As enterprises worldwide adopt generative AI to drive innovation and efficiencies, concerns about risks and challenges are growing, particularly among C-suite executives. While 93% of organisations use generative AI in some capacity, leaders are aware of the need to balance innovation with risk to compete in an increasingly AI-driven world. Research reveals that planning for IT resources, sourcing and protecting data, and ensuring accuracy and transparency of AI models are significant challenges facing organisations. Furthermore, the lack of expertise and discipline in implementing responsible generative AI can expose sensitive data, introduce bias, and harm innovation. A unified asset strategy is identified as a potential solution to these challenges, enabling organisations to manage, protect, and optimise digital and physical assets used in and produced by generative AI applications. The research also highlights the need for experienced AI leaders, such as a chief AI officer, to drive the effective and compliant adoption of generative AI.
Balancing Innovation and Risk in the Age of Generative AI
With ubiquitous, free generative AI tools, citizen ‘data scientists’ propagate shadow AI without the training, discipline and organisational support needed to implement responsible generative AI.
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