AI readiness: How to mitigate risk with AI governance
AI governance promotes responsible AI use without hindering innovation. Learn how to enhance your governance strategies for secure AI adoption.
Feb 24, 2025 • 5 Minute Read
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AI has nearly limitless potential. But with great power comes great responsibility. If you want to make the most of AI technology—without it backfiring in the process—you need AI governance.
Governance is a critical component of any AI strategy and one of the five key pillars of AI readiness:
- Data
- Governance
- Investment
- Skills
- Strategy
In this article, we dive into the Governance pillar and share insights from our original research with 600 tech executives and leaders across industries. Here’s what we learned about AI governance and how organizations can adopt AI while minimizing risk.
AI governance: Balancing innovation and responsibility
Successful AI governance provides a framework for responsible, ethical AI adoption. It includes processes and policies that mitigate risk, build trust, and ensure compliance over time when using or building AI.
Organizations with well-developed AI infrastructure governance have:
- Organization-wide policies for AI use and development
- Tools and processes to monitor and mitigate AI risks, such as drift, bias, data privacy, and legal liabilities
- Guidelines to ensure compliance with AI legislation and regulations
- Channels to discuss ethical concerns or questions about AI
The good news? More than half of tech leaders understand the need for governance. 64% of leaders say their organization has the infrastructure to comply with and adjust to potential regulatory changes on AI going forward.
Scaling AI with confidence: The role of governance in AI success
Organizations need AI governance for the same reason they need cybersecurity protocols: To mitigate risk and protect their customers and business.
Improper AI use can damage brand reputation, lead to customer data breaches, and even result in physical harm to humans. Governance aims to reduce these risks without impeding innovation.
In fact, its restrictions can spur experimentation and new breakthroughs. Consider the DeepSeek AI model that made waves. Due to AI chip embargo restrictions, the DeepSeek developers had to train their models with less powerful GPUs. These constraints forced them to come up with creative workarounds, ultimately empowering them to build a competitive AI model at a cheaper price point than companies like OpenAI.
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How to build an AI governance framework for ethical and responsible use
There’s a lot to keep track of when it comes to AI governance, especially when the AI landscape is constantly changing. Here are key ways to upgrade your governance strategies, minimize risk, and keep up with ever-evolving best practices.
Develop a centralized policy for AI use and development
The majority of organizations (79%) have a centralized AI-usage policy or set of guidelines for AI use and development.
A consistent, centralized framework of best practices is the basis of AI governance and gives employees guidance on how, when, where, and why they can use AI.
Even if you can’t roll out AI across your organization or develop a comprehensive policy right now, a basic usage policy is better than nothing. In most cases, employees are already experimenting with AI on their own. Rather than risk shadow IT, provide employees with clear guardrails to prevent any major mishaps.
This is especially crucial for government agencies and public sector organizations. With Biden’s AI executive order rolled back and no clear AI guidance from the Federal government, they’ll need to develop their own policies to continue with their AI projects.
Mitigate risk with data governance for AI
Beyond usage guidelines, establish dedicated policies to address specific AI risks like:
- Bias and discrimination
- Copyright infringement and plagiarism
- Data privacy
- Lack of transparency and accountability
- Misinformation
As time goes on, AI models drift, cybersecurity threats evolve, and business goals change. Your policies should reflect these shifts and ensure responsible AI use over time. Revisit your policies every six months to make sure they’re still meeting your needs.
Set aside dedicated resources for AI cybersecurity risk management
Only 29% of organizations have dedicated resources to manage AI risks. 40% respond on a case-by-case basis, and a third have few to no resources to respond to AI risks.
Even with formal policies, you can’t completely eliminate AI risks. Set up dedicated resources to respond to potential AI threats before they happen so you aren’t left scrambling in a high-stress situation.
Create employee feedback channels and monitoring for AI ethics
Comprehensive governance consists of a lot of moving parts. Set up automated dashboards to monitor your organization’s AI systems, flag potential risks, and ensure compliance with your policies, ethical best practices, and laws.
It’s also important to set up feedback channels for employees to share concerns or ask questions about ethical AI use. 94% of organizations have feedback channels to respond to criticisms or questions related to AI ethics.
But not all of them are able to respond to employee concerns. 48% of organizations have dedicated feedback mechanisms for AI ethics concerns but can’t always respond to employee comments. If this sounds like your organization, you need dedicated teams to manage these channels.
If you don’t take internal feedback seriously, you could run into larger ethical concerns later. Monitor these channels and respond to feedback to stay on top of potential risks and show employees you take their concerns seriously.
Build your workforce’s AI ethics skills
Despite the explosion of AI, only 1.8% of people learning how to use AI have actively searched how to adopt it responsibly.
When it comes to AI governance, organizations don’t just need policies—they need to ensure their people follow them. That process starts with raising awareness about why governance is important and how irresponsible AI use can affect the entire organization.
Check out these courses to get them started:
Check out these additional resources to enhance your AI readiness
Governance may not be the flashy part of AI adoption, but it’s ultimately what allows organizations to keep using AI without negative impacts.
Learn more about the components of AI Readiness and how to take your organization to the next level:
- How to enhance your AI strategy development
- How to bridge the AI skills gap with upskilling for AI
- How to improve your data management strategy for AI
- How to create an AI investment strategy to maximize ROI
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