The Role of Human Oversight in Mitigating Generative AI Risks

Generative AI is transforming multiple business and technology arenas at an unprecedented rate. However, while there are many business benefits enabled by this low-code/no-code technology, there are also significant risks to business data, operations, and even reputations and revenues. While generative AI technologies can help to mitigate these risks, human oversight is essential to effective risk management and leverage of generative AI.

Generative AI: Big Promise, Big Risk

Generative AI combines artificial intelligence, machine learning, and big data to “train” software systems, enabling them to generate conversational, plain-language answers to queries of all kinds. Its current abilities have already motivated people and companies to implement generative AI deployments at a breathtaking pace. And leading enterprise technology vendors such as AWS, Google, and Microsoft are in various stages of delivering offerings and enhancements powered by generative AI. 

Enterprises across multiple industries are also implementing, experimenting with, or considering adding generative AI to their business software and services portfolios. For example, MediaPost recently reported the results of a survey of 1,000 marketing professionals conducted in March 2023 by chatbot vendor That survey found that two-thirds of respondents’ companies use generative AI for brainstorming. Moreover, 73 percent of those companies already use generative AI tools to generate marketing content from email and website copy to online images and sales collateral. Some 66 percent of survey respondents report a positive return on investment (ROI), while 58 percent claimed increased performance of their marketing efforts thanks to generative AI.

The Critical Role of Human Oversight

Generative AI is already delivering on the promises of deeper, more satisfying engagement for users, new revenue streams, advertisers, and marketers, and greater agility and productivity for enterprises. However, these early generative AI deployments are not without significant risks. Three of the top challenges cited by respondents to the survey were privacy and security concerns (45 percent), data scarcity (31 percent), and poor content quality (29 percent). 

These three concerns share a common characteristic. They cannot be addressed effectively by technology alone. Protection of privacy and security and the quantity and quality of the data that drives generative AI, requires human oversight. Experienced people must ensure that data security and privacy policies are effective, consistently enforced, and updated as technologies and threats evolve. And humans must select and curate the data used to inform generative AI deployments at their enterprises, to maximize the accuracy and business value of those deployments. This is why some three-quarters of survey respondents choose to train their generative AI implementations on proprietary, internal data pools instead of relying on publicly available data alone.

What You Should Do Now

Clean your pool(s). Before your enterprise can rely on its data stores to train and inform generative AI deployments, those data stores must be vetted thoroughly. If you cannot be certain that your data is accurate, comprehensive, consistent, secure, and up to date, your enterprise risks being hobbled by generative AI instead of aided by it. As has been proven true since the earliest days of modern computing, “garbage in, garbage out.” 

Trust, but verify. Your chosen generative AI solutions will likely include some that rely on data from sources outside your enterprise. This means you must know all you can about those sources and the quality of the data they supply. Everything your enterprise has learned about understanding and managing data lineage must be brought to bear on every external data source. This is essential to ensure the best training and results from your generative AI deployments.

Empower your people. Implement technologies and processes that foster and support the interdisciplinary collaborations necessary to manage the risks associated with generative AI and other low-code/no-code deployments. Ensure your users are trained and encouraged to practice good data hygiene consistently. And keep your IT estate and management processes updated to maximize the quality and security of your enterprise’s critical data in the face of continuing, explosive change. 

How Incisive Can Help

Incisive Software is focused on helping organizations build a strong foundation for success based on accurate and trustworthy data, especially in the face of new and growing risks spawned by generative AI and other low-code/no-code technologies. Incisive offers Incisive Analytics Essentials, a solution that enables you to gain managerial control over generative AI and other low-code/no-code deployments while making them available to authorized users. The Concourse platform, the heart of the Incisive solution, provides consolidated, comprehensive abilities to know what you have and what changes and effectively manage, protect, and trust your business-critical data across your entire enterprise.
To learn more about Incisive Analytics Essentials or to arrange a demo or free trial, visit, email [email protected], or call 408-660-3090.


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