{"slug": "nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them", "title": "NiCE’s next-generation Cognigy bets the hard part of AI agents is running them, not building them", "summary": "NiCE Ltd. launched the next-generation NiCE Cognigy this week, adding a redesigned Agentic Experience Studio, an AI Assist companion for building, testing and improving agents, reusable \"skills\" and turn-by-turn tracing, with default speech-to-text, text-to-speech and large language models now included in the per-conversation price and premium models from Deepgram, ElevenLabs and Anthropic billed by usage. NiCE Cognigy senior product marketing manager Nhu Ho said \"Capable and dependable do not always mean the same thing,\" citing a chart showing AI can work autonomously for roughly 16 hours this year, up from seconds in 2020 and minutes in 2024, but at a 50% success rate. Director of product management Clement Boutier said the prior platform's large number of configuration options \"creates friction to get started, which slows things down,\" and the new studio lets a builder stand up an agent in a few clicks while keeping full system-prompt access in advanced sections.", "body_md": "### NiCE’s next-generation Cognigy bets the hard part of AI agents is running them, not building them\n\nThe contact center has been the low-hanging fruit for the artificial intelligence industry. Ask any information technology or business leader what they want to use agentic AI for, and they will say it’s to improve the customer experience, which starts with the contact center.\n\nHowever, to date, the industry has spent the past two years arguing over which AI agent is the smartest. That’s the wrong debate. Model capabilities are improving so quickly and are getting so much cheaper that raw intelligence and reasoning are becoming the least differentiated part of the stack.\n\nThe real challenge for enterprises is operating a fleet of AI agents reliably across complete customer journeys, with the visibility and control a large business requires. Without that, the human, or worse, the customer, is left connecting the dots among the outputs of the growing number of agents they are communicating with.\n\nThat’s the thesis behind the next generation of [NiCE Cognigy](https://www.cognigy.com/), which [NiCE Ltd. launched this week](https://www.nice.com/press-releases/nice-launches-next-generation-nice-cognigy-to-accelerate-enterprise-ai-agent-deployment-and-orchestration). The release includes a redesigned Agentic Experience Studio, an AI Assist companion spanning the building, testing and improvement of agents, reusable “skills” that package instructions and tools, turn-by-turn tracing and native voice-to-voice model support.\n\nDefault speech-to-text, text-to-speech and large language models are now included in the per-conversation price, with premium models from Deepgram, ElevenLabs and Anthropic available with a few clicks and billed by usage.\n\nAhead of the launch, I attended an analyst briefing with Nhu Ho, senior product marketing manager at NiCE Cognigy, and with Clement Boutier, director of product management, who leads the team that built the release and owns the platform roadmap.\n\nHere are the important points from this release:\n\n### Capable is not the same as dependable\n\nHo opened with a chart showing how long AI can work on its own before a human has to step in. In 2020, it was seconds; in 2024, it was minutes; and this year it’s roughly 16 hours. The footnote was interesting, as it calculated that figure at a 50% success rate. “Capable and dependable do not always mean the same thing,” Ho said. “That is exactly where the platform matters.”\n\nFor CX leaders, that’s a solid benchmark to consider. A 50% success rate is a research milestone. In a contact center, it’s a churn event or a compliance violation. As models commoditize, value shifts to the system around them: testing, tracing, guardrails and deterministic fallbacks. NiCE doesn’t build frontier models, and frontier model builders don’t run contact centers. Positioning Cognigy as the layer that makes AI dependable is a smart place to plant a flag.\n\n### Simplicity is a strategic fix, not a cosmetic one\n\nCognigy earned its pre-acquisition leadership position by handling complex production deployments for large brands such as Lufthansa, Mercedes and DHL. But that flexibility and customizability added complexity. Boutier put it this way: “The large number of options when configuring an agent creates friction to get started, which slows things down.” The new studio lets a builder stand up an agent in a few clicks, with models already provisioned, while power-user tools, including full access to the agent’s system prompt, are available in advanced sections.\n\nThis is important because NiCE aims to create a “1+1=3” value proposition for its current customers. NiCE needs Cognigy to expand broadly across the CXone installed base, not just among expert teams at the largest enterprises. Boutier described three builder personas: smaller businesses building simple agents, contact center administrators and team leads, and engineers at technically sophisticated companies. AI Assist is aimed squarely at the first two.\n\nIn the demo, it built an agent, tested it, fixed the problems it found, and deployed it to WhatsApp. The flip side is that lowering the barrier means more agents built by less experienced people, which makes the governance features the real story of this release.\n\n### Hybrid is where the market actually lives\n\nDespite all the agentic hype, most enterprises aren’t ready to hand over entire journeys to an autonomous agent. Boutier outlined three modes: traditional natural language understanding, hybrid and fully agentic. Hybrid “is actually where most of our customers are,” he said, while fully agentic deployments are at the “beginning of the adoption curve.” This approach lets customers ease into agentic, build confidence and move to fully autonomous at their own pace.\n\nNiCE designed the product for that approach. An agent can serve as the orchestration layer, calling existing flows as tools. Flows can also be placed in front of agents, for example, to scrub credit card numbers or other personal data before any data reaches a model. Ho described the release as “an evolution, not a replacement,” with production deployments, application programming interfaces and integrations continuing to run unchanged.\n\nThat’s a meaningful advantage over AI-native challengers whose pitch effectively requires a rebuild. Contact centers are the fastest-moving environments, and deterministic workflows aren’t legacy baggage. They’re how a business enforces what a large language model shouldn’t be deciding.\n\n### Observability is the new battleground\n\n“You can have the best builder experience, but if you don’t have any feedback loop on what you’re building, you’re never going to build a great agent,” Boutier said. The new tracing shows each turn: which skill loaded, which tool was called and with what arguments, and when the agent handed off to a flow.\n\nThe Simulator now supports multivariate testing of up to 10 variants, using an LLM-as-judge to run synthetic customers against an agent. Boutier ran the same agent on two models and found that one was faster and consumed fewer tokens. This shifts model selection from a preference to a data-backed economic decision.\n\n### The front door is about to get crowded\n\nVoice-to-voice support may be the first feature customers deploy. Boutier noted that buyers are open to using a speech-to-text and text-to-speech cascade, “but what they realize is that voice-to-voice models sound just better.” In the demo, the agent delegated tool calls to a separate model while continuing to talk, making the conversation sound far more natural.\n\nCognigy now serves as both a Model Context Protocol client and server and supports agent-to-agent connections, including one customer linking Cognigy to agents built with Microsoft’s tooling. NiCE is also co-developing the Personal Agent Protocol with Meta and Sierra, which isn’t live yet. Boutier described Cognigy as “the front door” of the contact center, where a consumer’s personal agent must authenticate before it can proceed. It’s great to see NiCE collaborating with Sierra, a direct competitor, on this, as it makes things easier for a customer.\n\nThe industry views agent identity as a shared responsibility. But as [Sierra outlines](https://sierra.ai/blog/poppy), companies can also let personal agents work through their websites and APIs, so the front-door position depends on enterprises routing that traffic through Cognigy. This lets brands interact with personal agents safely.\n\nThere has been a wave of companies banning personal agents, which I think is a mistake. If something is good for a consumer, it will happen, so it’s better to be on the leading edge of enabling it rather than fighting it.\n\n### Advice for IT pros\n\n- **Map the hybrid line.** Decide which processes remain deterministic, such as payments, identity verification and regulated disclosures, and which can be delegated to an agent. Don’t let that line drift by default.\n- **Make tracing a go-live requirement.** No agent should reach production without someone able to explain why each action was taken.\n- **Use simulation to settle model debates.** Compare variants by cost per resolved conversation, not by anecdote, and rerun the tests as new models ship.\n- **Own compliance.** Boutier said responsibility is shared: “We offer the tools and the platform, but we cannot 100% control what they put in it.” Regional rules on AI disclosure and human escalation must be built in by the customer.\n- **Treat guardrails as a budget line item.** Each guardrail adds tokens and latency. “The more you add, the more bloated your agent becomes,” Boutier said. Spend that budget where risk is highest.\n- **Prepare for machine customers.** Don’t ban personal agents; rather, set policies now on which personal agents you’ll accept and what they can do.\n\n### Final thoughts\n\nThis release is less about new capabilities and more about NiCE betting on where value will accrue as AI agents mature. Intelligence is getting cheaper. Dependability, governance and the ability to blend autonomous reasoning with deterministic control are not.\n\nNiCE is the market leader in contact center as a service, as Cognigy was in conversational AI. Now the challenge is to get an easier-to-work-with Cognigy into the hands of thousands of CXone customers without creating a sprawl of individually governed agents. This will allow NiCE to maintain its industry leadership as personal agents arrive. As it does that, the Cognigy acquisition will move from an add-on to a core component of the NiCE platform.\n\n*Zeus Kerravala is a principal analyst at ZK Research, a division of Kerravala Consulting. 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Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.", "url": "https://wpnews.pro/news/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them", "canonical_source": "https://siliconangle.com/2026/11/13/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them-not-building-them/", "published_at": "2026-11-14 00:49:43+00:00", "updated_at": "2026-11-14 00:53:15.698717+00:00", "lang": "en", "topics": ["ai-agents", "ai-products", "artificial-intelligence", "large-language-models"], "entities": ["NiCE Ltd.", "NiCE Cognigy", "Nhu Ho", "Clement Boutier", "Deepgram", "ElevenLabs", "Anthropic", "Agentic Experience Studio"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them", "markdown": "https://wpnews.pro/news/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them.md", "text": "https://wpnews.pro/news/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them.txt", "jsonld": "https://wpnews.pro/news/nices-next-generation-cognigy-bets-the-hard-part-of-ai-agents-is-running-them.jsonld"}}