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The Gist
- What launched. NiCE unveiled NiCE Labs at NiCE World in Orlando on June 9, establishing a dedicated AI innovation engine focused on research, benchmarking, and rapid prototyping for enterprise agentic customer experience.
- Why it matters. NiCE says the gap between what AI can do in a research environment and what it reliably delivers inside a complex enterprise is where most organizations struggle. NiCE Labs is designed to close that gap through domain-specific research, rigorous model evaluation, and co-development with real enterprise customers.
- What's in it for you. NiCE Labs will publish reference architectures and benchmarking findings, release prototypes into its Agentic Portfolio on an accelerated cadence, and partner directly with customers and the broader ecosystem to translate cutting-edge AI research into measurable enterprise outcomes.
ORLANDO, Fla. — NiCE on June 9 announced NiCE Labs, a dedicated AI innovation lab designed to advance agentic customer experience through research, benchmarking and rapid prototyping. The lab was unveiled at NiCE World in Orlando at the Walt Disney World Dolphin Resort.
According to the company, NiCE Labs will serve as an incubation engine, pairing the vendor's AI expertise with direct customer and partner collaboration to tackle real-world enterprise CX challenges. The initiative targets the gap between what AI can do in research settings and what it reliably delivers inside complex enterprises.
The announcement came from Philipp Heltewig, chief AI officer at NiCE and co-founder of Cognigy, which NiCE acquired last September. Heltewig said on stage June 9 the reasoning capability of AI agents is growing exponentially — noting that leading models scored roughly 50% on the GPQA benchmark in 2024 and had climbed to 94% by early 2026 — and framed NiCE Labs as the mechanism for translating that raw capability into enterprise-grade CX performance.
"The pace of AI advancement is extraordinary, but raw AI capability and enterprise CX leadership are fundamentally different," Heltewig said in a statement. "NiCE Labs is how we close that gap. It brings together deep CX domain expertise, rigorous research and benchmarking discipline, and a rapid prototyping culture, all focused on one goal: ensuring that NiCE, and the enterprises we serve, are always operating at the leading edge of what agentic customer experience can be."
From the stage, Heltewig was direct about the constraints that make labs work like this necessary. Not every frontier model is the right fit for CX. In his keynote he cited Anthropic's Claude as an example, saying of the company's most advanced model: "You're not going to use that in CX — it's way too smart for what we need, and it's also way too slow." The point, he said, is model intelligence — identifying purpose fit for specific enterprise use cases, not chasing every new model release.
NiCE Labs: Three Pillars
Editor's note: NiCE Labs operates on three reinforcing pillars, each designed to move AI from research into enterprise-grade production.
| Pillar | What It Does | Enterprise Payoff |
|---|---|---|
| Research and Benchmarking | Conducts domain-specific AI research into how agents reason, learn and operate at enterprise scale; independently evaluates models, architectures and orchestration approaches against real-world CX scenarios | Evidence-based decisions about what enters the NiCE platform; principled model selection over vendor hype |
| Prototyping and Incubation | Builds AI-feature prototypes inside NiCE's Agentic Portfolio through a continuous experimentation cycle; incubates ideas that demonstrate clear enterprise value and feeds them into NiCE's product roadmap | Compresses time from promising concept to production-ready capability — in some cases from months to hours |
| AI Advocacy | Publishes research, reference architectures and benchmarking insights; engages academic institutions, model providers and the broader AI ecosystem | Makes NiCE Labs' AI thinking visible and useful beyond the lab; connects emerging AI with what is practical at enterprise scale |
In his keynote, Heltewig described how the prototyping pillar is already operating at speed.
"We've had cases where we discussed a certain feature that we could now enable with AI in the morning and by afternoon we had a prototype running in our labs," he said. He added that NiCE Labs is backed by a dedicated team of expert full-time employees with pods around the world working directly with strategic customers on real production problems — not a back-room research unit that surfaces findings occasionally.
"We don't want labs to be some backroom organization that is doing all of this, and once in a while you hear from it," Heltewig said from the NiCE World stage. "We want to engage with you, we want to engage with our customers, with our partners, and the wider ecosystem to build the future of AI and customer experience."
Related Article: NiCE Makes Its Move at NiCE World 2026: Agentic AI Is Now the Architecture
Table of Contents
The Gap NiCE Labs Is Built to Close
The business rationale for NiCE Labs maps directly to a pressure point NiCE has heard consistently from enterprise CX leaders: organizations are not struggling to find AI, they are struggling to make AI work reliably at production scale. NiCE describes the gap between what AI delivers in a research environment and what it performs inside a complex enterprise as where most organizations break down — and as the core problem NiCE Labs is purpose-built to solve.
That pressure was visible in the room at NiCE World.
Jack Roberts, senior global director of GMS Technology and Applications at Fabletics, told the NiCE World audience that his team learned early to resist the instinct to start with easy automation targets.
"Don't start with what's easy, start with something that matters," Roberts said. "Start with the friction points that are a genuine problem for your customers today." He added that failure in AI is not evidence of incompetence — "it's a sign of ambition" — a framing that aligns with the research-first, iterate-fast model NiCE Labs is structured around.
Mia Carraro, head of customer service excellence at Citi, offered a complementary perspective from the other side of the complexity argument. Carraro, who oversees CX strategy across 74 million customers and 65 million agent interactions annually, told the audience that complexity is not a reason to wait on AI — it is the reason you cannot.
"When you have a complex problem, when the stakes are high, when there's a need to get it right, complexity isn't the reason to wait on AI, it's the reason you can't," she said.
NiCE Labs is live as of the NiCE World announcement. Heltewig closed his keynote remarks on Labs by telling attendees that the first research, first prototypes and first results are already present at NiCE World this week.
"For years, the question has been, where is AI going?" Heltewig said. "And both at NiCE and at Cognigy, we've never been content to just watch. We intend to decide where it's going."
Agentic AI's Role in CX Transformation
Agentic AI is delivering measurable returns in enterprise CX as deployments move from experimental to operational.
Automation Rates & Outcomes
AI agents resolve up to 40% of inquiries across chat, email, voice and WhatsApp. Organizations implementing autonomous AI systems reported a 28% improvement in issue resolution time and a 19% increase in first-contact resolution rates. Omnichannel deployments cut operational costs by up to 30%.
Orchestration & Architecture
Unlike traditional chatbots, agentic systems reason, plan and execute multi-step tasks independently, ingesting multiple data streams and coordinating responses across enterprise platforms.
Governance & Human Workflow Integration
The operational model is shifting from human-assisted AI to AI-powered human workflows. Agents handle routine resolution while staff focus on governance, compliance and high-complexity interactions. Governed orchestration — constraining AI behavior through business logic with real-time monitoring — is emerging as the design standard.
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