Infosys highlights AI's growing impact on global industries

Infosys Knowledge Institute (IKI), the research division of Infosys, has released its latest survey, "Infosys AI Business Value Radar", which provides insights into the impact of Artificial Intelligence (AI) across various industries globally.

The study, involving 3,240 organisations worldwide across 132 AI use cases, identifies a major shift from AI experimentation to scaled deployment. This change has been facilitated by decreasing costs and improving success rates in AI utilisation.

The research highlights that 19% of AI use cases fully achieve their business objectives; an additional 32% partially meet their objectives. The report suggests that prioritising transformational AI use cases increases the likelihood of achieving business objectives. With declining AI costs, the anticipation is that these transformational use cases will soon generate more impactful business outcomes. Effective change management and employee training efforts are shown to enhance AI deployment success rates by up to 18 percentage points.

According to the study, industries such as professional services, life sciences, high tech, telecommunications, and insurance exhibit higher success rates with AI. Conversely, sectors like travel and hospitality, manufacturing, retail, and the public sector face challenges in consistently achieving success with AI initiatives. Interestingly, the financial services sector, despite being white-collar, falls just below average in leveraging AI effectively, attributed to regulatory and data modernisation hurdles.

In terms of AI use cases, IT, operations, and facilities lead with 38% of respondents adopting these. Cybersecurity, resilience, and software development follow closely, being pursued by 30% of respondents. These categories enjoy a 10%-15% higher success likelihood. Other pursued categories include marketing, customer service, and sales. Meanwhile, industry-specific applications such as claims processing in insurance and clinical trials in life sciences enhance core business operations, necessitating substantial transformation of data and technical infrastructure.

The report points out that only 16% of companies have implemented effective change management and employee training programs for AI. In organisations that have addressed these initial steps, there is nearly a twofold increase in the likelihood of AI deployment success achieved through comprehensive workforce AI readiness.

Several key recommendations emerge from the report, including the acceleration of "agentic AI" to drive operating model transformation, enhancing innovation through AI foundry and factory models, and investing in employee training for an 18-percentage point improvement in use case success. The report advises organisations to adopt a product-centric mindset in their AI operating models and to establish an AI governance task force to mitigate risks and enhance accountability.

Satish H C, Executive Vice President and Chief Delivery Officer at Infosys, commented, "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."

Jeff Kavanaugh, Head of Infosys Knowledge Institute, remarked, "In our largest AI research to date, we have uncovered the drivers of AI business success. Organizations that go beyond experimentation and fundamentally change their operating model, as well as support their employees through the journey, are most likely to thrive in the era of Enterprise AI."