The deadlines are piling up. The pressure to adopt AI solutions is mounting. Your executives want to know how to react to all the AI hype. It feels like the right decision to quickly adopt AI solutions in the market even if you don’t have time to review and assess risks or set up an AI governance. Spoiler alert – It’s not. The foundation for effectively using AI to grow your business is to ensure you set up both AI strategy and AI governance to minimize AI risks.

Technology makes it easy to add AI debt

Each time you decide to leverage off-the-shelf AI solutions without a holistic review, you add risk to your business, known as AI debt.  This refers to potential cumulative risks and challenges a company may face when adopting AI solutions without adequate AI risk assessment or a governance framework.  

OpenAI recently announced the GPTs Store, which gives all companies, regardless of size and budget, the ability to quickly create custom versions of GPT, adding to your AI debt is now even easier. Besides, when startups and tech providers use these AI tools in their solutions and release them automatically in their next update, you’ll have a fleet of AI-powered solutions without even noticing it.

Minimizing risk through AI governance

While using these tools to gain productivity and efficiency may seem like the right decision at the time, ignoring the risks related to data privacy, biases, and security with using AI leads to significant problems in the future. Going back and making changes will be time-consuming and costly down the road. Additionally, every time you use AI without proper AI governance, the problem and affected data grow both in terms of size and risk.

“Our customers tell us that they are concerned about protecting their intellectual property and their data privacy. They ask us how they can make sure their data won’t be available to others. Many are especially worried about their customers’ data,” says Sam Zolfagharian of YegaTech. “That’s where AI governance comes in. We need to make sure that we keep the balance between leveraging AI technologies, but in the meantime, think about what we need to do to minimize its risk.”

Establishing the right AI governance

By addressing AI governance issues while setting up your AI strategy or adopting AI solutions, you can avoid the AI debt challenge. However, because of high expectations from executives or clients, organizations are trying to digest what it means and how to use it at the same time as they deploy or adopt it. Many teams mistakenly assume that their existing data governance policies cover AI governance.

“Most organizations already have data governance and security in place,” says Zolfagharian. “But AI governance is separate. Also, AI governance is not just for users but also for AI providers. While we can put data governance partially under the umbrella of AI governance, it doesn’t mean you are safe from having any AI risk in your platform with only data governance.”

The right AI governance is unique to each organization

One of the biggest challenges in establishing AI governance is that “one size doesn’t fit all.” Organizations often look for a common framework that addresses the needs of all companies in their industry. However, this simply isn’t possible. If a framework works for a company similar to yours, it does not mean it could also work for your company. Like data governance, AI governance varies based on location – European regulations differ from U.S. laws. Even in the US, California’s regulations differ from Georgia’s (CCPA vs. GCDPA.) Additionally, AI solutions differ based on industry and specific company needs. While the AI model and related AI and data governance use the same core principles, the specifics must be tailored to the company’s unique needs.   

Therefore, when creating the initial AI governance, consider governmental requirements based on location. Because many data privacy rules and policies are based on the customer’s location, you must meet the regulations for all locations of any customer. Additionally, look at industry-specific regulations. Next, look at your specific company and customer needs, then add in extra measures as needed.

Addressing AI governance is a continuous effort

Organizations often think AI governance is a one-time “check-off-the-box” type of task. Because AI technology is still evolving and regulations are constantly changing, AI governance is an ongoing process, especially with AI in the relatively early days of wide-scale implementation. Therefore, if you only address AI governance at one time, you will likely not meet the legal requirements in the near future. Additionally, this approach gives you a false sense of security.

Instead, organizations should include AI governance throughout the entire life cycle of development_ if they’re developing any in-house AI solution_ and whenever their solution providers develop new or update their existing AI solutions_ if they’re using off-the-shelf AI solutions. At each juncture, your team should address AI governance, look at regulations, and adjust as needed.