AI-matured organisations reap 5% higher revenue growth

Strong governance, reskilling, and ethical practices distinguish AI-mature organizations.  

Organisations with advanced AI maturity are reaping nearly 5% higher revenue growth and a 28% greater likelihood of employees using AI tools, according to Deloitte’s recent findings. However, achieving AI maturity requires a comprehensive approach encompassing governance, reskilling, and ethical practices.  

"AI maturity is evaluated across five dimensions," explained  Tomoko Yokoi, Lead Researcher of AI Maturity Index at IMD Business School. It includes strong executive support, investing into AI infrastructure, using AI to enhance operational efficiency, reskilling employees for AI initiatives, and having AI ethics and governance in place.  

Top-performing organizations distinguish themselves by excelling across all five dimensions. "It’s whether they have all of these initiatives in place that sets them apart," Yokoi added.  

Governance plays a critical role in both revenue growth and employee adoption of AI. "It's previously seen that around a quarter of senior executives felt they had the governance in place ready to manage AI risk, but actually there were less than 10% who had these necessary structures in place to be ready to manage AI risk," noted Dr. Elea Wurth, Lead Partner- Trustworthy AI, Asia Pacific and Australia at Deloitte.  

Building trust and fluency in AI is key to successful adoption. Wurth emphasised the value of "fluency training," where employees gain a clear understanding of what AI is and how to use it effectively.  

Yokoi echoed this sentiment, stressing the need for balanced training approaches. "It’s about training employees not only to understand the risks and opportunities but also to ask the right questions and engage constructively with colleagues," she said. Organizations must decide whether to upskill the entire workforce or focus on specialized training for a select group of experts. "Ideally, the balance of both is good," Yokoi added.  

Responsible AI use hinges on translating principles into action. "The first move is to translate these principles into practical guidance," Yokoi explained. Integration into operations, calibration to align ethics systems with evolving AI models, and widespread education are critical next steps.