We’ve read hundreds of reports suggesting AI is revolutionising industries worldwide. These reports claim AI offers unprecedented opportunities for business growth and efficiency and cite nuanced case studies to support their claims.
However, while the world is trying to agree on metrics to test the rate at which AI empowers businesses to grow more efficiently, the data shows that AI impacts organisations fundamentally. How is not essential for now, but the technology is being compared to the internet boom from 1995 onwards. So, the impact is likely significant.
Still, these advancements (like with any frontier technology) bring about significant governance challenges for organisations. So, how do you govern AI? Our view: to govern AI, you need an AI governance policy that:
- helps you harness the benefits of AI; and
- mitigates AI risks.
This post provides an overview of AI governance. It highlights the importance of establishing a policy to manage the risks and complexities associated with AI within an organisation. The reader will gain insights into effective AI governance, such as accountability, risk management, compliance, and aligning AI systems with organisational culture and values.
The ideal audience for this post includes executives, legal professionals, IT managers, and decision-makers within organisations who are involved in or considering the implementation of AI technologies. It’s particularly relevant for those seeking to align AI initiatives with regulatory requirements, ethical standards, and strategic business objectives.
The importance of AI governance
AI governance is critical for maintaining the integrity, accountability, and transparency of AI systems within an organisation. The best practice to starting AI governance is through a well-structured AI governance policy.
This policy must align AI deployment with your organisation’s goals and safeguard your organisation’s stakeholders against potential risks, such as bias, data privacy concerns, and operational disruptions.
Key elements of an AI governance policy
- Accountability and oversight: The policy should establish roles and responsibilities to oversee AI initiatives. This oversight function ensures that the organisations uphold governance practices throughout the AI lifecycle.
- Risk management: AI introduces new risks that traditional governance frameworks may not address enough. These risks include data-driven biases, lack of transparency in AI decision-making, and the potential for AI systems to evolve beyond their initial programming. Given these risks, AI governance policies should incorporate mechanisms for ongoing risk assessment and management.
- Compliance: As regulatory landscapes evolve, organisations must ensure that their AI systems comply with existing laws and standards.
- Transparency and explainability: AI systems must be designed to allow for transparency in decision-making processes. This means establishing protocols to ensure that stakeholders can understand and, if necessary, audit how AI-driven decisions are made.
Insights from ISO/IEC 38507:2022
The ISO/IEC 38507:2022 standard offers guidance on the governance implications of AI use within organisations. It emphasises the need for governing bodies to adapt their oversight mechanisms to address the unique challenges posed by AI technologies. What follows is more insight from the standard:
- Maintaining governance: The standard highlights that you may to revise your existing governance frameworks when introducing AI into your organisation. Why? AI systems often operate at speeds and levels of complexity that can outpace traditional oversight practices. As such, governance policies must be agile and capable of evolving in response to AI-driven changes.
- Maintaining accountability: The governing body must maintain accountability across all levels of AI implementation. This duty includes both the technical aspects of AI systems and the ethical and legal implications of their use. The standard advises against attributing responsibility to AI systems themselves. In other words, accountability always resides with human operators and decision-makers.
- Data governance: AI systems rely heavily on data. As such, data governance is crucial to AI governance. The standard advises that organisations must ensure the quality, integrity, and security of the data AI systems use. This obligation includes implementing measures to prevent data-driven biases and ensuring that data processing activities comply with legal and ethical standards.
- Cultural and ethical alignment: The standard also stresses the importance of aligning AI systems with your organisation’s culture and values. This process involves setting up mechanisms to monitor AI behaviours and ensuring that they reflect your organisation’s ethical standards. By implication, in some cases, you may need to limit the scope of AI systems or augment human oversight to maintain this alignment.
Our approach to AI governance
At ITLawCo, we integrate insights from leading standards like ISO/IEC 38507:2022 into our AI governance frameworks.
Our approach ensures that your AI initiatives are compliant with current regulations and aligned with best practices for transparency, accountability, and ethical integrity. We work closely with your organisation to tailor AI governance policies that support your strategic goals while managing risks and safeguarding stakeholder interests.
How ITLawCo can help
With our deep expertise in AI governance, we are uniquely positioned to help you navigate the complexities of AI deployment. Whether you are developing a new AI strategy or refining existing practices, we provide practical, actionable guidance to ensure your AI systems are implemented responsibly and effectively. Contact us to build a robust AI governance policy that empowers your organisation to innovate with confidence and integrity.
