TechCrunch shares 5 steps board members and startup leaders can take to prepare for a future shaped by GenAI

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AI is on The minds of nearly every enterprise and startup leader today challenge human decision makers with a constant stream of “what ifs” about how we will work and live in the future. Productive AI, in particular, is redefining what business can do with artificial intelligence — and posing vexing questions about what business is. should be do

Managing risks and ensuring effective oversight of AI should become a central focus of boards, yet many organizations struggle to help provide their top leaders with more intelligence about artificial intelligence.

There is a growing need to educate board members. Over the past decade, the use cases for machine learning and other forms of AI have doubled. So there are risks. For boards, the AI ​​era has revealed new challenges when it comes to governance and risk management. A recent Deloitte survey found that most boards (72%) have at least one committee for risk oversight and more than 80% have at least one risk management expert. For all the attention and investment in managing other types of business risk, AI demands the same treatment.

AI risks abound. AI security risks, for example, compromise sensitive data. Biased outputs raise compliance issues. Irresponsible deployment of AI systems can have significant changes for the organization, consumers and society. All of these potential impacts are worrying for board members — and prompting them to play a greater role in helping their organizations address AI risks.

A growing need

Irresponsible deployment of AI systems can have significant changes for the organization, consumers and society.

The rise of generative AI makes the AI-risk challenge more complex and urgent. Its capabilities have wowed 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 increase productivity, generate previously overlooked insights, and generate revenue-enhancing opportunities. And almost anyone can use these tools. You don't need to have a PhD in data science to use an LLM-based chatbot trained on enterprise data. And as barriers to AI use are collapsing quickly at the same time AI capabilities are growing rapidly, there is tremendous work to be done when it comes to risk management.

Generative AI not only extends the risks associated with AI, but also shortens the timeline for developing strategies to support AI risk mitigation. Today's risks are real and will only grow as productive AI matures and its adoption increases. Boards don't have time to become more knowledgeable about productive AI and how it impacts risk management. The following five steps can help board members prepare their organizations for a future shaped by productive AI.



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