Getting Agentic with NiCE
Authentic natural beauty and artificial intelligence came together at NiCE’s annual analyst summit, held on the beautiful island of Maui. Against a backdrop of palm trees and crashing waves, the discussions focused on AI, particularly agentic AI, and how it is changing the customer experience (CX) landscape.
The theme was “Huliau,” Hawaiian for turning point. And our industry is certainly at one. In just a few short years, we’ve gone from the introduction of generative AI and large language models (LLMs) to agentic AI and AI agents, and more recently, the emergence of personal AI agents. At each stage, NiCE has embraced the change, transforming itself from a CCaaS provider focused on customer service into a broader CX AI platform provider. The company is looking beyond the contact center to other areas of the organization that touch customers, including sales and marketing.
Cognigy Changes the Game
NiCE’s acquisition of Cognigy is central to this transformation. It gives the company a native CX AI platform with conversational and agentic AI capabilities built in to the CXone platform, positioning NiCE to address a much broader portion of the customer journey.
NiCE has a history of smart acquisitions, with inContact being one of the most notable. But Cognigy may prove to be its most consequential acquisition yet, helping propel NiCE ahead of other CCaaS and CX players in AI and agentic AI.
As CEO Scott Russell noted, “With Cognigy, we made a bet on AI. Cognigy changed the nature of who we are as a company. The capabilities Cognigy brought into NiCE are at the core. We made a bold bet, and it was successful.”
NiCE Cognigy acts as the intelligence layer of the NiCE platform, with agentic AI providing “reasoning across channels, orchestrating actions, and powering AI agents that can move from conversation to resolution.”
While many vendors are bolting on AI, partnering with third parties, or providing an AI layer without the underlying infrastructure (yes, I mean you, Sierra), NiCE has assembled the pieces of a more complete platform. In my view, the platform is NiCE’s biggest competitive advantage, or “moat.” It brings together:
Agentic Experience Automation: AI agents that resolve customer needs instantly and proactively, including agents for customer service, sales, and marketing, along with knowledge management and agentic analytics.
Engagement Orchestration: Orchestration across channels, people, AI, and systems, including omnichannel routing, outbound engagement, voice and digital engagement, and a newly designed agent workspace.
Workforce Empowerment: Bringing humans and AI together as one workforce, with workforce management, quality management, performance management, and recording and compliance.
CX AI models and layer: The AI capabilities that support the broader platform.
Customer Engagement Data: The data foundation for connected customer experiences and intelligence.
NiCE Cognigy’s conversational and agentic AI layer underpinning the entire platform.
AI isn't bolted on or treated as a separate, standalone layer. Instead, it is part of the overall platform, providing a connected operating model. (Cognigy can also be deployed separately by companies that want to integrate its AI capabilities with their existing CCaaS systems.)
The advantage of the integrated approach is that the same AI capabilities operate across the platform, enabling more connected and compounding intelligence and a more seamless experience.
NiCE Cognigy offers two deployment paths: a fully integrated experience within CXone for customers seeking one connected operating model, and a best-of-breed agentic AI option that integrates with existing CCaaS, CRM, and enterprise systems.
There are clear benefits to having Cognigy natively integrated into the architecture. Customers get a common user experience and shared data platform, while AI agents can be built using customer data and trained directly on interaction data. Data, channels, and orchestration are available out of the box, reducing the need for customers to build connectors or MCP integrations themselves. The result should be faster time to value and lower implementation risk.
Orchestrating Humans and AI
A key focus area at the event was the changing workforce. With agentic AI, humans and AI will increasingly operate as one workforce, resolving customer needs across the enterprise. This goes well beyond handing an interaction from an AI agent to a human agent. It requires common rules, tools, and governance for both human and AI workers, along with orchestration across the entire customer journey.
NiCE’s latest architecture added key capabilities to the platform, focusing on humans and AI working together, along with learning loops across the entire experience:
NiCE AI Agents: serving as the execution layer, the AI agents understand intent, take action across enterprise systems, and resolve customer needs across voice and digital channels.
Agentic Engagement Plane: the orchestration layer, designed to authenticate, mediate, route, and govern interactions as customers, employees, personal AI agents, and enterprise AI agents increasingly interact with one another.
NiCE Guardian Agent: for providing governance, Guardian monitors AI and human actions in real time, applying compliance guardrails and detecting risk.
Agentic Analytics: moving beyond reporting what happened to identifying what should happen next, feeding signals back into agents and workflows for continuous improvement.
Shared Cases: provide clear ownership and tracking from request to resolution
Experience Memory provides persistent customer and interaction context based on understanding of history, preferences, outcomes, and intents. This memory persists across every interaction
Together, these capabilities support a learning loop in which the platform learns from human experts, turns that knowledge into AI agents, and continually improves them. NiCE is evolving toward a fully integrated, self-improving process: identifying automation opportunities, creating agents, evaluating them against synthetic customers, deploying them across channels, and using the resulting insights to improve subsequent iterations. Every conversation can contribute to what the platform learns and how it handles future interactions.
I spoke with Jeff Comstock, President of CX Product & Technology, about the platform and the learning loop, and what it means for businesses.
Personal Agents: The Future of CX?
One of the hottest topics at the summit was personal AI agents, such as Meta Muse, Instinct, OpenAI Dots and Perplexity Comet. These personal agents have emerged relatively recently, but adoption has been rapid, with Muse reaching the top of the U.S. App Store.
Personal AI agents point toward a fundamental shift in how consumers interact with businesses. Today, people commonly use AI to find information, get recommendations, or help complete a task. Personal agents take this a step further: they can act on a person's behalf, interacting with websites, applications, and potentially businesses to accomplish a goal. They may use voice or text to make reservations, cancel subscriptions, and handle other tasks. For contact centers, the implications could be significant. The entity initiating an interaction may no longer be a person typing into a chat window or speaking to an agent - it may be another AI system acting on that person's behalf.
That raises questions about customer identity and authentication, journey design, service automation, agent productivity, security, and even how contact center performance should be measured.
Consider a personal agent tasked with resolving a delayed shipment, an unresolved support case, or a medical appointment. If the business doesn't deliver the desired outcome, the agent can keep trying until it gets the result it was instructed to pursue. Instead of a frustrated customer giving up after waiting in an IVR queue or navigating a website, businesses could face persistent, automated follow-up. That could affect IVR queues, call volumes, and other aspects of contact center operations.
Businesses will need to prepare for a world in which contact centers serve two types of customers: humans and AI agents. Contact centers will need to accommodate machine-initiated interactions, authenticate personal agents appropriately, establish security and governance controls, and determine what these agents are authorized to do.
We're still in the early days of personal agents, but businesses should already be thinking about how to prepare. During the customer panel at the summit, David Mayer, Associate VP, Data, Analytics, Learning and Quality Strategy at Hyatt, noted that online travel agencies are beginning to use personal agents.
Mayer told the audience, “Personal agents are coming and we have to prepare. Security and authentication are essential, and we have to verify if it’s a real person and customer behind the agent and not a bad actor.”
Rather than waiting for customers to start asking for support for these interactions, NiCE is taking steps to prepare for this next stage of CX AI. The company is participating in the development of the Personal Agent Protocol (PAP), an open standard being developed by Meta and Sierra, along with several industry partners, to define how personal agents interact with businesses.
NiCE also offers the CXone AI Agent Gateway, which Neeraj Verma, Vice President, Product Management, describes as the front door for personal AI agents contacting a business. It detects when a caller is an agent, verifies who it represents, limits what it is allowed to do, and gives the business visibility into the conversation.
These efforts demonstrate that NiCE is thinking beyond what customers need today to what they will need as personal agents become more common.
Personal agents also introduce a new dimension to workforce management and engagement. Customers and workers can be human or AI, and interactions may involve multiple combinations: a customer interacting with an AI agent, an AI agent escalating to a human, a consumer's personal agent interacting with a human agent, or eventually, AI agents interacting directly with one another.
As Russell pointed out, brands no longer own the customer journey. The AI agent will never give up and keep on trying. This presents a number of issues, including how enterprises will control interactions and the customer journey.
Based on my discussions at the summit, NiCE has clearly been thinking about these scenarios and how to prepare for this emerging environment.
NiCE CTO Kevin Lee and I discussed personal agents and some of the considerations businesses will need to address. (Note: AI was used to remove the background noise and music)
Creating Our Own AI Agents
The highlight of the analyst event was when the analysts were let loose to create our own AI agents for “NiCE Air.” We began by using NiCE Agentic Analytics to identify automation opportunities and determine where AI agents could be deployed. The system did all the work in analyzing real customer interaction data to identify what to automate.
We then built our own AI agents both from scratch and from human-to-agent engagements to run on chat and voice. We were able to see first-hand how much intelligence is built into the system, and how easy it is to create the agents. We gave them names, personalities, skills, guardrails, rules, and more. I never thought I’d be able to build my own AI agent, but the tools NiCE Cognigy provides make it easy.
The Changing Boundaries of CX
In this video discussion, Andy Traba, Vice President, Product Marketing, and Jennifer Wilson, Director, Product Marketing, shared their key takeaways from the summit, including the rise of personal agents, the changing boundaries of CX, and NiCE's move beyond the contact center. A recurring theme was that value is increasingly accruing around platforms rather than individual point solutions.
Traba also discussed the learning loops that enable each interaction to make the next one better. Wilson highlighted the demonstrations presented at the event, including persona-based experiences in which the workspace changes according to different users and their priorities. The demos illustrated how humans and AI agents can work together to achieve the desired customer outcome.
Wilson also discussed the Agentic Engagement Plane as a unified orchestration layer for managing the customer journey as a whole. Traba noted that the different workers share a Case Manager and Experience Memory, reinforcing the idea that work and context need to carry across people, agents, and channels.
Looking Ahead
One challenge NiCE - and other CCaaS vendors - will face is expanding into other areas of CX, particularly sales and marketing.
As discussed throughout the summit, AI expands NiCE's strategic role beyond customer service. The company aspires to move from being a software partner to providing a broader CX AI operating model. Russell described the bet NiCE is making as AI across the full customer experience, encompassing every engagement, workflow, worker, and outcome, from first contact to final resolution and from the front office to the back office.
“Customer service is the cornerstone, but we do so much more,” he explained, while acknowledging that NiCE doesn't claim to have every piece. That makes an open architecture essential.
Expanding into sales and marketing also changes the buying dynamic. NiCE is increasingly dealing with C-suite executives and technical decision-makers, in addition to traditional contact center buyers. As Russell explained, AI agents touch models, data, integrations, and security, so the Chief AI Officer, platform team, and AI engineer now make decisions alongside operations.
The economic model is changing as well, with monetization expanding beyond seat licenses toward intelligence and automation outcomes.
Working with partners such as Accenture will help NiCE engage the C-suite in these broader discussions. But the company still needs to demonstrate that it is more than a CCaaS provider. In fact, the term “CCaaS” barely came up in the presentations. More customer wins beyond customer service and the contact center will be important in establishing NiCE as a broader CX vendor.
Competition is another consideration. NiCE must contend not only with established CCaaS and CX players, but also with newer AI-focused competitors such as Sierra, Decagon, and Fin, which was recently acquired by Salesforce.
Sierra has been successful in part because of its founders' personal relationships, which can help secure meetings with senior executives and enterprise buyers. However, Sierra only provides the agentic AI layer rather than the kind of end-to-end platform NiCE is building.
NiCE's integrated platform is a differentiator, while its option to sell Cognigy as an agentic AI layer that integrates with existing CCaaS and CRM systems gives customers another path - one similar to the approach taken by standalone AI providers. That flexibility should help NiCE compete with point solutions as well as full-platform vendors.
Ultimately, NiCE is making a bet on AI across the entire customer experience: every engagement, workflow, worker, and outcome, from first contact to final resolution, front office to back office.
As Russell acknowledged, NiCE doesn't claim to have every piece. Instead, it is “betting on one platform that serves most of the experience, and an open architecture that brings in the best capability from everywhere else.”
In my view, NiCE's AI-first platform provides a strong foundation for a workforce made up of humans and AI agents. Its integrated approach, combined with its work on personal agents, also positions the company to address the next stage of CX. The challenge now is to turn that vision into demonstrable customer outcomes and establish NiCE's position beyond the contact center.
