An effective AI governance strategy for UC requires human review, bias mitigation, data transparency and security controls. CISO involvement is key to success and ROI.

The rapid growth of AI in unified communications and collaboration tools is challenging how organizations have traditionally addressed governance. As agentic AI, AI assistants and other capabilities become increasingly embedded into UC, organizations must adopt new governance strategies for data sovereignty controls, real time monitoring and other guardrails.

Generative AI (GenAI) security has become a key component of governance for communications and collaboration. Nearly 80% of organizations that currently have a governance plan or will have one in place by the end of 2026 named GenAI as the second-most included component, according to Metrigy’s Workplace Collaboration and Contact Center: 2026 study of 305 organizations. Other key AI-related components include data loss prevention and securing AI bots and agents.

As AI permeates every aspect of UC, organizations must ensure that their governance and compliance policies evolve to minimize risk. Key challenges for IT leaders include the following:

Key AI governance strategies for UC

Continue reading at techtarget.com.

Will artificial intelligence eliminate jobs and crush employee morale? This is a million-dollar question of the AI era, one with which many business leaders are grappling with as they flesh out their AI strategies. Those fearing a “Yes” answer will take encouragement from our new research study, AI for Organizational Best Practices: 2026-27, with 759 companies globally.

Today, 95.7% of companies using AI report that its overall impact on their organization is overwhelmingly positive. Rather than acting as a job-killer, AI serves as a powerful catalyst for growth, shifting the nature of work and driving employee engagement to new heights, we found.

AI Creates More Jobs Than It Eliminates

For two-thirds (66.3%) of organizations, AI has created more jobs than it has eliminated. While automation undeniably reduces the need for certain manual positions, it fuels considerable demand for new, specialized skill sets. Technical roles are experiencing significant growth, with companies increasing their hiring for AI agent UX designers, data scientists, prompt engineers, and security experts, for example. Forward-thinking business leaders also hire for emerging general roles, such as AI ethicists and quality assurance personnel.

Conversely, as AI takes over routine tasks, some companies report a decrease in roles like administrative assistants, receptionists, frontline workers, and contact center agents. However, this shift doesn’t signify a shrinking workforce. Instead, it represents an evolution in how human talent delivers value to the enterprise. Top-performing companies—the research study’s “Success Group,” determined based on measured improvements from AI use—are even more likely to experience job growth, with 78.1% reporting net job creation due to AI.

Redesigning Work and Reimagining the Work Week

Successful companies do more than just use AI to automate existing workflows; they fundamentally redesign how work gets done. By intentionally redesigning work structures around AI capabilities vs. simply using AI to automate workflows, they’ve seen a 25.9% bigger drop in future costs, a 13.0% better increase in revenue, a 14.0% bigger drop in existing costs, and a 4.4% higher boost in CSAT, our study shows.

On average, the expectation is that AI can automate between 11% and 30% of repetitive tasks, freeing employees to focus on strategic, high-impact projects. The resulting efficiency boost could spark an interesting shift in the traditional work schedule. Slightly more than 42% of organizations believe AI will eventually reduce the work week. The remaining 57.8% expect the work week to stay the same length, but they anticipate that workers will achieve significantly more during those hours. Top-performing companies remain especially bullish, with nearly half predicting a shorter work week on the horizon.

Supercharging Employee Engagement and Efficiency

Employee efficiency is the the top metric companies use to determine AI success, and the results validate the investment. Using measures such as effective use of AI to help improve a task or process, improved quality of work done, and time savings on the same task or process, nearly 77% of companies report having realized an efficiency increase—and by no small measure. On average, businesses report a 22% gain in efficiency after deploying AI tools.

Employee morale benefits, as well. Among organizations measuring AI’s impact on staff, nearly 70% see improved employee satisfaction ratings, averaging a remarkable 30.1% increase. Companies track these engagement improvements through employee performance metrics, satisfaction surveys, and turnover rates. The message is clear: When employees use AI to eliminate the frustrating, manual parts of their jobs, they tend to feel more satisfied, empowered, and loyal to their organizations.

Leading the Change

To reap these benefits, leaders must prioritize formal training and comprehensive change management. Today, about half of businesses formally introduce and train their staff on new AI capabilities. Furthermore, 80% of organizations actively allocate specific staff and budgets for AI change management. Successful deployments rely on cross-functional teamwork, bringing together the CIO/CTO, human resources executives, and business unit leaders to guide employees through the transition.

AI does not replace human ingenuity; it amplifies it. For IT and business leaders, the mandate is clear: Embrace AI not just as a cost-saving tool, but as a strategic engine for job creation, workflow redesign, and unprecedented employee engagement.

In a market saturated with lofty promises about AI and next-generation customer experience, separating marketing hype from genuine business impact can be difficult to do. At Metrigy, we cut through the noise by going directly to the people who buy and use these technologies.

For our global Customer Experience MetriCast 2026 buyer-side market research study, we gathered insights from 1,437 CX and IT leaders across 10 countries. As part of the study, we asked these leaders to provide two sets of information we use in determining which providers earn recognition in our annual CX MetriStar Award program:

In this year’s CX MetriStar program, we recognized 74 distinct award winners across nine critical technology categories: agent assist, AI agents, contact center as a service (CCaaS), communications platform as a service (CPaaS), customer relationship management (CRM), interaction analytics, knowledge management, voice of the customer (VoC), and workforce engagement management (WEM).

We break down our recognitions into three honors:

Here are Metrigy’s 2026 MetriStar Top Provider Award winners, companies that excelled in both sentiment and business success (listed alphabetically):

Want to hear more about which providers are moving the needle on CSAT, employee efficiency, and cutting costs? Tune into our latest MetriSight podcast episode on our website, YouTube channel, or your favorite podcast app for a deep dive. You’ll also discover noteworthy trends we found in the MetriStar analysis!

eHealth’s Alice voice agent handled calls during the peak season for healthcare insurance enrollment and garnered a majority of “exceptional” satisfaction ratings.

In 2026, the phone remains the most vital—and most volatile—customer touchpoint, with every ring being a moment of truth for customer experience. For CX leaders grappling with not just maintaining but excelling at phone interactions, Metrigy has some good news from its recently published Q1 2026 Consumer CX Index, based on a study of 1,000 consumers in North America. That is: Most consumers today will give AI voice agents a chance.

Specifically, 59.1% of consumers studied said they’re willing to give an AI voice agent some time to solve their issue. There is a caveat, though. They’ll only do so if they know that escalating to a human agent is in the offing. Where do the other callers stand on the AI voice question? About 30% skip the “give it a try” step and jump immediately to the human option, and 11% hang up the moment they realize they aren’t speaking to a person.

Continue reading at nojitter.com.

As your organization explores how best to use generative and autonomous AI for customer service, it has no doubt quickly realized that keeping these advanced agents safe requires specialized oversight. The market for CX assurance has responded with a diverse range of solutions to readiness-test AI agents and observe them over time. But with so many options, where should a CX or IT leader start?

There’s no one-size-fits-all approach to safely deploying AI agents. To help make sense of the market, consider these four primary categories within the CX ecosystem:

1. Traditional CX assurance vendors – Evolving from legacy interactive voice response (IVR) testing, these vendors offer platform-agnostic tools that validate a company’s entire communications stack—from carrier-grade network performance to the final AI response.

2. AI agent providers – This category includes pure-play AI agent platforms as well as traditional CX giants that have embedded AI agents into their existing tech stacks.

3. AI-native testing and observability startups – Built specifically for the generative AI era, these startups act as an agnostic middleware layer that connects via APIs to any custom or walled-garden agent.

4. Conversation intelligence providers – Focused heavily on post-deployment assurance, these vendors analyze 100% of interactions to monitor how AI agents perform in the wild compared to their human counterparts.

As your organization’s AI ecosystem grows in complexity, you may find that relying on a single tool leaves dangerous blind spots in your customer journeys. Here, a  multi-vendor strategy is often the smartest path forward. For instance, you might use a native AI agent platform for daily prompt building, but layer a traditional testing vendor over the top for independent, outside-in validation. Alternatively, a voice-centric operation might pair a legacy voice testing specialist with an AI-native startup to handle complex text reasoning.

Choosing the right partner depends entirely on your existing tech stack, risk tolerance, and in-house engineering capabilities. To dive deeper into these four categories and explore detailed vendor profiles and evaluation criteria, check out the CX Assurance for AI-Powered Contact Centers market overview report.

In this episode, Mark Rohan, co-founder and COO of CX assurance company Klearcom, joins us for a discussion on the real-world challenges of using AI voice agents… and how to get ahead of them, plus measure success.

Higher education leaders are asking a critical question: How do we support students better without adding more strain to our teams?

Students expect immediate, personalized support. At the same time, higher education teams face budget pressure, staffing shortages, and increasing accountability for enrollment and retention outcomes.

New Metrigy research reveals how leading institutions are using secure AI and other customer experience (CX) strategies to transform the student journey. By orchestrating intelligent engagement across every department, institutions are improving measurable outcomes and reducing operational strain.

The impact is significant: 82% report improved service quality and over 85% are achieving major gains in student satisfaction.

Start creating seamless student experiences while giving staff the clarity, guidance, and governance they need to perform at their best.

Start solving your top challenges:

Improve admissions. Protect revenue. Ensure student success.

Download and read this issue paper at nice.com.

AI agents can contact customers, make decisions, act autonomously and close a sale with little or no human involvement. They can also renew orders and attempt upsells.

Remember the days when outbound sales teams were an army of people manually hammering away at phone keypads just to reach a busy signal or listen to the phone ring incessantly?

Businesses moved from that era of raw human labor into the world of predictive dialers, where math and algorithms took over to keep agents talking constantly. But even then, the effort was aimed at bringing a human agent to the customer.

Today, businesses are in the middle of the most significant shift yet — a move from simply connecting callers to having intelligent systems that can converse, decide and close a sale. Welcome to the era of agentic AI.

AI agents become outbound sales reps

Continue reading at techtarget.com.

Metrigy recently released our inaugural quarterly indexes for tracking how people feel about customer service and AI. Project leads Matt Craig, our senior director of product development, and Layne Haaksma, senior research analyst, walk us through the hows and whys of these indexes, and discuss the most interesting findings.

Artificial intelligence (AI) is no longer a technology trend on the horizon. It’s embedded in the tools people use at work, the apps on their phones, and the news cycle that greets them every morning. And yet, for all the coverage and conversation around AI, one question has remained surprisingly hard to answer with real data: How do Americans actually feel about it?
That’s exactly what we set out to find out.

Why We Built the AI Sentiment Index

At Metrigy, we’ve spent years researching how technology reshapes businesses and the people who run them. As AI has accelerated from an emerging capability to an operational reality, we kept seeing the same gap: plenty of vendor announcements, a plethora of headlines, but not enough, longitudinal insight into how everyday Americans (workers, professionals, retirees, students) are experiencing and thinking about AI.

So, we built the AI Sentiment Index. The index is based a quarterly tracking study designed to capture the evolving relationship between AI and human experience, across demographic groups, over time.

How the Index Works

The AI Sentiment Index is a longitudinal framework, which means it’s built to track change, not just capture a single snapshot. Each quarter, we survey a representative sample of 1,000 U.S. adults, with distribution across regions, age groups, income levels, and education backgrounds to ensure the data holds up.

The index centers on six questions regarding AI’s impact on personal life, society, and the economy. Respondents evaluate the current state of these areas and predict how they will evolve over the next one to two years. We use a diffusion index methodology, a standard approach in economic and sentiment tracking that goes beyond simple averages. Rather than just reporting how many people feel positive or negative, we weight the intensity of those feelings, giving extra emphasis when a large concentration of respondents feels strongly in either direction.

The result is both a current sentiment score and a forward-looking sentiment score, which we average into the overall AI Sentiment Index rating. The Q1 2026 data serves as our baseline, the starting point against which every future quarter will be measured. As we collect more waves of data, we’ll be able to identify meaningful shifts in sentiment and connect them to what’s happening in the broader AI landscape.

What the First Wave Tells Us

Our inaugural report tells a mixed story. Sentiment toward AI is broadly positive, yet that consensus is cracking. Demographic, economic, and generational divides are widening in ways that are hard to ignore.
People who use AI regularly tend to find it genuinely useful, often reporting that it helps them learn, get more done, and accomplish things they couldn’t previously have undertaken. At the same time, a significant portion of the population harbors real concerns—about privacy, job security, the pace of development, and whether they can trust what AI produces. The emotions people associate with AI run the full spectrum, from excitement and hope to skepticism and fear, and no single feeling dominates.
Perhaps most notably, the benefits of AI are not being felt equally. Higher earners, more educated workers, and mid-career professionals are experiencing AI as a productivity multiplier. Younger workers entering the job market and lower-income individuals are more likely to see it as a threat. These divides aren’t incidental. They reflect structural realities about who AI is currently built for and who bears its risks.

Shadow AI—i.e., the use of AI tools at work without employer knowledge or approval—is widespread and raising real cybersecurity concerns that organizations can’t afford to ignore.
These are exactly the kinds of signals that business and IT leaders need on their radar.

How the Index Will Evolve

This first report sets the baseline. Beginning with Q2 2026, we’ll compare each new wave of data against it, tracking directional shifts in how Americans feel as new AI capabilities emerge, regulations take shape, and real-world impacts (both positive and negative) become more visible.
While we’ll add varying questions as the AI market evolves, the six core index questions will remain consistent throughout 2026 at minimum. That consistency is what makes longitudinal tracking meaningful.

Read the Report

The AI Sentiment Index overview report is available now and free to read. It covers the key findings from our inaugural wave, including the methodology behind the index, how we calculated the scores, and what the data reveals across demographics.

Metrigy clients have access to the full detailed report, which goes deeper into the cross-tabulations, demographic breakdowns, and analysis behind the headline findings.

If you’re not yet a client and want access to the full data, reach out to our team. We’d love to talk.

Metrigy is an innovative research and advisory firm focused on AI, customer experience, and workplace collaboration. Learn more at metrigy.com.