AI governance: Balancing policy, compliance and commercial value

Concerns over responsible AI have risen sharply alongside AI adoption, and global policymakers are rapidly formalizing AI rules to mitigate societal, technical and commercial challenges.

Realizing the transformational potential of AI means distinguishing genuine matters of concern from ‘phantom’ risks, and enabling continued progress with appropriate legal frameworks, compliance protocols and ethical guardrails. 

This report cuts through AI hype and hysteria to offer a practical perspective on AI governance, strategies, challenges and risks. These insights are based on original research among 600 leaders in a wide range of organizations across the globe. We asked about what they’re already doing in relation to AI, what they’re planning to do and what concerns remain to be addressed. 

We are at a turning point in the evolution of AI. Generative AI has become ubiquitous, with ChatGPT experiencing the fastest growing user base in history, and as AI hardware continues to evolve we are seeing an explosion of new offerings and startups come to market. 

Our research confirms that AI is a fact of modern business. 

The majority are buying solutions from external AI vendors. The amount of data and investment in computational resources required to train the largest foundational models is vast. This high cost of implementation and concerns over how and when AI will provide a return on investment means that very few organizations are exclusively building their own solutions in house – with 22% choosing a hybrid approach. 

Globally, AI-specific regulatory reform is adding disparate rules to data protection, confidentiality and intellectual property. In addition, governance frameworks, policies and practices must be made fit for the AI era, and partner and vendor arrangements take on a different complexion where demand for innovative AI solutions is so high.

Against this backdrop, it is perhaps unsurprising that 99% of survey respondents ranked governance as a critical AI challenge, with difficulty defining what good governance looks like in their organization.

The overwhelming majority (96%) also cite overseeing AI initiatives to ensure they remain within regulatory guidelines as a top challenge, and we know that many organizations struggle to find the right capabilities and structures internally to exercise proper oversight.

Our data reveals inconsistent approaches to AI governance and ethical standards that are unlikely to meet the scale of the issues raised by AI. Organizations are taking necessary but not sufficient action.

The majority (83%) of companies have a vision and strategy for AI. Of that number, 86% have also adopted an AI code of ethics designed to guide projects and initiatives.

Half of leaders (49%) want to unlock the value of AI in line with their organizational values and a further 65% have put intention into action by terminating AI supplier contracts over ethical concerns.

Our research shows that a fragmented regulatory landscape and uncertainty over what good AI governance looks like are big challenges for organizations. But competitive pressures and speed of evolution mean that AI adoption can’t wait.

So what can you do to develop and deploy AI responsibly, safely and commercially, and to align commercial value with ethical values to achieve good AI governance? Below is a starting point for you to strengthen AI strategies.

To explore the findings in more detail in the full report, complete the form below.