Majority of AI use cases delivering on objectives: research

Just over half (51%) of AI use cases are now delivering on their business objectives as the technology matures, according to a large-scale research project from Infosys Knowledge Institute.

A survey of 3240 companies worldwide across 132 different AI business use cases found that 19% are delivering on all their business objectives and a further 32% are partly meeting their objectives. Organisations prioritising core, transformational AI use cases are more likely to achieve their goals, and as AI costs decline in the future, these use cases will rapidly begin to deliver more effective business outcomes, Infosys said.

The highest performing industries are white collar and technically focused industries such as technology, life sciences, professional services, telecommunications and insurance. Conversely, travel and hospitality, manufacturing, retail and the public sector are struggling to achieve consistent success.

The report also found that the top AI use cases are IT, operations and facilities related, with 38% of respondents implementing AI in these fields. This is followed by cybersecurity, resilience and software development, with 30% pursuing these categories.

Other popular use cases are marketing, customer service and sales. Meanwhile industry-specific applications, such as claims processing for insurance, are likely to improve core business operations.

But the report also found that only 16% of companies have implemented effective change management and employee training for AI. Those who have done so are up to 18 percentage points more likely to see AI deployment success.

Infosys is recommending five critical steps to generate business value from AI deployments, with the first being to accelerate adoption of agentic AI. Organisations should also speed up innovation by: adopting an AI foundry and AI factory model of simultaneous experimentation; investing in training to prepare employees; adopting a product-centric mindset to support AI operating models; and creating an AI governance taskforce to reduce risk and improve accountability.

Infosys Knowledge Institute head Jeff Kavanaugh said the research has uncovered the drivers of AI business success.

“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,” he said.

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