What are the main strategic AI risks for boards?

The main strategic AI risks are disintermediation, data-driven customer lock-in by competitors, exclusion from new ecosystems, loss of visibility in LLM-based discovery, and an outdated talent model. Boards must consider these alongside cybersecurity, privacy, intellectual property, bias, explainability, availability, and third-party risk.

How should a board evaluate an AI opportunity?

A board should start with customer compromises and competitive dynamics. It should ask what unmet customer need AI could solve, what data must be collected and connected, how quickly the company can test and learn, how Porter’s Five Forces may change, and what financial, privacy, security, operational, and reputational downside each use case introduces.

How can companies use customer data without becoming creepy?

Companies should obtain explicit permission, favor first-party and voluntarily supplied zero-party data, explain the value exchange, and use information to improve service rather than bombard customers with covertly targeted promotions. Dave recommends testing experiences with employees and asking a simple question: what will customers think when they realize how their information was used?

How is AI changing cybersecurity attacks?

AI makes cyberattacks faster, more automated, and more convincing. It can accelerate reconnaissance, identify vulnerable people and suppliers, generate realistic social-engineering messages, bypass defenses, and extract data efficiently. Chris says some attacks that previously required weeks or months of preparation can now be executed within days.

What cybersecurity information should boards receive?

Boards should receive business-aligned reporting that quantifies likely financial and operational losses, not only technical activity. Reporting should cover interruption costs, recovery, ransomware, data breaches, misappropriation of funds, intellectual property theft, legal and regulatory exposure, insurance coverage, supplier dependencies, and progress against material risk-reduction priorities.

Should cybersecurity slow AI adoption?

Cybersecurity should shape AI adoption, not stop it. Dave’s closing principle is, “Proceed with caution, but proceed.” Companies that delay strategic experimentation may face material competitive risk, while companies that deploy without permissions, controls, monitoring, recovery plans, and accountable governance may create equally material operational and legal exposure.

How Boards Can Govern AI Risk

Board directors and executives get a practical framework for pursuing AI-driven growth while managing strategic, cybersecurity, privacy, and operational risks.