It's 2024, and your company has fully embraced generative AI and artificial intelligence (AI). You and your team have been actively leveraging AI and machine learning (ML) projects across various projects, and the results are impressive. Innovation, speed, and efficiency are on the rise!
With the increase in the adoption of AI technologies, now is the perfect time for organizations to establish an AI Registry to keep track of all the AI and ML use cases deployed by your different teams and mitigate any potential risks.
In this blog post, we will help you understand and identify AI/ML use cases, including high-risk AI use cases, and explain why your organization should kick off the year by establishing an AI Registry. Without further ado, let's start!
What are AI/ML Use Cases?
The term "use case" is as straightforward as it sounds – it's the specific application or project where AI/ML technologies are put to work. Think of use cases as real-world scenarios where AI/ML solutions are deployed to solve particular problems or enhance existing processes.
Let's break it down with a few examples:
- ChatGPT for Content Creation: Marketing teams are currently using Generative AI, specifically ChatGPT, to generate blog posts, articles, product descriptions, and social media captions.
- Virtual Assistants: Companies are creating AI chatbots or virtual assistants to provide basic information, answer frequently asked questions, or perform simple tasks like setting reminders or sending messages.
- Document Management & Search: Many organizations are exploring applications of large language models to manage internal documentation and make it more searchable for employees.
Again, as you can see from the examples, these are not theoretical; they're the practical manifestations of AI and ML in the actions of a specific organization.
Depending on an organization’s AI maturity—the extent to which AI is powering their business and operations—they may have only a few AI use cases or hundreds or even thousands of different AI use cases. While every single AI use case in development or deployment requires governance, the level of governance and oversight required depends on the use case risk level—what level of risk the use case poses to the organization.
High-Risk Use Cases: A Closer Look
High-risk AI use cases tend to fall into at least one of the below categories:
- An AI use case whose outcomes have a significant impact on people’s lives, livelihoods, and access to essential services—for example, a credit risk prediction system that determines whether someone gets access to a loan or not;
- An AI use case whose outcomes have a significant impact on or pose a significant risk to the business—for example, a customer-facing support chatbot that is the frontline “voice” of the brand;
Use cases that fall into the first category tend to require significant regulatory and legal oversight, and use cases that fall into the second category tend to require significant business oversight and risk management.
For a comprehensive understanding of high-risk use cases that fall into the first category, check out our blog post "Understanding High-Risk AI: Responsible AI for HR, Healthcare, Finance, and Insurance."
While different organizations are going to have different levels of risk tolerance—and therefore different definitions of what kinds of use cases fall into the second category listed above—all organizations need to ensure that they have a plan in place to identify and triage high-risk use cases to minimize the overall risk of AI to the business.
So, where does an AI Registry come into play?
AI Registry - Your First Step for Responsible AI
An AI Registry is a centralized database or ledger that allows organizations to gain comprehensive oversight of all AI initiatives undertaken within the company. By maintaining an AI registry, companies can track and manage AI projects effectively, identify project ownership, and ascertain the individuals responsible for reporting on their outcomes, be they success or failure.
This systematic approach helps enhance transparency, accountability, and visibility, making it easier for businesses to navigate the rapidly expanding AI landscape with confidence and compliance. And, with the latent need in the market for increased centralization and explainability, the AI Registry is incredibly and increasingly important.
Here are four reasons why your organization should consider starting an AI Registry today.
1. Get visibility into where and how your organization is using AI.
To govern your organization's AI systems effectively, you first need to have a clear understanding of where and how AI is being used across various teams and business units. This includes not only the AI systems developed internally but also any third-party AI tools that your organization is using.
Creating an AI registry can help you gain complete visibility into your company's AI landscape and develop a robust governance strategy that fits your organization's unique needs.
2. Identify High-Risk Use Cases that need immediate triaging.
Your AI Registry is an essential tool that can help you identify whether your AI use cases pose a low or high risk to your organization. In case of high risk, the registry can help you identify the critical factors that make a use case "high risk." This will enable you to ensure that the use case receives appropriate oversight from the start of the development or deployment process. These critical factors are essential to meet regulatory requirements and mitigate the risks associated with high-risk use cases.
3. Ease your stakeholders into new AI governance processes with the easy first step of “intake.”
If your organization is new to AI governance, introducing new processes to manage the risk and compliance of your AI systems can be tricky; you don’t want to introduce governance workflows that are overly burdensome or heavy unless absolutely necessary, especially for stakeholders whose primary goals are related to AI adoption and deployment.
Establishing your AI Registry and a standardized process for “intake” of new AI use cases is a great way to introduce AI governance to technical and business stakeholders who might otherwise be skeptical of governance.
Intake can be a low effort for these stakeholders, and it allows you to ensure that low-risk use cases can quickly be identified and pushed through a lightweight governance process while high-risk use cases are pulled aside and given the proper levels of oversight.
4. Meet "AI inventory" requirements from laws and regulations.
Laws, regulations, and standards increasingly require organizations to maintain an "AI inventory" or "AI catalog"—including the EU AI Act, the OMB Guidance, and a recent Executive Order in the United States. An AI Registry will quickly get you in compliance with these new requirements and ensure you future-proof your business for future regulations and standards.
Establish your AI Registry Today with Credo AI
As we enter 2024, establishing an AI Registry is imperative for organizations embracing AI and ML technologies. This centralized database offers transparency, accountability, and regulatory compliance. Embracing responsible AI governance through an AI Registry ensures your organization's readiness for the AI-driven future, fostering innovation with responsibility.
Kickstart your AI Registry now by scheduling a call with our dedicated team. We look forward to supporting you in your journey through AI governance!
DISCLAIMER. The information we provide here is for informational purposes only and is not intended in any way to represent legal advice or a legal opinion that you can rely on. It is your sole responsibility to consult an attorney to resolve any legal issues related to this information.