Enterprises push agentic AI from pilots to scale

Agentic AI is shifting from experimentation to enterprise deployment, but scaling remains uneven. Although agentic AI has been adopted by some 80% of Fortune 500 companies, many organizations are still operating isolated pilots rather than integrated systems that can support core business workflows.

NiCE chief operating officer Arun Chandra says companies need to connect agentic AI initiatives to clear strategic or financial objectives, such as increasing revenue or reducing costs. He argues that organizations should redesign inefficient workflows before adding AI, because applying agents to outdated processes can limit their value.

Effective deployment also depends on giving agents access to the data, knowledge, context, and back-end systems needed to make decisions and take action. Fragmented systems can weaken performance, while governance, privacy, security, and change management become more important as agents take on more consequential work.

Chandra says enterprises should view the workforce as a combination of humans and AI agents held to similar standards. A connected strategy focused on high-value use cases, workflow changes, and measurable outcomes could eventually allow agents to act proactively and coordinate with other agents to resolve customer needs.