Trust
Commit to Trusted AI to enhance trust among stakeholders, customers, and employees.
4. Data Governance and Privacy
Generative AI relies heavily on data. Boards should address the following:
- Data Quality
Ensure that the data used for training generative AI models is accurate, diverse, and representative. Poor-quality data can lead to biased or unreliable outcomes. - Privacy Compliance
Understand privacy regulations (such as GDPR or CCPA) and ensure that generative AI processes comply with them. Protecting user privacy is paramount.
5. Human-AI Collaboration
Generative AI isn’t about replacing humans; it’s about augmenting their capabilities. Boards should explore:
- Human-AI Synergy
Encourage collaboration between employees and AI systems. Define clear roles and responsibilities. - Change Management
Prepare employees for the shift. Upskill and reskill teams to work effectively alongside AI.
6. Scenario Planning
Anticipate different scenarios related to generative AI adoption:
- Upside Scenarios
Imagine the positive impact of successful generative AI implementation. How can it enhance customer experiences, streamline processes, or drive innovation? - Downside Scenarios
Consider risks—such as unintended biases, security breaches, or misuse of generative AI. Develop contingency plans.
7. Board Diversity and AI Literacy
Diverse boards bring varied perspectives. Ensure that board members understand AI concepts:
- AI Education
Regularly educate board members on AI developments, terminology, and trends. - Inclusion
Include AI experts or advisors on the board to provide specialized insights.
8. Monitoring and Accountability
Generative AI evolves over time. Boards should establish mechanisms for ongoing monitoring and accountability:
- Performance Metrics
Define KPIs to measure the effectiveness of generative AI solutions. - Ethics Audits
Regularly assess AI systems for ethical alignment and transparency.
9. Collaboration with Stakeholders
Engage with stakeholders beyond the boardroom:
- Industry Partners
Collaborate with industry peers to share best practices and learn from each other. - Regulators and Policymakers
Participate in shaping AI regulations and policies.
Conclusion
Generative AI is both exciting and complex. By proactively embracing Trusted AI principles and engaging with the technology, boards can lead responsible innovation. Let’s pave the way for AI that serves the greater good while safeguarding our organisations and stakeholders 2.
Remember, the journey toward generative AI readiness begins today!
