What Boards Must Know About AI Now

AI is a Board-Level Priority

AI is no longer merely a technical tool under the sole domain of the CIO. It is now a fundamental driver of business strategy and governance that requires board oversight. Corporate directors are increasingly recognizing that the fiduciary duty of care and loyalty now includes a responsibility to understand and oversee the organization's use of AI. Boards that fail to grasp the strategic implications of AI, from enhancing operational efficiency and customer experience to creating entirely new business models, risk falling behind competitors. Boards must balance these strategic implications with a proactive approach to managing new and complex risks. The discussion has gone from "should we use AI?" to "how will we govern AI responsibly to create value and mitigate risk?"

This elevated focus is driven by the fact that AI can amplify existing corporate risks in areas like data privacy, cybersecurity, and regulatory compliance. Algorithmic bias, for instance, can lead to discriminatory outcomes that expose a company to legal and reputational harm. Consequently, boards must ensure that robust AI governance frameworks are in place. This includes scrutinizing management’s AI strategy, implementing controls for transparency and accountability, and assessing the board’s own AI literacy. In a world where AI-powered decisions are made at lightning speed, directors cannot afford to be passive observers. Directors must be educated on the ethical, legal, and operational implications of AI. 

Opportunities AI Presents for Boards

Enhanced Decision Making 

AI can process and analyze vast amounts of data far faster than humans. Boards can use this to access deeper, more nuanced insights for making strategic decisions. This goes beyond merely analyzing current data. By simulating various future scenarios and testing assumptions against real-world data, AI can aid the board in developing more resilient long-term strategies.

Streamlined Board Operations 

AI can improve the efficiency of the board itself. AI can automatically generate summaries of complex board materials, draft meeting minutes, and help with scheduling. This allows directors more time to focus on high-level discussion and strategic oversight.

Proactive Risk Management 

By using machine learning to detect anomalies and patterns in real-time, AI can spot potential risks like fraud, cybersecurity threats, or supply chain vulnerabilities before they escalate. This is a powerful tool for boards to manage and mitigate risks more effectively. 

Increased Transparency and Accountability  

With AI, it's easier to see exactly how decisions are made. AI tools can record every step, so boards have a clear audit trail of their actions. This makes the board more accountable and helps the company meet all its legal and reporting requirements.

Tailored Director Education 

The pace of technological change means that directors need to continuously learn. AI-powered educational platforms can create personalized learning pathways for board members based on their existing expertise and the company's specific needs. 

Managing AI Risks

Algorithmic Bias and Fairness 

AI systems learn from data. If the data used for training reflects societal biases, historical discrimination, or incomplete information, the AI will perpetuate and even amplify those biases in its decisions.

Therefore, boards must ensure that safeguards are in place to monitor and mitigate the risk of bias and ensure fairness. AI models whose decision-making processes are transparent and auditable should be prioritized. Boards can utilize specialized software to test AI models for discriminatory patterns. For critical decisions boards should mandate human review.  

Data Privacy and Security

AI systems often require access to vast amounts of data, much of which can be sensitive or personally identifiable. This makes them prime targets for data breaches and cyberattacks. Furthermore, AI models themselves can inadvertently "leak" sensitive information about their training data. 

To mitigate security risks, advanced encryption, access controls, and regular security audits should be implemented. To ensure data privacy only the data necessary for the AI's intended purpose should be collected and stored, and whenever possible identifying information from data should be stripped. These security and privacy practices should be integrated throughout the AI development lifecycle, from design to deployment. 

Regulatory and Legal Compliance 

The regulatory landscape for AI in the U.S. is rapidly evolving. While a comprehensive federal law is pending, various state laws, industry-specific regulations (e.g., in finance or healthcare), and executive orders are creating a complex web of compliance requirements. Non-compliance can lead to hefty fines and legal action. 

In order to mitigate risks relating to compliance it is recommended to work closely with legal experts specializing in AI law and data privacy, and to conduct regular audits to ensure AI systems and processes comply with all relevant laws and standards.

Performance, Reliability, and Safety

AI models, especially in real-world environments, can be unpredictable. They might make errors, or encounter edge cases they weren't trained for. In critical applications (e.g., autonomous vehicles, medical diagnostics), failures can have catastrophic consequences.

It is therefore important to rigorously test AI models in diverse scenarios. Further, AI systems should be continuously monitored and clear protocols for updates and retraining should be established. In an instance where testing and monitoring fail there should be ability for human oversight and "off switches" or fallback procedures.

Governing AI for Value and Risk

The immense opportunities of AI are matched only by its potential for reputational and legal harm. The primary role of the board is to ensure responsible governance. This can only be accomplished by moving AI from an IT discussion to a full board-level risk and strategy committee agenda item.  Begin by tasking management with a comprehensive inventory of all current AI applications and their associated risks and benefits. Simultaneously, dedicate time to a focused board education session on AI fundamentals. Finally, initiate a review of your corporate governance framework to explicitly account for AI oversight. By fostering AI literacy and aligning AI initiatives with core business objectives, your board can transition from passive observers to essential guides on the journey toward a responsible and prosperous AI-powered future.