AI’s speedy evolution and daily use cases are arriving at an accelerated pace. Leaders must acknowledge the risks and uncertainty of AI use in their organization as it is used to drive potential business value.


Copyright: – “4 ways CISOs can manage AI use in the enterprise”


Over the summer, I wrote a column about how CIOs are worried about the informal rise of generative AI in the enterprise. That column may have been the understatement of the year.

Since then, many CIOs I’ve spoken with have grappled with enterprise data security and privacy issues around AI usage in their companies. A primary fear is that employees, partners, and organizational stakeholders might share everything from private data to source code into public large language models (LLMs), expose proprietary information and intellectual property, or reveal vulnerabilities to exploit. Other fears cover compliance with emerging AI regulations and the risk of models becoming contaminated or biased through adversarial attacks.

One Fortune 500 executive recently told me that they were worried that one organization could use a public LLM to learn what its competitors were asking that same LLM. For example, one pharmaceutical company using ChatGPT4 or similar for corporate espionage could essentially spy on its competitor’s research queries. A public LLM aggregates the data of the prompt itself and which user initiated that prompt. So, by asking about a certain company’s research, that data can become part of the public record.

But with time, CIOs are starting to figure out ways to manage the use of generative AI within the enterprise. A recent CIO column suggested that the biggest worry for CIOs should not be the fear of AI growth but rather figuring out the best way to gradually incorporate generative AI into the enterprise, either as an add-on model or a foundational piece of the architecture. While it is a given that AI will help organizations drive competitive advantage, the roll-out of this quickly evolving technology must be done safely.

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Let’s dig a little deeper into how CIOs can succeed at helping manage the safe use of generative AI within their organizations.

Protecting data

In a recent meeting I attended with over 100 security executives, the prevailing theme among participants was that the primary techniques used today to manage the safe use of AI in their organization were employee training and usage policies. Most of these executives are primarily concerned with all of the bad things that can happen, as one might expect, not the advantages that AI can provide. A few even suggested that they have considered policies to prevent the use of public LLMs.[…]

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