AI is here. You know your organization should be using it.
But what guardrails should you put in place?
How do you empower your team to leverage AI while also mitigating any risks?
This is the realm of AI governance. It’s something every organization should think about as they define their AI strategy. While it may sound intimidating, it gets easier if you engage the right partner (like Corsica Technologies) for AI consulting.
Whether you go that route or use internal resources, here’s everything you need to know about AI governance.
What is AI governance?
AI governance refers to the policies and frameworks that an organization puts in place to ensure that its employees use AI ethically, securely, and effectively. Governance policies often go beyond risk mitigation as well, seeking to maximize the value that a company gets from AI.
Many organizations are just waking up to the fact that they need AI governance policies. The technology is advancing so quickly—and is so widely available—that employees may be using AI tools already, whether their leadership team realizes it or not. Companies need to get control of this area with intelligent AI governance policies.
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As you can imagine, AI governance comes with several challenges. Here’s what you need to know.
What are the challenges of AI governance?
Whether AI adoption is coordinated or happening in an ad hoc fashion, it can have repercussions throughout an organization. Here are several specific challenges that AI governance should address.
Defining a vision for AI
Without a clear vision from leadership, different teams and individual employees may react differently to the introduction of AI. When leadership articulates a vision, it helps everyone to understand what AI means in the context of the organization’s unique operational processes.
Cultural change
AI is such a new technology, it will almost certainly change your organization’s culture. Whenever your culture starts to change, you want to get control of that change and give it the right shape.
This is why AI governance must account for cultural change. You want to let your teams know exactly how the company will be using AI, what’s expected of them, and how AI will impact their jobs. Communicating things like this before, during, and after AI implementation can help provide clarity and craft a culture that has a positive, informed view of AI.
Ethics
AI presents a new way of working. Users can achieve tasks in seconds or minutes that were incredibly difficult or time-consuming before.
Yet with great power comes great responsibility.
It’s important to specify what kind of AI use is acceptable—and what’s not acceptable. You may find that some employees are already using AI to perform tasks while still getting credit for doing the work manually. You may also find that some employees are using AI outputs without checking them for quality or accuracy. There are many ways that people can get into ethical trouble with AI, so a good governance policy should spell out exactly what the organization expects.
Data governance
On the technical side, it’s important to set up your AI tools with the best possible datasets. Unfortunately, few organizations consider this before implementing AI. They may have some files stored locally, some in the cloud, and no cohesive system bringing them all together. AI can only work with the data it has, so the best AI implementations begin with a cohesive approach to data storage.
Of course, permissions and access are a key part of this as well. If file permissions aren’t set up properly, an AI tool may return answers from a document that a user isn’t supposed to access. The good news is that Microsoft Copilot, when implemented on top of proper permissions in Microsoft 365, automatically shows users only the data to which they have access.
Cybersecurity
When it comes to cybersecurity, not all AI tools have your best interests in mind.
Specifically, the public version of ChatGPT is continuously trained on information entered into prompts. If one of your employees types some proprietary data into ChatGPT and asks the bot to interpret it, that proprietary data may leak out in response to a prompt from another user.
This is a serious issue, and your AI governance policies should take it into account.
The good news is that Microsoft Copilot doesn’t share your organization’s proprietary data outside your Microsoft environment. Learn more here (scroll down to #7): Microsoft Copilot vs. ChatGPT.
AI governance frameworks
How should you go about defining and implementing AI governance?
An existing framework is a great place to start. The organization that offers the framework has done the heavy lifting, and you can follow the framework exactly or modify it to fit your needs.
Here are some of the leading AI governance frameworks. Some of these are aimed at organizations that develop AI systems, while others are intended for companies implementing existing AI tools. Wherever your organization lands, it’s worth gaining a directional understanding of current AI governance frameworks as you decide how to proceed.
- NIST AI Risk Management Framework. This approach helps organizations identify the unique risks that AI may pose to their organization.
- OECD AI Principles. This set of guidelines promotes the use of AI that is innovative, trustworthy, and respectful of human rights and democratic values.
- IEEE Ethically Aligned Design. This framework promotes a vision for prioritizing human well-being with autonomous and intelligent systems.
- AIGA Hourglass Model of AI Governance. This framework uses three conceptual layers (environmental, organizational, and systems) to break out the requirements of AI governance into manageable areas.
AI governance tools
It’s a complex undertaking to establish and maintain AI governance. Luckily, it gets easier with the right software. AI governance tools are designed to help organizations implement and manage their AI governance policies efficiently and scale them across the organization.
Here are a few leading tools:
- Credo.ai is all about making AI trust a competitive advantage by operationalizing AI governance at scale.
- Domo integrates AI-powered experiences into its software, making it easier for users to register and manage external AI models securely.
- WitnessAI enables safe and effective adoption of enterprise AI, with security and governance guardrails for both public and private LLMs.
While these tools can smooth the path to better AI governance, someone still has to understand them, use them, and implement your governance policies.
How do you get help with AI governance?
For busy IT teams, AI governance is a large project to tackle. The impact is even more significant if you don’t have internal IT staff.
If you have limited bandwidth and you’re not sure where to start, a consultancy offers a great path forward. Here at Corsica Technologies, we can help you define AI governance policies for your organization. An expert partner brings an outside perspective that you can’t get any other way. You can avoid common pitfalls while adapting internal processes to best practices that will align you with AI capabilities and requirements.
Not ready to talk to a partner? Check out our FREE Generative AI Policy Template. You can use it to start defining AI governance at your organization.
Want to learn more about AI governance?
Reach out to schedule a consultation with our AI specialists.
