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This evolution matters because enterprises face increasingly complex challenges: Handling customer inquiries requires understanding intent and emotion—as well as meeting consumer expectations of continuous support. Supply chain decisions demand real-time analysis of variables too complex for a single human to understand. Strategic planning involves synthesizing information from a vast number of disparate sources.
Increasingly, enterprises use AI in HR, procurement, sales, finance and IT departments to increase efficiency and reduce routine manual work. In recent years, IBM deployed agentic AI internally across a wide variety of workflows and functions to 270,000 employees. The initiative resulted in an estimated USD 4.5 billion productivity impact.
The shift toward agentic AI is industry-wide: Gartner predicts 60% of IT operations will incorporate AI agents by 2028. Forrester forecasts the world’s top five human resources management platforms will offer digital employee management capabilities in the coming year.
Beyond simple productivity gains, agentic AI transforms enterprise operating models. When agentic AI is embedded across departments and functions, its ability to make accurate, real-time decisions increases dramatically. With manual work performed by digital workers, employees necessarily shift focus to more value-driven work.
Today, enterprise data originates from a wide range of sources, spanning financial records, digital collaboration software and customer relationship management (CRM) platforms. Unifying this data reduces redundancies across platforms and allows for more accurate business-level forecasting.
