NiCE and Metrigy Research Finds Growing Openness to AI as Trust Shapes Customer Experience

NiCE (NASDAQ: NICE) released its Q3 2026 AI Consumer Experience Index, showing greater willingness to choose AI when issue resolution is guaranteed.

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28.8% of consumers would choose an AI agent when resolution is guaranteed, up 5.8 percentage points since Q1 2026

HOBOKEN, N.J.--(BUSINESS WIRE)-- NiCE (NASDAQ: NICE), a CX AI company, today released findings from the Q3 2026 AI Consumer Experience Index showing that consumers are more willing to choose AI agents when they know their issue will be resolved. Conducted by Metrigy, in partnership with NiCE, the new research highlights an opportunity for enterprises to earn customer trust and loyalty through AI that delivers accurate service and connects customers with a person when needed.

The quarterly study surveys 1,000 U.S. adults to measure how customer service experiences compare with expectations across eight dimensions, including AI satisfaction, AI trust and issue resolution. Scores track change from a Q1 2026 baseline of 100.

For the third consecutive quarter, trust ranked first among the factors consumers value most in interactions with businesses, selected by 41%, ahead of resolution at 35.4%. When resolution was guaranteed, 28.8% said they would choose an AI agent, up from 23% in Q1. Accuracy was the leading reason consumers chose a service channel, cited by 54.7%. Together, the findings point to a practical priority for CX leaders: make reliable outcomes the foundation of AI adoption.

“AI adoption is earned every time a customer gets the help they need,” said Arun Chandra, Chief Operating Officer, NiCE. “The next wave of adoption depends on AI agents that understand the customer, take action and carry the context forward when a person needs to step in. NiCE brings together NiCE Cognigy and NiCE CXone to help enterprises connect AI agents, workflows and human expertise, turning AI innovation into customer experiences that build trust.”

Key findings show where businesses can build on that opportunity:

• AI satisfaction and trust lead progress since Q1. The AI Satisfaction Index reached 109.4 and the AI Trust Index reached 106.9, gains of 9.4 and 6.9 points from the Q1 baseline. These were the largest improvements among the eight dimensions tracked.
• Consumers value AI and human expertise working together. The most popular service model combines AI and human agents, switching automatically based on complexity (39.4%). Another 37% prefer human-led service supported by AI, while 23.6% favor AI-led service with people available when needed.
• Choice is a service benefit consumers value. Nearly two-thirds of consumers (63.9%) would pay more for better service. The most-selected premium feature was the ability to choose between an AI agent and a human, cited by 37.0% of all respondents.
• Adults aged 25 to 34 show strong engagement with AI. Nearly three-quarters (74.4%) expect AI to improve customer service over the next two years, compared with 49.5% overall. Their usage reinforces that optimism: 39.7% reported using an AI text agent, compared with 26.2% of consumers overall.
• Retail shows the strongest AI improvement among the three sectors tracked. Its AI Index stood at 108.1, the largest gain against each sector’s own Q1 baseline across retail, financial services and healthcare. Retail’s broader CX Index remained below baseline, highlighting the opportunity to extend AI gains across the full service experience.

The findings also reinforce the importance of earning loyalty with each interaction. Consumers said they would tolerate an average of 2.78 poor experiences before leaving a company, assuming they could do so, down from 3.24 in Q1.

“Trust isn’t a soft metric anymore. It’s the one that decides whether a customer comes back,” said Robin Gareiss, CEO and principal analyst for AI and CX, Metrigy. “Consumers are more open to AI when they can count on a resolution, and they’re now sending personal AI agents to negotiate, escalate, and decide for them. Those agents will recommend the brands they can trust. The opportunity for businesses is to earn that trust consistently, with every customer and every agent, and make it easy to reach a person when the situation calls for one.”

NiCE helps enterprises put these priorities into practice through NiCE Cognigy and NiCE CXone, connecting AI agents with customer service workflows and employees across voice and digital channels. This approach enables businesses to expand AI adoption while maintaining continuity as customers move between automated service and human support.

The full Q3 2026 AI Consumer Experience Index, including consumer persona, industry and channel analysis, is available here.

Learn more about NiCE’s approach to AI-powered customer experience at nice.com.

About the AI Consumer Experience Index
The Metrigy AI Consumer Experience Index is a quarterly study of 1,000 demographically representative U.S. adults, produced independently by Metrigy in partnership with NiCE. Respondents rate their customer service experiences against their expectations on a five-point scale, and scores are calculated using a diffusion index method, with Q1 2026 set as the baseline of 100.0. The topline margin of error is approximately ±3.1 percentage points; subgroup estimates have greater uncertainty. The Q3 2026 wave was fielded August 10–14, 2026.

About Metrigy
Metrigy is an innovative research and advisory firm focusing on the rapidly changing areas of artificial intelligence, customer experience, and workplace collaboration, along with several related technologies, including knowledge management, security, and workforce engagement management. Metrigy conducts research with business leaders, consumers, and technology vendors. Our analysts deliver strategic guidance and informative content, backed by primary research metrics, indexes, and analysis, for technology providers and enterprise organizations.

About NiCE
NiCE (NASDAQ: NICE) is transforming the world with AI that puts people first. Our purpose-built AI-powered platforms automate engagements into proactive, safe, intelligent actions, empowering individuals and organizations to innovate and act, from interaction to resolution. Trusted by organizations throughout 150+ countries worldwide, NiCE’s platforms are widely adopted across industries connecting people, systems, and workflows to work smarter at scale, elevating performance across the organization, delivering proven measurable outcomes.

Trademark Note: NiCE and the NiCE logo are trademarks of NICE Ltd. All other marks are trademarks of their respective owners. For a full list of NICE's marks, please see: www.nice.com/nice-trademarks.

Forward-Looking Statements
This press release contains forward-looking statements as that term is defined in the Private Securities Litigation Reform Act of 1995. Such forward-looking statements, including the statements by Mr. Chandra, are based on the current beliefs, expectations and assumptions of the management of NICE Ltd. (the “Company”). In some cases, such forward-looking statements can be identified by terms such as “believe,” “expect,” “seek,” “may,” “will,” “intend,” “should,” “project,” “anticipate,” “plan,” “estimate,” or similar words. Forward-looking statements are subject to a number of risks and uncertainties that could cause the actual results or performance of the Company to differ materially from those described herein, including but not limited to the impact of changes in general economic and business conditions; competition; successful execution of the Company’s growth strategy; success and growth of the Company’s cloud Software-as-a-Service business; rapid changes in technology and market requirements; the implementation of AI capabilities in certain products and services, decline in demand for the Company's products; inability to timely develop and introduce new technologies, products and applications; difficulties in making additional acquisitions or difficulties or effectively integrating acquired operations; loss of market share; an inability to maintain certain marketing and distribution arrangements; the Company’s dependency on third-party cloud computing platform providers, hosting facilities and service partners; cyber security attacks or other security incidents; privacy concerns; changes in currency exchange rates and interest rates, the effects of additional tax liabilities resulting from our global operations, the effect of unexpected events or geo-political conditions, including those arising from political instability or armed conflict that may disrupt our business and the global economy; our ability to recruit and retain qualified personnel; the effect of newly enacted or modified laws, regulation or standards on the Company and our products and various other factors and uncertainties discussed in our filings with the U.S. Securities and Exchange Commission (the “SEC”). For a more detailed description of the risk factors and uncertainties affecting the company, refer to the Company's reports filed from time to time with the SEC, including the Company’s Annual Report on Form 20-F. The forward-looking statements contained in this press release are made as of the date of this press release, and the Company undertakes no obligation to update or revise them, except as required by law.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261109259865/en/

Corporate Media Contact
Christopher Irwin-Dudek, +1 201 561 4442, media@nice.com, ET

Investors
Ryan Gilligan, +1 551-417-2531, ir@nice.com, ET
Omri Arens, +972 3 763-0127, ir@nice.com, CET

Source: NiCE

Key Terms

diffusion index method technical

A diffusion index method is a way to summarize whether many individual indicators are generally rising or falling by counting how many components show improvement versus deterioration and converting that count into a single index. Common implementations give each component a score (for example +1 for up, 0 for unchanged, −1 for down), average those scores across the set and then rescale the result (often to a 0–100 or −1 to +1 range) so the index shows breadth: values above the midpoint indicate more components improving than worsening and values below indicate the opposite. The method measures direction and breadth, not the magnitude of changes in each component, so it tells you how widespread a trend is rather than how large the underlying changes are.

margin of error technical

The margin of error is a measure of how much the results of a survey or estimate might differ from the true value, due to random chance. It indicates the level of uncertainty in the data, helping investors understand how much confidence to place in the results. Think of it like the wiggle room around a guess—smaller margins mean more precise estimates.