NiCE Bets Big on Agentic AI With New Mpower Agents Launch
NiCE rebrands as an AI company and launches Mpower Agents for enterprise-wide automation, while analysts note industry caution around GenAI adoption.
NiCE, a leading contact center as a service (CCaaS) provider, has rebranded itself as an "AI company" and unveiled CXone Mpower Agents at its Interactions conference in Las Vegas. The new AI agents aim to automate workflows across self-service, mid-office, and back-end fulfillment, positioning NiCE at the forefront of the Agentic AI movement.
Key Announcements
- Mpower Agents: Designed to create and deploy AI agents in seconds, automating end-to-end customer service workflows.
- No-Code AI Studio: Allows business users to generate agents using outcome-based prompts without coding.
- AWS & Snowflake Partnerships: Integrates Amazon Bedrock, SageMaker, and Snowflake’s Data Cloud for scalable, secure AI deployments.
Analyst Perspectives
While NiCE pushes for enterprise-wide automation, analysts highlight lingering hesitancy among brands:
- Max Ball (Forrester): "Many brands are slow to adopt GenAI for customer-facing roles due to legal and trust concerns."
- Blair Pleasant (COMMfusion): "True Agentic AI—with reasoning and action—is still early for most contact centers."
Industry Trends
- Deloitte: Predicts 25% of GenAI-using companies will pilot Agentic AI by 2025.
- Gartner: Forecasts Agentic AI will handle 80% of routine service inquiries by 2029.
NiCE’s Strategic Shift
Under new CEO Scott Russell, NiCE is expanding beyond CCaaS into AI-driven CX, emphasizing:
- Human-AI collaboration: Supervising AI outputs to mitigate hallucinations.
- Proactive issue resolution: Addressing problems before customers notice.
Related Links
"There’s a big difference between AI that talks and AI that gets things done," said Barry Cooper, President of NiCE’s CX Division. The company’s bet on Agentic AI will test whether the contact center industry is ready for fully autonomous workflows.
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Dr. Sarah Chen
AI Research Expert
A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.