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AI Risk Management For Corporate Boards: 5 Areas You Should Be Prioritizing

AI Risk Management For Corporate Boards: 5 Areas You Should Be Prioritizing


(This article is part of a series on Artificial Intelligence for Board Members and Senior Executives.)

In my last article, I detailed the risks that corporate boards must consider in the era of AI (See Top 5 AI Risks In The Era Of ChatGPT and Generative AI ). The rate of growth of these technologies is daunting, and it can certainly feel like there’s nothing that we can do about it.

But of course there is. There always is. And the time to begin is indisputably now.Without further delay, then here are my suggestions for how you can begin to manage and mitigate the risks that your organization faces from the exponential growth of AI.

1. Risk of Disruption

AI has the potential to disrupt industries on an unprecedented scale, making it crucial for board directors to monitor the competitive landscape and adapt accordingly. To manage the risk of disruption:

  • Stay informed, and encourage management (especially the CEO) to stay informed about emerging AI capabilities and their potential impact on the company and your industry. Ask for regular briefings and updates on the most relevant AI developments and keep potential risks and opportunities on the agenda. Subscribe to industry newsletters, attend conferences, and bring in AI experts to keep abreast of the latest developments and their impact on your company.
  • Promote a culture of innovation and agility that starts with the CEO. Ensure that management is fostering experimentation, learning, and adaptation to help the company respond quickly to the rapid changes in the AI landscape. AI initiatives will only succeed with direct support from the top. (See How To Implement And Scale AI In Your Organization)
  • Oversee strategic planning and investments in AI-driven projects. Monitor and evaluate the progress of these AI initiatives and ensure that they align with the organization’s long-term goals and vision. AI shouldn’t be done for the sake of doing AI, it should be done to solve critical business problems or create new opportunities for growth.

2. Cybersecurity Risk

AI exacerbates the challenges of cybersecurity by increasing the sophistication and volume of cyber-attacks. To address this risk:

  • Understand the AI threat landscape. Stay informed about the latest AI-driven cyber threats, such as AI-generated phishing emails, deep fakes, and automated vulnerability exploitation. We are now living in an age where we can’t trust what we read, see or hear because it may have been created by a bad actor using AI. (See The Scary Truth Behind The FBI Warning: Deepfake Fraud Is Here And It’s Serious—We Are Not Prepared For An Attack)
  • Ensure investment in advanced cybersecurity, including continual updates, to stay ahead of evolving threats. Request regular reports on the organization’s cybersecurity posture and AI-driven defense strategies. (See If Microsoft Can Be Hacked, What About Your Company? How AI is Transforming Cybersecurity.) Encourage management to explore and invest in AI-driven security solutions, such as machine learning-based intrusion detection systems, threat intelligence platforms, and automated incident response tools.
  • Request evaluation of vendor relationships with respect to AI security. Organizations often rely on third-party AI systems or services, making it crucial to assess the safety of these external solutions. Ensure that management conducts thorough security assessments of AI vendors and integrates security requirements into vendor contracts.

3. Reputational Risk

The behavior of AI systems can lead to PR disasters if they fail to align with your organization’s values. To mitigate reputational risk:

  • Establish clear guidelines and ethical standards for AI development and deployment. Work with management to ensure that they have a code of ethics for AI that reflects your organization’s values and expectations, and that all AI projects adhere to these standards. (See Google, Facebook And Microsoft Are Working On AI Ethics—Here’s What Your Company Should Be Doing )
  • Request regular audits and assessments of AI systems to ensure the results align with the company’s values. Ask management to conduct third-party audits or internal evaluations to assess the performance, fairness, and transparency of AI systems (although transparency may be a significant challenge).
  • Develop a crisis management plan for the board to address any AI-related incidents that may harm your organization’s reputation. Consider that each evolution of AI within the company is likely to increase the risk of an unforeseen incident. Ensure that there is a clear communication strategy to respond quickly and transparently to any issues that arise, and that the board is kept informed of any incidents.

4. Legal Risk

With regulations surrounding AI evolving rapidly, board directors must stay informed and ensure compliance. To manage legal risk:

  • Track emerging legislation at the federal, state, and international levels by ensuring that corporate counsel or another relevant executive owns this task and reports frequently. Make AI legal risk an agenda item at board meetings to ensure that this is kept up-to-date. (See The EU Is Regulating Your AI. Five Ways To Prepare Now)
  • Have management collaborate with legal experts to ensure that your organization is prepared for upcoming regulatory changes. Encourage management to conduct regular legal assessments to identify potential compliance gaps and develop strategies to address them. Currently, highly-regulated industries are taking action against the use of AI.
  • Foster transparency in AI decision-making processes, whenever possible, to comply with existing and future regulations. “Black box” AI—where no one can tell you how AI arrived at a particular result—will (in many cases) be replaced with interpretable AI by law sooner or later. By ensuring that management develops documentation and reporting processes now, you will avoid complicated entanglements later.

5. Operational Risk

AI systems can lead to operational failures if not properly managed or understood. To address operational risk:

  • Request employee training and education related to AI systems. Ensure that management is providing appropriate training and resources for employees to understand and use AI technologies correctly, or to not use it in certain situations.
  • Ensure robust monitoring and evaluation processes for AI systems. Encourage management to establish clear performance benchmarks and track the performance of AI systems against these goals. Have management present a framework for what type of AI requires what type of human participation. (See AI Can Be Dangerous—How To Reduce Risk When Using AI)
  • Support AI system resilience and redundancy. Advocate for the development and deployment of AI systems that are resilient and have built-in redundancies to minimize the impact of operational failures. Encourage management to consider investing in AI system backups, alternative decision-making processes, or fail-safe mechanisms.

In the face of growing AI adoption, board directors should prioritize AI risk management as a core component of their strategic planning. By taking a proactive approach to addressing the risks of AI, boards can not only safeguard the interests of the company but also seize the opportunities that AI presents to drive innovation, enhance customer experiences, and create a competitive edge.

Ultimately, the key to successfully navigating the risks of AI lies in striking the right balance between embracing its potential and mitigating its risks.

If you care about how AI is determining the winners and losers in business, how you can leverage AI for the benefit of your organization, and how you can manage AI risk, I encourage you to stay tuned. I write (almost) exclusively about how senior executives, board members, and other business leaders can use AI effectively. You can read past articles and be notified of new ones by clicking the “follow” button here.


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