Experian, a leader in data and technology, has released a report on the implications and execution of Responsible AI among UK business leaders. The research reveals a burgeoning embrace of AI and the recognition of its potential.

The majority of participants—89%—have noted positive impacts on their operations from AI. Despite these advantages, there is a strong belief among 87% of respondents that prioritising Responsible AI will be crucial in the near future for standing out in a competitive market.

The report indicates rising consumer expectations as a significant catalyst for the drive towards Responsible AI. A noteworthy 84% of respondents conveyed that customers are increasingly concerned with understanding AI governance and accountability frameworks.

Despite recognising the value of Responsible AI, 76% of leaders report challenges in its practical implementation. Chief among these obstacles are limited technical expertise (32%), difficulty in applying theoretical principles to real-world solutions (31%), and the struggle to balance innovation with governance (30%).

The study also uncovers a gap in data quality and skills. Although 90% contend that high-quality data is imperative for Responsible AI, merely 43% trust their data's robustness to support it. Similarly, only 48% feel their teams are adequately prepared to propel Responsible AI forward, underscoring the urgent need for enhanced data management, practical training, and cross-functionality.

To aid in overcoming these hurdles, Experian's report proposes strategies for embedding Responsible AI. Recommendations include consistent AI model assessments and applying best practices in security for every AI implementation. The insights provided by Experian’s AI specialists are designed to influence training approaches, innovation, and Responsible AI deployment.

The report underscores the need for solidifying data governance and fostering collaboration for successful AI integration. As reflected by Christine Foster from Experian, the integration of quality data, accountability, and supportive tools are foundational for ongoing AI evolution.

Responsibility in AI is not solely about technological frameworks but also about cultural and organisational shifts towards transparency, fairness, and sustainability. As industries continue to adopt AI technologies, forming strong frameworks is not just beneficial—it's necessary for maintaining competition and building trust with stakeholders.