Industry Giants Vow To Harness Generative Ais Full Potential Amid Governance Challenges

Generative AI Governance: Unlocking Innovation and Value

A recent study by the IBM Institute for Business Value found that companies aim to grow their generative AI model portfolios by 50% over three years, but one in three pause an AI use case after the pilot phase. This indicates a need for effective governance.

Effective governance is no longer seen as an obstacle to innovation but rather as a driver. With the market for generative AI expected to double every other year, and successful digital transformation with this technology at its center capable of resulting in up to USD 1.25 trillion in additional market cap, companies must rethink their approach.

Research suggests that “AI washing” is prevalent, where companies overstate their progress. For example, IFA Magazine reports a 75% increase in UK companies mentioning ‘AI’ in shareholder statements between 2022 and 2024, but only 5% of generative AI experiments are operationalized into production in the Nordics.

An EU-wide study from the European Commission shows that as of 2023, only 8% of EU businesses actively use AI technologies. This data highlights the contrast between AI ambitions and practical outcomes across Europe.

A lack of joined-up thinking is a major barrier to realizing the benefits of generative AI. Companies often deploy AI in silos, with different teams experimenting with small initiatives without an AI inventory. Without this, companies waste resources and miss out on bigger opportunities.

When customers know a brand is using AI, their trust in the brand declines by a factor of 12. Companies must address this issue head-on and put measures into place to reduce the risk of AI bias and discrimination.

However, perceptions about AI governance are shifting. Chief data scientists and chief compliance officers now recognize the importance of effective governance for ensuring safety and effectiveness. They see governance as crucial for responsible AI deployment and mitigating potential risks.

Governance isn’t just about reducing risk; it’s also about accelerating innovation. By proactively rolling out an AI governance framework, companies can unlock efficiencies and gains that may have been eluding them until now. An effective framework helps prioritize the right use cases, focusing investments where they’ll generate the largest returns.

Building trust into AI initiatives is essential. Ensuring data sets are appropriate, sustainability targets are taken into account, and more can help move more generative AI models into production, giving companies an advantage over competitors.

Recent developments in regulation support this approach. The World Economic Forum reported that funding for generative AI reached £25.2 billion in 2023. This critical role of robust governance is underscored by the EU’s landmark AI Act, which aims to standardize regulations focusing on accountability and transparency.

To succeed, building an AI governance framework may seem daunting, but it’s not as challenging as it appears. Companies should create a cross-function AI team to ensure responsibility isn’t isolated to the risk and compliance department. Prioritizing AI literacy at the C-level can also help ensure alignment across leadership. Finally, setting clear goals for your AI initiatives from the outset is essential.

By following these steps, organizations can put themselves in the best position to succeed in a world where generative AI is playing an increasingly significant role.