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Best Practices for AI Compliance and Security
Creating new forms of artificial intelligence may be a great leap forward, but controlling them can be a stumbling block for businesses and government agencies alike.
As businesses deploy AI more rapidly and consistently, governments have done what they can to keep a handle on it. The EU AI Act generated headlines and increased interest in regulations surrounding this new technology, but it is not the only legislation that proposes a framework for AI governance. The U.S.’s First AI Executive Order seeks to do the same — and in the U.S. alone, 45 states have introduced AI-related bills.
AI governance has evolved, and the world is constantly finding new ways to leverage its accelerated timeline.
Meanwhile, businesses are working to navigate AI responsibly, driven by legal compliance and concerns over potential misuse. Mismanaged AI could jeopardize critical systems and erode customer trust, underscoring the need for thoughtful implementation and oversight.
They are wise to worry. However, the most forward-thinking companies embrace AI with complete confidence because they have created governance programs that serve as guardrails for this incredible new technology. Effective governance ensures AI consistently aligns with an organization’s best interests, safeguarding against potential risks while unlocking its full potential.
The Governance Basics
AI governance should be dynamic and scale alongside AI deployment. Organizations must budget for continuous monitoring, invest in ongoing training, and evolve their governance frameworks to address new risks.Staying ahead of threats requires a flexible, proactive approach, mitigating risks in a constantly shifting landscape.
For this reason, transparency in AI isn’t just a box to check off — it’s a business imperative. AI models must justify their decisions clearly, especially in mission-critical use cases. This ensures trust with stakeholders and safeguards against unintentional biases.
In the years ahead, we can expect a heightened focus on business resilience, transparency, and sustainability, all driven by AI and related technologies. As organizations adopt and roll out AI more widely, governance frameworks will be expected to evolve and prioritize ethical use, regulatory compliance, and risk mitigation.
Continuous investment in these areas will define success as AI continues scaling into new uses.
From a governance standpoint, risk management is increasingly intertwined with corporate AI strategies, especially in highly regulated industries like finance, healthcare, and the law. Advanced risk assessment tools will be critical in navigating this landscape, as they will ensure AI systems don’t just work but are ethically sound.
The key to getting it right will be to adopt governance strategies that blend rapid innovation with rigorous oversight, keeping the organization in front of regulatory requirements while maintaining airtight trust and accountability.
A Roadmap for Governance
Companies must adopt their self-governance programs to use AI safely — or pay the price. And there is no company that will remain untouched by this disruptive new technology.
Whether it integrates AI into its tech stack or not, every business is at risk of AI misuse. For example, employees might unwittingly use AI programs without proper oversight or understanding (e.g. improper use of data). These are the kinds of possibilities that summon risk and compliance leaders to begin governing AI.
Building the right governance program will differ for every organization. Still, there are six principles every organization can learn to take to start to keep the program on the right footing:
- Know where your AI lives
- Investigate the AI risks
- Educate your company on AI
- Understand how much risk your company is willing to take on
- Define a cadence for inventory review
- Begin to operationalize your AI governance plans
The first of these principles warrants a closer look.
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