Beena Ammanath
Contributor
Beena Ammanath is a global and U.S. Technology Trust Ethics Leader at Deloitte AI Institute.
AI is on the minds of nearly every enterprise and startup leader today, challenging human decision-makers with a constant stream of “what if” scenarios for how we will work and live in the future. Generative AI, especially, is redefining what business can do with artificial intelligence — and presenting thorny questions about what business should do.
Managing risks and ensuring effective oversight of AI will need to become a central focus of boards, yet many organizations can struggle when it comes to helping their top leaders become more intelligent about artificial intelligence.
The urgency to educate board members is growing. Over the last decade, the use cases for machine learning and other types of AI have multiplied. So have the risks. For boards, the AI era has exposed new challenges when it comes to governance and risk management. A recent Deloitte survey found that most boards (72%) have at least one committee responsible for risk oversight, and more than 80% have at least one risk management expert. For all the attention and investment in managing other kinds of business risk, AI demands the same treatment.
AI risks abound. AI security risks, for example, can compromise sensitive data. Biased outputs can raise compliance problems. Irresponsible deployment of AI systems can have significant ramifications for the enterprise, consumers and society at large. All of these potential impacts should cause concern for board members — and prompt them to play a greater role in helping their organizations address AI risks.
A growing sense of urgency
Irresponsible deployment of AI systems can have significant ramifications for the enterprise, consumers and society at large. lockquote>
The rise of generative AI makes the AI-risk challenge even more complex and urgent. Its capabilities have stunned users and opened the door to transformative use cases. Generative AI, including large language models (LLMs), image and audio generators and code-writing assistants, is giving more users tools that can boost productivity, generate previously overlooked insights and create opportunities to increase revenue. And almost anyone can use these tools. You do not need to have a PhD in data science to use an LLM-powered chatbot trained on enterprise data. And because the barriers to AI usage are quickly crumbling at the same time AI capabilities are rapidly growing, there’s a tremendous amount of work to be done when it comes to risk management.
Not only does generative AI amplify the risks associated with AI, but it also shortens the timeline for developing strategies that support AI risk mitigation. Today’s risks are real, and they will only grow as generative AI matures and its adoption grows. Boards have no time to spare in getting more savvy about generative AI and how it will influence risk management. The following five steps can help board members prepare their organizations for a future that will be shaped by generative AI.
