# NiCE bets on AI, data and accountability > NiCE transforms contact centers with AI while legacy business buys time. - Title: NiCE bets on AI, data and accountability · SiliconANGLE - Summary: NiCE transforms contact centers with AI while legacy business buys time. NiCE uses AI and data to shift contact centers, with legacy business providing… - Keywords: nice, data, accountability, cxone, cognigy, genesys, five9, amazonconnect, aiagents, contactcenter, aiplatform, bets - Source: SiliconANGLE — https://siliconangle.com/2026/10/19/nice-bets-the-company-on-ai-data-and-accountability-and-the-legacy-business-buys-it-time - Author: Zeus Kerravala - Published: 2026-10-19T19:03:43+00:00 - Read time: 2 min - Topics: nice, ai, data, accountability, cxone, cognigy, genesys, five9, amazonconnect, aiagents, contactcenter, aiplatform ## NiCE shifts to AI platform NiCE Ltd. transformed from contact center-as-a-service to an AI platform after acquiring Cognigy. > Most acquisitions that companies make expand the portfolio and the capability ## Cognigy becomes core platform Cognigy now powers NiCE's conversational and agentic AI across all platforms. > Cognigy is now the underlying substrate for all of our conversational and agentic AI ## NiCE data drives AI value NiCE's interaction data and screen recordings fuel AI models with contextual insights. > They need NiCE data. They need our workloads. They need our interactions. They need our intents ## AI adoption grows rapidly Prospects with automated insights book nine times more AI than those without, API volume up 7.5x in two years. > Prospects that get an automated insights readout based on their own data book nine times more AI ## Personal agents disrupt contact centers AI agents don't sleep, don't give up, and don: t care about voice response trees. > You have bots talking to bots ## Accountability shifts to runtime Human and AI agents must be held to same standards during runtime, not design time. > The race we are in is not about the smartest agent ## Legacy business buys time NiCE's large installed base provides time to navigate AI transition while pure-play AI startups lack cushion. > That 52% year-over-year ARR is not from pilots and POCs ## AI revenue timing uncertain Enterprise AI adoption moves slowly, with 30-day time-to-value as key metric for deployment. > The bottleneck is deployment, which is why Heltewig’s 30-day time-to-value goal is so important ## Personal agents surge in Asia Hyatt reports AI agents already active in Asia with no historical baselines for measurement. > We don’t have any historical baselines ## Banking cautious about AI Citi says banking requires high accuracy, but attitudes are shifting toward AI adoption. > When you’re dealing with your money, there’s no tolerance for error ## Data as strategic asset Call recordings and screen recordings become raw material for AI agents, not compliance artifacts. > Call recordings, transcripts, quality scores and screen recordings were once compliance artifacts ## Agent traffic planning needed Enterprises must measure machine-generated traffic and verify agent identity before deployment. > Start by measuring how much inbound traffic is machine-generated ## Enforcement over instructions AI agents need permissions enforced in harness, not just prompt-based guardrails. > What you got to do is you got to put a padlock on a cookie jar ## Change management critical 70% of AI success depends on change management, not deployment. > Hyatt’s Meyer agreed, favoring a 70/30 split between change management and deployment ## Knowledge base accuracy vital AI agents can't work around outdated knowledge articles, requiring regular updates. > Human agents can work around inaccurate or outdated knowledge articles through training ## Resolution over containment Measuring intent resolution beats containment metrics for AI success. > Hyatt is moving toward measuring whether the customer’s original intent was resolved ## Key takeaway NiCE uses AI and data to shift contact centers, with legacy business providing transition time.