AI is rapidly changing not only how companies use technology, but also how software vendors deliver value. In this episode with chat with Pravel about how Zoho is positioning itself to enable its customers to leverage AI for measurable return on investment, the opportunities for specific industries, and how the software as a service market is evolving to enable citizen development. We also talk about the role of partners, and how best to support regional needs for data sovereignty.

The tone of recent announcements and initiatives reflect a not-so-subtle shift in how buyers view AI, and they want to understand its real world benefits.

There is no doubt that AI has transformed the workplace collaboration and customer experience landscape. AI’s impact was on full display at the recent Enterprise Connect conference in Las Vegas where advancements in AI were at the forefront of just about every vendor’s story. Even vendors such as Google and Microsoft, who were notably absent, chose to use the week of Enterprise Connect to make AI announcements focused on their office productivity suites.

However, the tone of recent announcements and initiatives reflect a not-so-subtle shift in how buyers view AI: They are less enthralled with AI’s hype, but instead want to understand its real-world benefits.

The State of AI Adoption

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Technology evolves at breakneck speed, but human nature takes a little longer to catch up. We all know this intuitively, but here at Metrigy, we wanted to back up our instincts with hard data. That’s why we’re thrilled to introduce two new foundational tools business leaders can use to understand everyday people’s latest state of mind: our quarterly Consumer CX Index and AI Sentiment Index. These indexes provide a much-needed pulse check on how consumers are navigating the blurring lines between high-tech efficiency and human connection.

The Customer Experience Balancing Act

Let’s start with the Q1 2026 Consumer CX Index, which establishes a baseline customer experience score of 123.8 (a composite built on eight sub-indexes). Overall, consumers feel optimistic about their interactions with brands today. Businesses resolve issues effectively, and customers generally feel valued after their interactions. In fact, our highest-scoring sub-index is the Relationship Index at 137.5, which evaluates how valued customers feel.

However, a more complex story emerges regarding artificial intelligence (AI). Another of the eight sub-indexes, the AI Trust Index, measures the reliability of AI-powered customer service. It is the lowest of all, at 109.8. Consumers still overwhelmingly prefer human agents—84.9% of them, to be exact. Furthermore, even when guaranteed that an AI agent could fix their problem, 77.0% still want a human being. We call this the human-versus-AI disconnect. Of course, you shouldn’t dismiss AI completely. Consumer preference for using AI agents has grown 29.3% since 2023, and users report surprisingly positive experiences when dealing with AI video agents.

Here are a few pertinent takeaways from the CX Consumer Index:

• The three-strikes rule – Patience is wearing thin. On average, it takes just 3.2 bad experiences before a consumer abandons a brand completely. High-income earners and seniors are even less forgiving, churning after roughly 2.5 bad interactions.
• Trust over speed – Forget the race to resolve tickets in record time. A resounding 41.4% of consumers rank trust as the most important element of customer service, while only 10.2% prioritize speed.
• Retail sets the gold standard – The retail sector leads the pack in overall CX. Finance and healthcare hold steady, though they struggle with wait times, while government agencies sit firmly at the bottom of the list.
• Proactive outreach wins – Consumers love when you anticipate their needs. The perceived value of proactive engagement skyrocketed 17.5 percentage points since late 2025. Almost half of consumers find fraud alerts, post-interaction follow-ups, and delivery updates genuinely helpful.

The AI Divide in Everyday Life

Now, let’s pivot to the broader technological landscape with our Q1 2026 AI Sentiment Index. Launching with a baseline score of 124.0, this index tracks how AI impacts consumers personally, economically, and socially by comparing positive and negative sentiments. We found a deeply fragmented landscape. People love the productivity boosts and cognitive enhancements, but they worry heavily about privacy, job security, and factual confusion.

Key findings from the AI Sentiment Index include:

• The demographic divide – Older Millennials, specifically those aged 35 to 44, have embraced AI as power users, with 42.5% reporting that AI makes them much better off. Meanwhile, the 65-and-older crowd largely shrugs it off, with 56.0% stating the technology has no effect on their lives at all—if they’ve even used it.
• Shadow AI in the workplace – Employees aren’t waiting for official corporate policy. A surprising 33.9% of users admit to using AI tools at work without employer consent. Experienced managers looking to increase team output are likely champions of this underground adoption.
• The verification gap – Here’s a statistic that should keep IT leaders awake at night. Among users generating AI content, 41.1% never or only occasionally check the output for accuracy. This creates a massive risk for confident falsehoods slipping into professional communications and production code.
• Future polarization – Looking a decade ahead, respondents are evenly split. About a third expect continuous growth and opportunity, while another 34.8% brace for widespread problems and instability. Younger workers, entering a volatile job market, feel particularly pessimistic about their career prospects.

The Bottom Line

What do these two new indexes tell us? The market is in the midst of a massive transition. Customers and employees are eager to use AI to bridge skill gaps and solve problems, but they refuse to sacrifice transparency, accuracy, and human empathy. Successful organizations in 2026 will balance the transactional efficiency of AI with the emotional intelligence and accessibility of live agents.

Do you want to explore the data behind these trends? We invite you to dive into the full Metrigy studies to uncover comprehensive demographic breakdowns and strategic guidance. You can find the full detailed reports and presentation here: CX Consumer Index and  AI Sentiment Index. Let’s build a future where technology amplifies our human connections!

Comprehensive study reveals population perspectives on the personal, societal, and economic impacts of AI as the technology becomes a mainstay in daily life

MARCH 31, 2026 – Metrigy has released its inaugural AI Sentiment Index – 1Q 2026, exploring the complex relationship between the public and rapidly evolving AI technologies. Although many users feel AI has already made them “better off,” there is a significant fracture in expectations for the next decade, with nearly 35% of respondents anticipating a period of widespread instability and problems.

Sentiment around AI is defined by a generational divide. The 35-44 age group has emerged as the technology’s “power users”—with 65.5% using these tools daily or weekly. Meanwhile the 65+ demographic remains largely untouched, with more than half reporting that the technology has had no effect on their lives. 

Furthermore, almost half of the total population views generative AI as a fundamental shift akin to the invention of the smartphone, yet nearly 48% feel the current pace of development is moving too fast.

“AI is reaching its ‘smartphone moment,’ but the public is still deciding if that’s a promise or a threat,” says Matt Craig, Sr. Director of Product Marketing at Metrigy. “While 35-to-44-year-olds are optimistic and diving in as daily power users, the youngest cohort is cautiously fearing a decade of instability.”

Artificial Intelligence Sentiment Index – 1Q 2026 research study explores how various demographics are integrating AI into their lives and careers. Key coverage areas include:

• Generational Sentiment: Age is highly correlated with adoption, with the youngest cohort showing more long-term pessimism, those in their 30s and 40s extremely optimistic, and older generations expressing the highest levels of skepticism.
• Emotional Complexity: There is no single dominant emotion toward AI; instead, the public is balanced between skepticism, curiosity, and hope, with a direct correlation between higher education levels and positive outlooks. Gender, however, plays a role here: Women index higher on skepticism and fear and men display higher levels of excitement and hope.
• Primary Use Cases: Consumers are primarily utilizing AI for research and personal tasks, though a significant portion now uses it for creative and professional work.
• Workplace Adoption: A significant gap exists in corporate oversight, as more than 60% of employees using AI at work began doing so on their own, with only 28% doing so with employer consent. Meanwhile, job security is a significant point of contention

“AI is changing our lives almost daily, so it’s vital to track how consumer sentiment is changing over time,” says Metrigy CEO Robin Gareiss. “Understanding people’s perspectives on how they use AI, what they fear or like about it, how it affects them emotionally, and what it means for their livelihood are paramount to any business, educational institution, or government agency moving forward–and this research will provide that crucial information.”

The study involves a representative sampling of 1,000 U.S.-based consumers and will be conducted quarterly. Now that the baseline index is set, subsequent quarters will identify areas that are changing and in which direction.

The full Artificial Intelligence Sentiment Index – 1Q 2026 release is available now. To download a copy, please visit www.metrigy.com.

Many moons ago in grade school, I learned about the five senses. To make a point about the importance of each of the senses, the teacher made us select one sense we thought we could live without. As we went around the room, not a single student selected eyesight.

It’s just a small indicator that even as young children, we inherently feel the value of seeing a group of friends at the beach over the taste of a freshly baked cookie or the feeling of a tight hug. Fast-forward several decades, and video communications has amplified the value of vision. Today’s younger generations cannot fathom only being able to communicate with a friend or family member through snail mail or an occasional phone call.

Yet, when it comes to interactions with businesses, visual communication is not readily available: 48% of companies use video, but nearly half of those only use it when an agent permits the escalation, according to Metrigy’s Customer Experience Optimization 2025-26 global study of 656 companies. Meanwhile, more than 90% of consumers want to visually engage with businesses, especially when it comes to troubleshooting products, conducting consultative calls, online shopping, and orientations/training, according to Metrigy’s CX Optimization – Consumer Views 2024-25 research study of 503 North American consumers. 

Not every type of call requires a visual interaction, but voice and text only go so far. Many companies, and their customers, would benefit from one- or two-way video calls. For example, 71% want to use video or video with screen sharing when troubleshooting new products, while 73% want the same for consultative calls with physicians, lawyers, or financial advisors. 

The trouble is, 40% of consumers say companies don’t make it easy to communicate over video and 29% say they would like to communicate over video but no companies they have interacted with offer it. Not using video is a wasted opportunity. Those that do provide visual capabilities are seeing huge improvements to their business metrics: 74% saw a 41% improvement in customer satisfaction, 67% increased resolution speed by 40%, and 43% increased sales by 33%.

Enter AI and Augmented Reality

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One AI enterprise lead shares why his team is taking the long view on agent assist and its ultimate value

Here’s a question I think worth pondering for customer experience (CX) leaders developing their artificial intelligence (AI) strategies and technology roadmaps: Is agent assist a permanent fixture of the modern contact center desktop, or simply a stopgap on the way to full automation?

It’s a question that’s been in my own thoughts over the last few weeks, initially landed there during a customer presentation at the NiCE Cognigy Nexus 2026 conference that took place March 11-12 in Munich. For global financial services firm Allianz Group, agent assist is a bridge technology that, while serving a useful immediate purpose, is perhaps even more valuable for its role in maturing the AI ecosystem. Such is the view relayed by Benno Schindler, conversational AI tribe lead at the company’s IT and digital arm, Allianz Technology, during his presentation, Allianz: Mastering Agentic AI and Building High-Impact Agents.

The Bridge to Agentic AI

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With all the technologies available to improve customer experience (CX), enterprise IT/CX leaders often ask where to invest their limited budgets. Hands down for me, it’s conversation analytics – the data and insights derived from customer interactions. Companies can invest in agent assist or AI self-service agents, for example, but how do they know if what they’re doing is working? How do they know what to automate? How do they know what changes to make for continuous improvement? 

When AI analyzes every customer interaction, they can answer all those questions and more. Analytics are the cornerstone for improvements in both CX and the technology that supports it. Today, 49.8% of companies use conversation analytics, but the value of the data can’t be understated: More than 90% say the data derived from conversation analytics is either the most valuable or among the most valuable data available in the company, according to Metrigy’s AI for Business Success 2025-26 global study of 1,104 companies.

As this technology continues to rise in value, I’m reminded of an incredible session I recently attended at the Cresta Wave conference. Barry Chester, Cresta’s Head of Airlines, interviewed Rachel Walker, Managing Director of Customer Support and Advocy, and Brandy Maxwell, Senior Manager of Customer Insights Policy Execution, both with United Airlines.

United Airlines’ Path to Success 

United Airlines is well into its deployment of Cresta’s Conversation Intelligence products, including Insights and AI Analyst, along with other Cresta offerings. United has even stood up an “Insights to Action” team that leverages the findings. (This, by the way, is a stellar move. I see far too many companies gathering insights and customer feedback and failing to act upon them.)

Getting to the point they’re at now was a progression, starting from paper tallies showing what they thought were their top drivers when customers called into the contact centers, progressing to surveys asking customers for the reasons for their calls. United then added more automation by looking at keywords and breaking down categories, but the tool in use at the time was inflexible, non-real-time, and lacked a good interface.

Once they started using Cresta, all of that changed. Easy-to-use interface? Check. Changes in the moment? No problem. Real-time analysis of what was happening in the moment? Done. The changes were so significant, Maxwell refers to Cresta as United’s “game changer.” The Insights to Action team started operationalizing the information and developing processes to leverage it.

The team worked with digital partners, communications teams, bot and automation teams, and others to make changes based on this data. Insights to Action would suggest changes (or brainstorm together with other departments to develop solutions), show the return-on-investment (ROI) for making the change, and document the results after the changes took place. “We put an ROI against it,” Walker says. “We can go back and say, ‘You making this change did drive the cost savings.’ It motivated the teams. Real data, real volumes, real cost savings.”

For example, customers may have been calling for clarification on communications United sent to them. By changing the communications moving forward to clarify the content, fewer customers would have to call. The data guided them to identify an issue that could be resolved fairly easily. 

“It’s an opportunity to establish the contact center as an insights value driver for the business,” Chester says. “We can actually inform our cross-functional departments. Your contact center is the front door to the business; being able to provide the intelligence back to the organization to help drive change, to improve the overall customer experience is a massive opportunity.”

Metrigy’s research backs this up, with 83.7% of IT/CX leaders saying that insights data should be included in dashboards for companywide decision-making. 

Maxwell highlights three core examples of where United uses the insights gleaned from Cresta’s products and turns them into action:

• Call deflection – United has a fare type that doesn’t allow customers to make changes to their travel plans unless they upgrade to a different fare, and they must pay to upgrade. Even though they could upgrade to the new fare type and make their travel changes in self-service, they still were calling into the contact center to talk to someone. 

Cresta Insights uncovered why: United was asking customers to pay to upgrade before they knew if they could make the travel change they wanted. So, United redesigned the self-service experience, enabling customers to see if they could get the change that they wanted first, and then pay for the upgraded fare at the end of the interaction. 

The results? An immediate 50% reduction in live interactions for that contact type, saving the company millions of dollars a year, along with improved customer satisfaction.

• Customer feedback – United’s customers could see the upgrade waitlist about 72 hours in advance of their flight, but they would call prior to that to see how the list was looking. The agents had, and would freely give, the information to customers. But customers simply wanted to see the information digitally. In response to the feedback, the company recently introduced an enhancement to show the upgrade waitlist 30 days prior to a flight, freeing agents to handle more complex issues
• In-the-moment scenario – Maxwell pointed to an incident last year with an air travel disruption. United wanted to validate that safety was the main issue of concern with its own customers. But analytics showed them customers were more concerned about rebooking. Data from Insights and AI Analyst provided the information to know what customers were talking about, which helped both customers and agents.

“With AI Analyst…it’s not just anecdotal, it’s real data. We can ask questions back and forth. Why it’s happening and what customers are contacting us about. Also, we can see how our front line is doing,” Walker says. “Our agents are so happy that we’re getting better information out to them much faster.”

Moving forward, United wants to use the products to help with day-to-day work because they must do more with the same size team. Cresta’s Automation Discovery, for example, can help them understand how to automate more functions.

CVS Finds Value in AI + Human to Improve Healthcare

In another session at the event, Srikant Narasimhan, VP of enterprise customer experience and insights, CVS Health (which includes Aetna, Caremark, CVS Pharmacy, Minute Clinic, and more brands), described how AI has found a home in the company’s CX strategy. Though many think AI is coming for their jobs, Narasimham says CVS views AI as complementary with humans.

“Human plus AI is better than human without AI,” he says. “AI takes the stupid out of work. So, it’s more of a capability to free up the productivity and the mind space for teams to deliver a better experience.” 

The front-line employees want to help patients and impact their healthcare, and when they realize how AI will make it easier to deliver a better outcome for the patient or their family member, the adoption flows from that. In fact, Metrigy’s study shows 71.9% of companies see a 31.1% improvement in CSAT/PSAT when they use agent assist.

One of the first applications of AI for CVS was summarization, which resulted in a fast return through reducing after-call work time. Illustrating those wins to their leadership enabled CVS to obtain buy-in for other capabilities, including predictive CSAT.

CVS leverages Cresta’s predictive CSAT on every call, giving the company a more complete picture of      the true customer sentiment. Previously, CVS relied on customer surveys, where they received a 5% response rate. 

“Now, we’ve scored 100% of our calls. So, at an agent level, we understand performance, not just from their perspective but from the consumers’ perspective,” Narasimhan says. 

Predictive CSAT models are running at an 85% to 95% accuracy rate, according to Metrigy’s research.

By tracking CSAT in this way, CVS’ time to insight is accelerated. CX leaders can see when sentiment is declining and get in front of it quickly, being more proactive with communication and explaining alternatives to customers. In the world of customer surveys, it would take a few weeks to get enough information to analyze—and even then, it was only from a fraction of interactions.

Moving forward, CVS plans to work with Cresta on a scoring model to rate all calls on customer experience and agent quality. One benefit from that is to improve coaching. What’s more, they will use analytics to understand why customers are not using self-service options for certain functions, such as changing mailing addresses. 

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Integrating AI technologies into customer experience workflows can cut costs. But focusing solely on cost reduction misses opportunities to accelerate revenue.For many business leaders, cost cutting is the key value of AI for customer experience (CX) transformations. But the most successful companies are not deploying AI simply to cut costs. Instead, they are adopting clear economic models that align AI investments with measurable business success metrics — ranging from revenue growth to improved employee retention.Based on Metrigy’s research from multiple reports, five economic models are emerging as the primary ways organizations generate value from AI in CX.

1. Cost efficiency.
2. Revenue acceleration.
3. Risk mitigation.
4. CX improvement.
5. Employee stability.

Underscoring these models is access to interaction analytics data, which provides the insights to know whether the models are working as intended. Understanding these models and backing them with interaction data helps organizations build stronger business cases for AI investments and ensures they track the right metrics to measure success.

5 economic models for AI in CX

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Knowledge management is front and center for companies moving toward AI enablement of CX. This session provides a look at what knowledge management strategies are paving the way for AI-enabled customer experiences that deliver measurable business impact, from determining a knowledge focus, solidifying data sources, tapping into the power of generative AI-knowledge search, and beyond.

Knowledge Management Expert Insights Series, Ep.1 – Strategies & Best Practices for CX Knowledge Management Today

Presented by: Beth Schultz, VP of Research and Principal Analyst

Original Air Date: March 24, 2026

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These essential tips assure AI agents function properly before and after they hit production.

The excitement surrounding generative AI in customer experience (CX) is undeniable. From ultra-responsive chatbots to autonomous “agentic” systems that can rebook flights or process refunds, the potential for scale and efficiency is transformative. However, as we move from scripted, deterministic logic to probabilistic large language models (LLMs), the traditional testing playbook isn’t enough any longer.

In a world where an AI agent might provide a different (yet correct) answer to the same prompt every time, or suddenly go haywire, how do you ensure it stays on brand, replies within the scope of company policy, and otherwise keeps out of trouble? As Metrigy has found in its CX research, new risks associated with the use of AI agents are driving many companies to adopt tools and processes aimed at assuring AI agents are performing as expected prior to deployment and that they keep doing so once implemented.

Drawing from insights shared in conversations with a host of industry experts, here are seven essential tips for assuring AI agents function properly before and after they hit production.

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