With many organisations transitioning from just AI experimentation to scaled deployment, there is a need to create an AI governance task force to reduce risk and also to improve accountability, said Infosys Knowledge Institute, a research arm of Infosys. In its survey, it recommended five critical steps- Accelerate agentic AI; speed up innovation; prepare employees by investing in training; adopt a product-centric mindset to support AI operating models; and also create an AI governance task force so as to become AI-first and also to generate business value from AI deployments.
Titled Infosys AI Business Value Radar, the survey revealed that 19% of AI use cases deliver on all their business objectives, while another 32% show promise by partially meeting their objectives.
With decline of AI costs in the future, transformational use cases will rapidly begin to deliver more effective business outcomes. It also found that white-collar and technically focused industries, such as professional services, life sciences, high tech, telecommunications, and insurance tend to achieve more success from AI. Interestingly, financial services are the only white-collar industry that ranks just below average on performance, likely due to regulatory and data modernisation challenges.
AI is not benefitting all industries equally as travel and hospitality, manufacturing, retail, and the public sector struggle to achieve consistent success.
Satish H C, executive vice-president and chief delivery officer at Infosys, said: “Enterprise AI is ready to scale. With effective use of data architecture, operating models, and employee readiness, businesses can accelerate their adoption of AI to achieve measurable success. Our research indicates that agentic AI is critical to operating model transformation. We expect this to develop significantly over the coming year to become the driving force of enterprise transformation as it reshapes business processes, operating models, and technical architectures.”
When it comes to top use cases, IT, operations, and facilities are the most pursued AI use case category, with 38% of respondents implementing it. This is followed by cyber security, resilience, and software development, with 30% pursuing these categories. The report also said that companies that have taken initial steps to address AI can nearly double their likelihood of success with AI deployments by fully investing in workforce AI readiness.