Artificial intelligence (AI) has become embedded in the systems that power organisations, industries, and people’s daily lives. Generative AI (GenAI), in particular, is reshaping how organisations operate. In doing so, the technology is driving efficiencies and unlocking new opportunities. With this potential comes significant risk. Without comprehensive AI governance in place, organisations may struggle with compliance, ethical dilemmas, and trust issues that could undermine their AI investments.

Today, organisations are in a race to integrate AI into all aspects of their operations. However, a fundamental truth remains – AI will only be as valuable as the trust people place in it. Governance has become the bedrock upon which responsible AI must be built.

SAS research shows that 95% of businesses lack a comprehensive AI governance framework for GenAI, exposing them to compliance risks and ethical concerns. Without clear policies and oversight, AI systems can reinforce bias, compromise data security, and generate unreliable outcomes. Alarmingly, only 5% of companies have a reliable system in place to measure bias and privacy risk in large language models.

Regulatory considerations

Regulatory developments are particularly challenging as governments worldwide continue to assess whether and how to regulate AI. The European Union’s AI Act is leading the way, while countries across Africa and the rest of the world are considering their own regulatory frameworks. Organisations that fail to anticipate these changes risk not only legal penalties in some countries but also reputational damage and loss of public trust.

Governance provides the framework for mitigating these risks, ensuring AI systems align with ethical standards, business objectives, and legal requirements. To be effective, AI governance must incorporate oversight and compliance mechanisms that integrate legal, ethical, and operational safeguards. Transparency and accountability must be prioritised to ensure AI systems explain their decisions clearly, particularly in high-stakes sectors like finance, healthcare, and public services.

The integrity and security of data must be maintained by implementing mechanisms that protect sensitive information, detect biases, and ensure AI models use high-quality, unbiased information. AI governance is not a one-time task. Instead, it requires real-time monitoring and continuous adaptation to keep pace with evolving regulations and industry best practices.

Eroding trust

In the absence of strong governance, organisations face several challenges that can erode trust in AI. Weak regulatory compliance exposes organisations to increasing legal scrutiny, as governments worldwide tighten AI-related legislation.

Without proper oversight, AI models trained on biased data risk amplifying societal inequalities, damaging reputations, and alienating customers. Security vulnerabilities further compound these risks, making AI systems prime targets for cyberattacks that can lead to data breaches, intellectual property theft, and misinformation. Perhaps most critically, organisations without AI governance frameworks struggle to gain public and employee trust, limiting the widespread adoption of AI-driven solutions.

To ensure AI remains a force for good, organisations must adopt a governance-first mindset. AI must be developed and deployed in ways that are ethical, transparent, and human-centric. At SAS, we advocate for responsible innovation, ensuring AI systems prioritise fairness, security, inclusivity, and robustness at every stage of their lifecycle. Organisations need to move beyond passive compliance and take a proactive approach to AI governance.

Changing AI focus

This requires investments in training, the development of internal AI policies, and the implementation of technology that enforces governance at scale. Furthermore, organisations must cultivate a culture of AI literacy. Research shows that many senior decision-makers still do not fully understand AI’s impact, making it critical for organisations to equip their executives with the knowledge and tools needed to implement AI responsibly.

Ultimately, AI governance is not just about mitigating risks. Rather, it must be considered a strategic advantage. The companies that build AI systems on a foundation of trust will be the ones that thrive in an AI-driven world. Early adopters of trustworthy AI will not only stay ahead of regulatory shifts but also strengthen customer relationships and unlock AI’s full potential in a responsible and sustainable manner. AI’s evolution is inevitable, but how organisations engage with it will determine whether they succeed or fall behind.