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Enterprise AI Takes Center Stage as Over 50% of AI Use Cases Now Deliver Impact: Infosys Research

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Infosys

12 Mar, 2025, 10:50 GMT

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  • Agentic AI emerges as a priority for operating model transformation
  • Effective employee engagement and change management improve AI success by up to 18 percentage points

BENGALURU, India, March 12, 2025 /PRNewswire/ -- Infosys Knowledge Institute (IKI), a research arm of Infosys (NSE: INFY) (BSE: INFY) (NYSE: INFY), a global leader in next-generation digital services and consulting, today unveiled its largest survey of AI effectiveness to date. Titled Infosys AI Business Value Radar, the report surveyed 3,240 companies worldwide across 132 different AI business use cases and highlights a significant shift in AI deployment. Many organizations are now transitioning from experimentation to scaled deployment, thanks to decreasing costs and increasing success rates.

The research reveals that 19% of AI use cases deliver on all their business objectives, while another 32% show promise by partially meeting their objectives. The research indicates that organizations prioritizing core, transformational AI use cases are more likely to achieve business objectives. As AI costs decline in the future, the research data indicates these transformational use cases will rapidly begin to deliver more effective business outcomes. Well-designed change management strategies combined with robust employee training efforts enhance AI deployment success rates by up to 18 percentage points. These findings underline the growing potential of enterprise AI to deliver business value across industries, when supported by bold action focused on reshaping business processes, employee training and data architecture to ensure success.

Key Findings and Recommendations from the Infosys AI Business Value Radar Report

High-performing Industries:

  • White-collar and technically focused industries, such as professional services, life sciences, high tech, telecommunications, and insurance tend to achieve more success from AI.
  • Financial services are the only white-collar industry that ranks just below average on performance, likely due to regulatory and data modernization challenges.
  • However, AI is not benefiting all industries equally: Travel and hospitality, manufacturing, retail, and the public sector struggle to achieve consistent success.

Top Use Cases:

  • IT, operations, and facilities is the most pursued AI use case category, with 38% of respondents implementing it. This is followed by cybersecurity, resilience, and software development, with 30% pursuing these categories. Use cases in these categories are 10%-15% more likely to succeed.
  • The next most pursued are marketing, customer service, and sales.
  • Industry-specific applications, such as claims processing in insurance and clinical trials in life sciences, tend to improve core business operations. These use cases typically require transformation of data and technical architecture.

Change Management:

  • Only 16% of companies have implemented effective change management and employee training for AI.
  • 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.

Key Recommendations: The report recommends these five critical steps to become AI-first and generate business value from AI deployments:

  • Accelerate agentic AI as a route to operating model transformation.
  • Speed up innovation by simultaneous experimenting through an AI foundry and AI factory model.
  • Prepare employees by investing in training to achieve an 18-percentage point uplift in use case success.
  • Adopt a product-centric mindset to support AI operating models.
  • Create an AI governance task force to reduce risk and improve accountability.

Satish H C, EVP, Chief Delivery Officer, 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."

Jeff Kavanaugh, Head of Infosys Knowledge Institute, said, "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."

To read the full report with detailed insights, please visit here.

About Infosys

Infosys is a global leader in next-generation digital services and consulting. Over 300,000 of our people work to amplify human potential and create the next opportunity for people, businesses and communities. We enable clients in more than 56 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer clients, as they navigate their digital transformation powered by cloud and AI. We enable them with an AI-first core, empower the business with agile digital at scale and drive continuous improvement with always-on learning through the transfer of digital skills, expertise, and ideas from our innovation ecosystem. We are deeply committed to being a well-governed, environmentally sustainable organization where diverse talent thrives in an inclusive workplace.

Visit www.infosys.com to see how Infosys (NSE, BSE, NYSE: INFY) can help your enterprise navigate your next.

Safe Harbor

Certain statements in this release concerning our future growth prospects, or our future financial or operating performance, are forward-looking statements intended to qualify for the 'safe harbor' under the Private Securities Litigation Reform Act of 1995, which involve a number of risks and uncertainties that could cause actual results or outcomes to differ materially from those in such forward-looking statements. The risks and uncertainties relating to these statements include, but are not limited to, risks and uncertainties regarding the execution of our business strategy, increased competition for talent, our ability to attract and retain personnel, increase in wages, investments to reskill our employees, our ability to effectively implement a hybrid work model, economic uncertainties and geo-political situations, technological disruptions and innovations such as Generative AI, the complex and evolving regulatory landscape including immigration regulation changes, our ESG vision, our capital allocation policy and expectations concerning our market position, future operations, margins, profitability, liquidity, capital resources, our corporate actions including acquisitions, and cybersecurity matters. Important factors that may cause actual results or outcomes to differ from those implied by the forward-looking statements are discussed in more detail in our US Securities and Exchange Commission filings including our Annual Report on Form 20-F for the fiscal year ended March 31, 2024. These filings are available at www.sec.gov. Infosys may, from time to time, make additional written and oral forward-looking statements, including statements contained in the Company's filings with the Securities and Exchange Commission and our reports to shareholders. The Company does not undertake to update any forward-looking statements that may be made from time to time by or on behalf of the Company unless it is required by law.

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