Smart Customer Service White Papers
NiCE
Who’s going to manage the AI agents on your service team? Forrester has the scenarios.
Forrester's 2026 report, "AI Agents Reshape The Customer Service Workforce In Dramatic Ways," models a customer service organization that gets smaller at the front line and deeper in specialist roles: subject experts, relationship managers, hybrid quality managers, AI agent builders, and heads of support insights.
The harder question is how you run it. A workforce made of people and AI agents still needs forecasting, coaching, quality, and clear ownership. See the two- and five-year scenarios.
What the new org looks like:
• Compare two- and five-year staffing scenarios
• See which roles shrink, specialize, and emerge
• Assign ownership for AI supervision and quality
• Build the skills path for your team
Design the model before the org changes.
NiCE
Scale agentic AI pilots into enterprise systems: An MIT Technology Review webcast featuring Arun Chandra, NiCE COO
Most organizations can launch an agentic AI pilot. Scaling it across the enterprise is a different challenge entirely. Watch "Scaling Agentic AI Pilots into Enterprise Systems," an exclusive session with MIT Technology Review Insights and NiCE COO Arun Chandra. Discover how leading enterprises are moving beyond isolated pilots and standalone tools to connect AI across customer conversations, workflows, data, and decision-making, creating systems that continuously learn, improve performance, reduce complexity, and drive measurable business outcomes.
You'll discover how to:
- Move agentic AI beyond isolated pilots
- Build connected systems that continuously improve
- Transform customer conversations into operational intelligence
- Turn AI investment into measurable enterprise ROI
- Build an AI system designed to compound value
Watch now:
NiCE
Top 10 AI for CX customer stories
See how 10 global enterprises, including Toyota, Bosch, Hyatt, and Henkel, are putting AI into production to improve customer experience, increase efficiency, and drive business value. From automating end-to-end interactions and orchestrating proactive journeys to equipping employees with trusted knowledge, these stories show what AI looks like in action across industries. Discover proven approaches and measurable outcomes that can help shape your own AI strategy.
In this eBook, you’ll learn:
- How leading enterprises are applying and scaling AI across customer service operations.
- Which use cases are improving resolution, engagement, employee effectiveness, and operational efficiency.
Download the eBook
NiCE
The orchestration advantage: why platform architecture determines whether CX AI scales
Fragmentation rarely begins with one bad technology decision. It accumulates as each team solves a local problem — a virtual agent here, agent assist there, analytics to find patterns, automation to cut manual work — until the business is running dozens of capable tools that were never designed to operate as one system. Each works. The journey between them does not.
In this independent report, Opus Research analysts Derek Top, Ian Jacobs, and Amy Stapleton set out what has to be shared for agents, people, and systems to work as a coordinated whole: journey and intent state, identity and consent, policy and guardrails, knowledge governance, and evaluation, testing, and audit. They examine what separates a pilot from a production operating model, how human and AI work should be measured on one scorecard, and why the arrival of customer-owned AI agents makes identity and authorization urgent rather than theoretical.
The report closes with a nine-dimension readiness framework. Score your organization from 9 to 27, then use the two weakest dimensions to decide where the next twelve months of investment should go.
What the report covers:
• The five layers of a CX AI control plane
• Where fragmented CX AI stacks break, and what it costs
• Three practical tests for any openness claim
• A nine-dimension readiness score you can run today
Know your CX AI orchestration score.