Infosys: Enterprise AI Shifts from Experimentation to Impact
Infosys Knowledge Institute, the research arm of Infosys, has released its most extensive study to date on AI effectiveness.
For the research, the Infosys AI Business Value Radar surveyed 3,240 companies worldwide, covering 132 AI business use cases.
The findings highlight a significant shift: businesses are no longer just experimenting with AI but are scaling it to achieve tangible outcomes.
The report reveals that 19% of AI use cases fully deliver on their business objectives, while another 32% show partial success.
As the costs of AI implementation decline, these numbers are expected to rise, particularly for organisations focusing on transformational AI applications.
The industries seeing the biggest impact
Certain industries are emerging as leaders in AI deployment.
Professional services, life sciences, high tech, telecommunications, and insurance are seeing the highest success rates.
These sectors, often reliant on technical expertise and data-driven decision-making, are reaping the benefits of AI-driven transformation.
However, AI implementation is not without its challenges.
The financial services industry lags slightly behind its white-collar counterparts, largely due to regulatory and data modernisation hurdles.
Meanwhile, sectors such as travel and hospitality, manufacturing, retail, and the public sector have struggled to achieve consistent AI success.
The most successful use cases
The report highlights IT, operations, and facilities management as the most pursued AI applications, with 38% of respondents implementing AI in these areas.
Cybersecurity, resilience, and software development follow closely, with 30% of companies focusing on these use cases, which are also among the most likely to succeed.
Marketing, customer service and sales are also key areas of AI investment.
In industry-specific applications, such as claims processing in insurance and clinical trials in life sciences, AI adoption is proving to be a critical driver of efficiency and accuracy.
However, these applications often require significant transformation of data and technical architecture.
Change management remains a key challenge
Despite AI’s growing impact, companies are still struggling with change management and employee readiness.
The report states that only 16% of organisations have implemented effective employee training and change management strategies for AI adoption.
Businesses that invest in these areas can improve their AI success rates by up to 18%, Infosys said.
Jeff Kavanaugh, Head of Infosys Knowledge Institute, emphasises the importance of organisational change.
“In our largest AI research to date, we have uncovered the drivers of AI business success,” he explains.
“Organisations 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.”
Agentic AI driving business transformation
The study also identifies agentic AI – AI systems designed to take proactive, autonomous actions – as a critical factor in business model transformation.
As AI technology matures, enterprises are expected to integrate agentic AI into their operations to reshape processes and technical infrastructures.
Satish H.C., EVP and Chief Delivery Officer at Infosys, highlighted the importance of this trend, stating, “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.”
Looking ahead
The report outlines five key steps for companies aiming to maximise AI’s value.
These include accelerating agentic AI adoption, investing in AI innovation through a dual AI foundry and AI factory approach, preparing employees through training, adopting a product-centric AI operating model, and establishing AI governance frameworks to manage risk.
As enterprise AI moves from theory to execution, organisations that invest in robust AI strategies, workforce training, and governance will be best positioned to capture long-term value.
With AI deployment success rates on the rise, businesses that take bold action today are likely to lead in the AI-driven economy of the future.
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