In this exclusive interview, we sit down with Martin Taylor, deputy CEO and co-founder of Content Guru, to explore how CX leaders can successfully navigate the challenges of data ownership while embracing the transformational potential of AI and automation. 

Watch the Full Interview on Youtube 

The Data Explosion: From Calls to Connected Everything 

The scale of data generation in modern contact centers is staggering. “We’re creating billions of records a year just as Content Guru, as is everybody else,” Taylor explains in the interview. “So you’ve got increasingly information not just from calls anymore but from all the digital channels.” 

But it’s the emergence of what Taylor calls the “digital customer” that’s truly transforming the landscape. With predictions of 39 billion Internet of Things devices by 2030, each representing a human in the eyes of regulators, the volume and variety of personal data flowing through CX environments is exploding exponentially. 

” The UK Information Commissioner’s Office considers data generated by IoT devices  – be it a movement or somebody’s temperature detected by a smart health device or a smart fridge  reporting it is  empty – as a piece of personal data,” Taylor notes. 

The Jurisdiction Maze: Where Geography Meets Governance 

One of the most complex challenges facing global organizations is navigating the intersection of geography and regulation. As Taylor explains, “Data is being produced at large volume all over the world, every day, every second. So how that is generated and the rules under which it is being generated vary by geography and by market segment.” 

The implications go far beyond GDPR. While the regulation establishes that “the data subject is ultimately the owner of the data,” the practical responsibilities for processors and vendors create a complex web of obligations that vary by jurisdiction and sector. 

“The EU want it to take place within the EU. The UK want it to take place within the UK, the US in the US,” Taylor explains. “And then if you go to the actual sectors themselves like medical or financial, they’ve got a load of rules of their own and those are done per country as well.” 

Breaking Down Silos: The New Collaborative Imperative 

The complexity of modern data governance is forcing unprecedented collaboration between traditionally separate functions. Taylor shares a real-time example from his own organization: “An example from here today is about something that’s come to my desk  about live sentiment analysis and its legality within an EU AI Act context.” 

This seemingly straightforward CX enhancement required input from legal, product, and information security teams – a pattern that’s becoming the norm rather than the exception. “Those sorts of conversations are happening throughout all levels of the value chain from the provider of a service right through to the vendor,” Taylor observes. 

The Death of “Public Cloud” Assumptions 

Perhaps one of the most significant shifts in thinking has been the abandonment of the idea that being “in the cloud” absolves organizations of data responsibility. 

“I think we’ve seen the death of this idea of there being such a thing as a public cloud,” Taylor states emphatically. “Everyone can see that clouds belong to organizations now and that they reside in specific jurisdictions.” 

The AWS outage in Virginia that affected organizations worldwide serves as a stark reminder of this reality. Many affected companies didn’t even know they had connections to that specific location, highlighting the importance of understanding not just whose cloud you’re using, but where it physically resides and under what jurisdictions it operates. 

Balancing Innovation with Responsibility 

As organizations rush to embrace AI and automation, the challenge becomes maintaining innovation velocity while ensuring responsible data handling. Taylor uses an oil refinery analogy to explain this balance: “I think of raw data as like crude oil and then the refining process, fractional distillation. You’re looking now for that kind of high quality racing fuel  that we use to feed the AI.” 

Not every implementation needs to become more complex, but those involving AI require higher-quality data and more sophisticated governance. “In some cases, it’s AI, it needs that richer fuel. You can’t feed it the heating oil, because it won’t work,” Taylor explains. 

Looking Ahead: Preparing for 2026 and Beyond 

As we look toward the year ahead, Taylor predicts continued growth in both opportunity and complexity. “We’ve all heard  a lot about agentic AI  during 2025. I think 2026 is when it starts to get applied,” he notes, while emphasizing that this won’t mean wholesale replacement of human agents. 

Instead, organizations should prepare for “more data, more automation, and that means more data handling challenges.” This will require: 

• Enhanced Security Postures: Moving beyond perimeter defense to comprehensive data protection throughout its lifecycle 

• Geographic Strategy: Making deliberate choices about data processing locations based on customer needs and regulatory requirements 

• Vendor Due Diligence: Evaluating partners not just on technical capabilities but on jurisdictional alignment and compliance frameworks 

The Trust Dividend 

Ultimately, the organizations that succeed in this complex landscape will be those that can demonstrate they’re worthy stewards of customer data. As Taylor concludes, “There’s going to be a lot more scrutiny of how all of this wonderful new processing is going to happen.” 

The complexity brings opportunity for those willing to invest in getting it right. By building transparent, responsible data governance practices, organizations can turn compliance obligations into competitive advantages – earning customer trust while enabling innovation. 

The question isn’t just who owns your customer data – it’s whether you’re prepared to prove you deserve that ownership. 

Continue the Conversation 

For more insights on navigating these challenges, visit contentguru.com 

With global enterprises like BT, Deutsche Telekom, and EE already seeing results, the discussion explores how hybrid human-AI teams, composable experience design, and data-driven automation are shaping the contact center of 2026 — and how a unified CX platform can future-proof operations and drive measurable business value.

In this CX Today interview, Rob Scott sits down with Shrenik Jain, VP of Product Management for CCaaS at Sprinklr, to explore what’s next for contact centers and how Sprinklr is taking a platform-first approach to transform customer experience.

Jain explains why Sprinklr didn’t follow the legacy voice-first route, how unification enables smarter AI, and what the shift from assistant AI to agentic AI means for tomorrow’s CX workforce. If you’re rethinking your contact center strategy for 2026, this one’s worth a watch.

Key Discussion Points:

• The real reason CCaaS is saturated: Why traditional cloud migration is no longer enough, and what customers now expect.
• Connected intelligence over channel sprawl: How Sprinklr integrates social, voice, messaging, and AI into a single platform.
• The rise of agentic AI: What moving from reactive assistants to autonomous agents means for skills, roles, and workforce planning.
• Actionable insights, not just dashboards: How AI is shifting from descriptive to prescriptive, and even autonomous decision-making.

To explore Sprinklr’s unified CXM platform and how it enables smarter, scalable, AI-powered customer engagement, visit sprinklr.com

Why This Year Is Different

Forget everything you know about chatbots and IVRs. Agentic AI represents autonomous agents that reason, make decisions, and take action independently—while seamlessly collaborating with human agents. The proof? Companies like Zepz are deflecting 30% of contacts while processing $16 billion in transactions. TUI Group migrated 10,000 agents across 12 European markets and cut operating costs by 10%. UC San Diego Health integrated Epic EHR for self-service patient authentication. These are full production deployments, and they are already delivering measurable ROI.

The Stakes: Early adopters are gaining significant competitive advantages. By the time you read about their success in case studies, they’ll be two years ahead. Re:Invent 2025 is your chance to close that gap.

Your Three-Track Amazon Connect Focused Strategy

Here are our recommended sessions across the five-day event, one things for sure, you need a plan. Choose your track:

Track 1 – Breakout Sessions led by Amazon Connect Customers and AWS Experts

Other sessions:

• BIZ211 | So Energy streamlines customer service with AI-powered automation
• BIZ212 | Anthology boosts contact center efficiency with AI
• BIZ213 | Petco unlocks agentic AI-powered customer service with Amazon Connect
• BIZ214 | Traeger accelerates contact center agent productivity with agentic AI
• BIZ215 | Cochlear enhances contact center observability with Amazon Connect
• BIZ216 | Redefining service excellence: Canada Life’s AI-powered contact center
• BIZ217 | Global tourism brand transforms customer service with Amazon Connect
• BIZ218 | UC San Diego Health modernizes patient engagement with Amazon Connect
• BIZ219 | Personalize Customer Experiences at scale with AI-powered Amazon Connect
• BIZ220 | Transforming contact centers in financial services with Amazon Connect

Outcome: Business case validation, ROI metrics, peer testimonials, strategic roadmap.

Track 2 – Business applications technical sessions Led by Amazon Connect Experts

Must-attend sessions include:

• BIZ302 | Create advanced self-service experiences with Amazon Connect
• BIZ308 | Modernize your contact center agent workspace with Amazon Connect
• BIZ310 | Optimize contact center staffing using AI-powered assistants
• BIZ311 | Optimize customer conversations in your IVR with Amazon Connect
• BIZ316 | Streamline Amazon Connect management with agentic AI-powered controls
• BIZ318 | Transform data into insights with AI-powered Amazon Connect
• BIZ320 | Unlock intelligent generative AI-powered email with Amazon Connect

Outcome: Production-ready skills, architectural patterns, implementation blueprints.

Track 3 – CX Leaders Take Note: Three Keynotes You Cannot Miss

Your Day-by-Day Navigation Plan

Monday

Arrive early, get your badge, attend foundational sessions.

PQ sessions:

• Biz 221 | Agentic AI advancements in customer experience with Amazon Connect 10:00-11:00am, Las Vegas | Wynn | Latour 2
• INV203 | Innovation Talk | The agent-enabled workplace: Transforming businesses 12:00pm-1:00pm Venetian | Level 5 | Palazzo Ballroom B

Other sessions:

• BIZ215 | Breakout session | Cochlear enhances contact center observability with Amazon Connect 11:30 AM-12:30 PM, Las Vegas | Wynn | [Silent Session] Lafite 7 (Pink Theater)
• BIZ211 | Breakout session | So Energy streamlines customer service with AI-powered automation 1:00pm-2:00pm Las Vegas | MGM | Grand 123
• BIZ214 | Breakout session | Traeger accelerates contact center agent productivity with agentic AI 2:30-3:30, Las Vegas | Venetian | Lido 3106

Hit the Welcome Reception (4:00-7:00 PM) to orient yourself and network.

Tuesday

Matt Garman’s keynote at 8:00 AM-10:30AM sets the agenda.

• BIZ213 | Breakout session | Petco unlocks agentic AI-powered customer service with Amazon Connect 1:00-2:00pm, Las Vegas | Venetian | Lido 3106
• BIZ219 | Breakout session | Personalize customer experiences at scale with AI-powered Amazon Connect 4:00-5:00pm Las Vegas | Wynn | [Silent Session] Lafit 7 (Turquoise Theater)

Connect Customer Event 6:00pm-8:00pm at the Cromwell. Customers are encouraged to attend!

Attend post-keynote sessions on new announcements. Explore the Expo (10:00 AM-6:00 PM). Evening networking receptions (6:00-8:00 PM).

Wednesday (Busiest Day)

Agentic AI keynote (8:30 AM), hands-on workshops midday, Partnership keynote (3:00 PM), Expo Happy Hour (4:30 PM), networking receptions (6:00 PM).

• Swami Sivasubramanian Keynote 8:30am-10:30am Venetian
• BIZ220 | Breakout session | Transforming contact centers in financial services with Amazon Connect 10:00-11:00am Las Vegas | MGM | Grand 123
• BIZ217 | Breakout session | Global tourism brand transforms customer service with Amazon Connect 12:00pm-1:00 Las Vegas | MGM | Grand 119
• BIZ212 | Breakout session | Anthology boosts contact center efficiency with AI 4:30pm-5:30pm, Las Vegas | Wynn | [Silent Session] Lafite 7 (Orange Theater)

Thursday

Infrastructure keynote (9:00 AM), choose between ACQUIRED event or sessions (11:00 AM), Werner Vogels closing keynote (3:30 PM), re:Play party (7:30 PM).

• BIZ216 | Breakout session | Redefining service excellence: Canada Life’s AI-powered contact center 12:30-1:30pm Las Vegas | Wynn | Latour 2
• BIZ218 | Breakout session | UC San Diego Health modernizes patient engagement with Amazon Connect 3:30pm-4:30pm Las Vegas | Wynn | [Silent Session] Lafite 7 (Pink Theater)

Friday

Final sessions wrap at 12:30 PM. Plan departures accordingly.

Insider Tips for Maximum ROI

1. Book Repeat Sessions Strategically Popular workshops like BIZ302 (self-service AI) and BIZ312 (AI agents) have repeat offerings marked “-R” or “-R1”. If your first choice is full, grab the repeat. Some sessions, like BIZ221 and BIZ219 will be Simulcast into a content hub. If you can’t get into a room, check out a content hub!
2. Leverage the Guided Expo Tours AWS experts lead 60-minute tours at specific times (Tuesday-Thursday at 11 AM and 3 PM). First-come, first-served but invaluable for navigating 400+ sponsors.
3. Download Session Content Early Presentations and code samples often appear in the mobile app during or immediately after sessions. Download before WiFi gets congested.
4. Use Multi-Venue Travel Time Wisely Allow 20-30 minutes between The Venetian, Caesars Forum, MGM Grand, Mandalay Bay, and Wynn. Use this time for informal networking or catching up on notes.
5. Attend Chalk Talks for Peer Learning Unlike lectures, chalk talks are interactive discussions where you can ask specific questions and whiteboard solutions with AWS experts and peers.
6. Visit the Certification Lounge Open Monday-Thursday (7:30 AM-5:00 PM) at The Venetian. Get certified, verify existing certifications, or access study materials. Sponsored by Accenture.
7. Balance Keynotes with Hands-On Time Don’t just collect slide decks. Workshops provide production-ready skills you can implement within 30 days of returning.

What to Bring

• Laptop (essential for workshops)
• Comfortable shoes (10,000+ steps daily)
• Business cards (old school, still effective)
• External battery (charging stations get crowded)
• Light jacket (venues vary in temperature)

The Bottom Line

AWS re:Invent 2025 isn’t just announcing the future of customer experience—it’s demonstrating it with production deployments, real ROI metrics, and hands-on workshops that give you the skills to implement immediately.

The companies presenting their success stories aren’t waiting for AI to mature. They’re already deflecting 30% of contacts, reducing costs by 10%, and serving customers across 130+ countries with AI agents that reason, decide, and act autonomously.

Your competition is in those sessions. The question is: will you be there too?

The cause? Both a rapid decline in customer experience interactions and a similar decline across BPO partners who have stopped evolving. Providers that once promised transformation, but over time, have begun to settle for maintaining the status quo. 

This isn’t another story about cost-cutting gone wrong. It’s about revenue: measurable, P&L-destroying losses that CFOs and revenue leaders are only now beginning to trace back to a decision made years ago in procurement. 

The $2.4 Million Question Nobody Asked 

Consider a global technology brand, one of those names everyone knows. The company was losing $2.4 million a year through its service booking process. 

Their product wasn’t faulty; their pricing wasn’t wrong. Somewhere along the line, nobody had stopped to ask the fundamental question, “Is our BPO partner actually making us better?” 

The process by which the company scheduled, confirmed, and serviced customer repairs and installations, had become tangled in inefficiencies. Error rates crept into double digits. Each mistake meant rework, refunds, and customer frustration. 

When Transcom was brought in to help, they led a complete workflow mapping process. What they uncovered was striking. The previous provider had failed to evolve with the business requirements, and worse, had failed to act as a proactive business partner. 

Workflows were outdated, knowledge was inconsistent across teams, and no one had taken responsibility for driving shared business goals. Transcom guided the redesign, standardized processes across regions, and built a clear, unified knowledge base. 

Within months, the error rate dropped to just 3%, less than half the original target of 7%. The annualized $2.4 million leak stopped almost overnight. 

This wasn’t a technology problem. It wasn’t a staffing issue. It was a partnership problem masquerading as both. 

The Stagnation Tax 

Ericka Heligman, who’s spent nearly two decades working with and for global BPOs, has seen this pattern play out time and again. “Too many providers stop evolving,” she says. “They’re not bringing new ideas and they’re not driving smarter ways to create value for clients.” 

When that happens, the results are predictable. Multi-million-dollar relationships quietly disappear because someone, somewhere, decided the status quo was good enough. 

Right now, she’s seeing the same story unfold with a global powerhouse brand whose long-time BPO partner has gone dormant, functionally asleep, while the market races ahead. The client’s frustration isn’t just about missed efficiencies; it’s about a lack of proactive involvement to drive ongoing, substantive improvement and real value. 

This is the true stagnation tax, not just the cost of inaction, but the opportunity cost of failing to lead. 

That’s where Transcom takes a different approach. As Jeff Blair, Chief Growth Officer at Transcom, explains: “We’re pragmatic and client-first. We take immense pride in being a proactive partner who acts as a seamless extension of our clients’ business.” 

Transcom supports a tech-agnostic model which means the company partners with the best AI and automation providers in the market and only develops proprietary tools when no suitable solution exists. This flexibility ensures clients always get the right technology for their business goals, not whatever happens to be sitting on a provider’s shelf. 

The result is a partnership built on progress, not product sales. 

What CFOs Actually Care About (Spoiler: It’s Not Customer Happiness) 

Let’s be direct. CROs don’t invest in CX because they’re sentimental about customer happiness, they do it because CX has a measurable, proven impact on revenue. 

The data is impactful: 82% of customers say they stay and spend more with brands that deliver great experiences. On the flip side, 85% have stopped or reduced spending after a poor interaction.  That’s not just a customer satisfaction problem, but a revenue retention crisis. 

CX is either your growth engine or your churn accelerator. If your BPO partner isn’t actively, constantly working to tip that balance in your favor, they’re costing you more than their monthly invoice. 

The Advisory Gap 

This is where most traditional BPO relationships collapse into irrelevance. They deliver the service you specified, at the price you negotiated, with the KPIs you defined three years ago. And then they stop. 

Transcom’s CX Advisory practice flips the script. Their focus is on auditing your business, finding hidden inefficiencies, pinpointing overlooked KPIs, and uncovering opportunities for innovation before your competitors even see them coming. 

Think about that for a moment. Instead of a partner who waits for your RFP to tell them what to fix, you get a partner who tells you what’s broken before you realize it’s costing you money. 

For that tech company with the repair and instillation errors, the breakthrough didn’t come from better agents or smarter AI. It came from business process mapping, an unsexy, detailed, forensic analysis of where knowledge gaps and inconsistent workflows were creating expensive mistakes. Then the team implemented knowledge standardization across internal teams and external partners, deployed through a coordinated regional campaign. 

Call it what it is: this isn’t outsourcing in the traditional sense. It’s a strategic partnership. 

The Next-Generation BPO Imperative 

The BPO industry is sometimes viewed with skepticism. Too many providers treat outsourcing as a cost arbitrage play: find cheaper labor, lock in a contract, and coast on renewals. 

Here’s what’s changing: enterprise buyers are no longer shopping for the cheapest option. They’re looking for partners who can deliver competitive advantage. Partners who won’t just execute the playbook you handed them, but who will help you rewrite it every quarter based on what’s happening in your business and your market. 

The leading tech brand referenced earlier didn’t just need better execution. They needed someone to notice the problem, quantify the impact, redesign the process, and coordinate implementation across multiple geographies and stakeholder groups. That’s consultancy-level work wrapped in BPO-level scale. 

The Bottom Line (Literally) 

If you’re a revenue leader, a CFO, or anyone responsible for growth, here’s the uncomfortable question: Is your current BPO partner making you more competitive, or just less expensive? 

In 2025, those are very different things. The market is moving too fast, customer expectations are rising too quickly, and AI is democratizing too much for “good enough” to remain viable. 

Your CX partner should be obsessed with your P&L. They should be able to draw a straight line between their work and your retention rates, your upsell opportunities, and your churn reduction. They should be bringing you insights, innovations, and improvements you didn’t ask for, because they understand your business well enough to see what you can’t from the inside. 

The brands winning in this environment aren’t the ones with the fanciest AI stack. They’re the ones who’ve figured out that CX is a revenue engine, and their BPO partner is either fueling that engine or silently draining it. 

The only question that matters: which one is yours? 

AI was supposed to make contact center work easier. That was the promise, anyway. Fewer repetitive tasks. Smarter routing. Real-time guidance that helps agents deliver better service without the stress.

But when you sit down with agents away from their supervisors and their performance scores, many will tell you a different story. They’re tired. Not from handling difficult customers or meeting ambitious targets, but from something more subtle and harder to name.

They’re exhausted from being watched, guided, and scored by systems that never stop paying attention.

The Well-Intentioned Digital Supervisor

The technology itself is impressive. Modern AI systems can now analyze 100% of customer interactions rather than the traditional 1-3% sample size, tracking everything from sentiment shifts to script adherence in real time.

Contact centers have embraced these tools enthusiastically. According to Omdia’s 2025 Digital CX Survey, the top reason North American contact center leaders invest in AI-powered CX technologies is to minimize agents’ cognitive load, stress levels, and burnout.

The intentions are good. AI drafts responses during live calls. It surfaces customer data automatically. It whispers coaching advice through headsets. It summarizes interactions the moment they end.

For supervisors, the benefits seem clear. Dashboards display sentiment scores, performance metrics, and coaching opportunities across the entire team. No interaction goes unanalyzed. No pattern goes unnoticed.

But here’s what the metrics don’t capture: According to Omdia’s survey, 75% of North American contact center leaders expressed concern about AI’s impact on agents’ well-being.

Something isn’t working as planned.

The Cognitive Tax of Constant Guidance

Consider what it’s like to work with an AI assistant that never stops helping.

You’re on a call with a frustrated customer. The AI pops up a suggested response. You’re already forming your own reply based on years of experience, but now you need to decide whether to use the suggestion or follow your instinct. That’s one decision.

The system flags the customer’s rising frustration. You already sensed it, but the alert adds pressure. That’s another decision.

Your response goes slightly off-script. The AI doesn’t flag it as an error, but your performance score adjusts slightly. You notice. That’s mental energy spent wondering if you made the right choice.

According to research on AI in contact centers, these AI-based tools are often used to intensify monitoring through AI-enabled cameras and perpetual real-time coaching, which drives up stress and burnout, increases insecurity, and decreases satisfaction at work.

Psychologists call this vigilance tax. It’s the extra cognitive effort required to monitor and correct a system that’s supposed to reduce your workload. Every time an agent pauses to evaluate an AI suggestion, or worries about how their natural response will score against the algorithm, they’re paying that tax.

Recent data shows 87% of agents report high stress levels, and over 50% face daily burnout, sleep issues, and emotional exhaustion. The paradox is striking: technology designed to help is contributing to the problem it was meant to solve.

From Assistance to Algorithmic Management

The shift has been gradual but significant. AI tools don’t just assist anymore. In many contact centers, they manage.

AI-based coaching software serves as an algorithmic manager, providing automated coaching and direction during calls while also generating performance data that can influence variable pay, training, or disciplinary recommendations.

The system decides which calls agents take. It monitors tone of voice. It measures empathy. It tracks when agents pause, when they deviate from suggested language, and when they take too long to respond. All of this data feeds into performance evaluations that can affect pay, promotion opportunities, and job security.

Research indicates around 70% of workers feel that performance data is used primarily for disciplinary purposes rather than skill development, creating a sense of constant surveillance rather than support.

One agent described it this way: “I feel like I’m in a driving test that never ends. Even when I know I’m doing the right thing for the customer, I’m wondering how the algorithm will score it.”

The Reality Behind the Dashboard

Let me share a real-world scenario that plays out across contact centers every day.

An experienced agent handles a complex financial services call. She’s been with the company for five years and knows the products inside out. A customer is confused about a recent charge.

Her AI assistant, trained on thousands of similar interactions, immediately suggests a scripted response that technically addresses the question. But the agent senses the customer needs something different. A more personal explanation. An acknowledgment of their frustration before diving into the details.

She follows her instinct. The call ends well. The customer is satisfied.

But her performance score for that interaction dips slightly because she deviated from the AI’s recommendation. Her supervisor doesn’t question it, but she notices. Next time, she hesitates a fraction longer before trusting her judgment.

These trends are bad for workers, as they drive up stress and burnout, increase insecurity, and decrease satisfaction at work.

Multiply this scenario across hundreds of interactions, and you begin to understand why agents feel drained not by customers, but by the technology layer between them and their work.

As AI Takes Routine Work, Complex Calls Intensify

There’s another dimension to this challenge that deserves attention. As AI takes over routine customer inquiries, agents face more complex interactions, ramping up their stress levels.

The automation of simple queries means agents spend more of their day handling difficult situations. Angry customers. Technical problems that defy standard solutions. Emotionally charged conversations that require empathy and judgment.

These interactions are inherently more demanding. When combined with real-time AI monitoring and guidance, the cognitive load becomes significant.

Studies show more than 68% of agents receive calls at least weekly that their training did not prepare them to handle. The AI can suggest responses, but it can’t fully prepare agents for the emotional complexity of these conversations.

What CX Leaders Can Do Differently

The solution isn’t to abandon AI. The technology offers genuine benefits when implemented thoughtfully. But contact center leaders need to recognize that automation and monitoring tools create new forms of stress even as they solve old problems.

Here’s how forward-thinking CX leaders are addressing this balance:

Design for Support, Not Control

AI should augment agent capabilities without dictating every decision. Agents need space to use professional judgment and apply empathy in ways that algorithms can’t anticipate.

Be Transparent About How Scoring Works

Hidden metrics erode trust. When agents understand how performance algorithms work and what they’re measuring, they feel less like they’re being judged by an inscrutable system.

Train for Confidence Alongside Compliance

The goal should be helping agents use AI as a tool they control, not a test they must pass. Training programs should emphasize when to follow AI suggestions and when to override them.

Monitor Wellbeing as Closely as Metrics

Track emotional exhaustion, cognitive load, and job satisfaction with the same rigor applied to average handle time and customer satisfaction scores. According to ICMI research, 45% of organizations and 55% of contact centers do not measure employee satisfaction or stress levels.

Protect Agent Autonomy

Give agents the ability to override AI recommendations when they know what’s best for the customer. Document these overrides not as failures, but as examples of professional judgment that can improve the AI’s training data.

Limit Real-Time Interventions

Constant suggestions and alerts increase cognitive load. Consider whether agents truly need real-time guidance on every interaction, or whether post-call coaching might be more effective for development.

By addressing the root causes of burnout and promoting strategies that balance AI efficiency with human wellbeing, we can create a more sustainable and productive contact center environment.

The Economic Reality

The business case for getting this right is compelling. According to Frost & Sullivan, replacing a single agent can cost $30,000 to $40,000. For an organization with 1,000 agents and an attrition rate of 40%, this translates to as much as $16 million in annual replacement costs alone.

Industry data shows the average attrition rate has risen from 42% in 2022 to 60% currently. While multiple factors contribute to this increase, the relationship between AI implementation and agent wellbeing cannot be ignored.

When experienced agents leave, they take valuable knowledge and skills that aren’t easily replaced. New hires require time to develop the nuanced judgment that makes customer interactions successful. This can lead to longer call-handling times, increased error rates, and lower customer satisfaction scores.

A Call for Thoughtful Implementation

The contact center industry stands at a crossroads. AI technology will continue advancing. Automation will expand. The question isn’t whether to adopt these tools, but how to implement them in ways that empower rather than exhaust the humans who use them.

Contact center agents are often strongly motivated to provide high quality customer service, and they embrace these technologies where they are adopted in a way that supports employees, allowing them to better apply or develop their skills and to be more effective in their jobs.

The path forward requires recognizing that the best AI systems don’t replace human judgment. They amplify it. They provide information and support without demanding constant attention or creating anxiety about algorithmic scoring.

Companies that figure this out will have a significant advantage. They’ll retain experienced agents who develop deeper expertise over time. They’ll deliver better customer experiences because their agents aren’t mentally exhausted from managing the technology layer. They’ll build cultures where AI is genuinely seen as a helpful tool rather than an ever-present evaluator.

Here’s What Keeps Me Up at Night

AI can listen faster, analyze deeper, and remember more than any human ever could. But it doesn’t understand what it means to be trusted by a customer in a moment of frustration. It doesn’t know what it feels like to have your professional judgment constantly scored and compared to an algorithm’s recommendation.

As AI capabilities expand, contact centers face a defining question that will shape the future of customer service work: Are we building technology that empowers people to do their best work, or are we creating systems that quietly train them to stop thinking for themselves?

The human voice, with all its imperfections and intuitive understanding, remains what customers trust most. The challenge for CX leaders is ensuring that the technology we implement strengthens that human connection rather than making it harder to maintain.

No amount of automation can replace the judgment of an experienced agent who truly understands their customer’s needs. The question is whether we’re giving those agents the space and support to use that judgment, or whether we’re measuring and monitoring them into exhaustion.

The answer will determine not just the future of contact center work, but the quality of customer experience itself.

Ready to join the conversation? Connect with 40,000+ CX professionals in our LinkedIn community to share your experiences with AI implementation and agent wellbeing. Subscribe to our weekly newsletter for the latest insights on building contact centers that work for both customers and the people who serve them.

As someone who has felt the pain of clunky handoffs and fuzzy diagnostics, I care about tools that make customer journeys clearer and kinder. Maestro is Operata’s most ambitious step yet. It expands CX Observability from a primarily Amazon Connect footprint to 50+ CCaaS, Voice AI, AI customer service, CPaaS, and CRM platforms. It introduces a unified Customer Journey Trace, a smarter CX Copilot that uses AWS Bedrock and OpenAI GPT-5.0 for natural language analysis, and an open approach for developers that includes an Insights Library and the first MCP server for CX Observability.

John Mitchem, Co-Founder & CEO at Operata: “We launched Operata to solve observability in voice and contact centres. You can’t fix what you can’t see, especially now that AI agents and human agents share the same customer journey.”

Why This Matters: Observability Is the New Control Plane for AI-Era CX

Modern contact centres are multi-platform and AI-augmented. Voice bots hand over to humans. Carriers, IVRs, CCaaS, CRMs, and LLMs all sit in the flow. Without end-to-end visibility, leaders are left guessing where quality drops, latency spikes, or handoff failures occur. Customers feel it first, NPS follows.

Mitchem again: “Start with your observability platform. Put the tools in place to judge whether new services reduce friction or create it. This has been true in IT for years, and it should be no different for your customers.”

The Maestro Release: Three Pillars

1) The Global Platform for CX Observability

Maestro supports 50+ platforms across CCaaS, AI Customer Service, Voice AI, CPaaS, and CRM, including Amazon Connect, Genesys Cloud, NICE CXone, Zoom, Talkdesk, 8×8, Twilio, PolyAI, LiveKit, Pipecat, Salesforce, ServiceNow, and Zendesk.

A new “Verified” designation flags ready-to-use data collection and integrations, with a one to three day path to verify additional supported platforms.

Why it matters: Most enterprises are hybrid and multi-vendor. Maestro gives IT and Operations one consistent view across providers, today and tomorrow.

2) One Picture Across CX Services

Customer Journey Trace presents a single, visual flame-graph timeline for every interaction, spanning telephony, IVR, CCaaS, AI agents, and human agents. Teams get span-level metrics, logs, and context in one place.

The new CX Copilot lets users ask natural-language questions, see visual results, save prompts, and trigger next-best actions, grounded in their own Operata data.

“Leaders need the whole story, not just the symptoms. Journey Trace exposes transfer delays, AI-to-human mis-handoffs, and downstream latency, the places where customer trust quietly erodes.” — John Mitchem

Ask questions like, “Where are transfers breaking,” or “Which ISPs will impact voice next week,” and get answers rooted in operational truth.

3) Open Standards for Developers, AI, and Data Teams

Maestro aligns open data collection and pipelines to industry standards for interoperability and scale.

• Insights Library: 50+ critical, real-time CX insights, from atomic signals like low MOS or high latency to composite outcomes like abandonment, rolled into CX Risk ratings.
• Operata MCP Server: the first Model Context Protocol server for CX Observability. It lets LLMs and agentic AI query Operata insights and dashboards directly, securely, and with the right context.

Why it matters: As Voice AI and agentic workflows scale, context is everything. Structured, queryable CX context helps AI return relevant answers and actions, not guesswork.

Built for IT & Ops, and Now for Data, AI, and CX Leaders

Observability has lived in IT. Maestro broadens the impact. Operations can spot issues before they hit NPS. CX leaders can see real experience impact across journeys. Developers and Data or AI teams can integrate Operata’s signals into their own systems and copilots.

“There is no one-size-fits-all AI. Diversity of models matters, but the context you feed them matters more. Operata provides journey context across platforms so your AI can answer the two questions every leader asks: what went wrong, and how do we fix it?” — John Mitchem

AWS Roots, Broader Reach

Operata’s growth has been propelled by deep work with Amazon Web Services and the Amazon Connect ecosystem. Maestro keeps that strength and extends it across ecosystems such as Genesys, NICE, Zoom, Talkdesk, Twilio, and more.

“We became popular with vendors because we help their customers succeed. It is not only finding what is wrong, it is proving what is working, and enabling rollouts with confidence.” — John Mitchem

Availability

• Insights Library: Generally Available from 22 October 2025
• All other Maestro features: Preview for existing and new customers
• Preview access: Registration required
• Amazon Connect customers: upgrade to Operata AWS Collector for Preview

The CX Today Take

This feels like a category moment. Monitoring was a safety net. Observability is now the operating system for CX, especially as AI agents join human agents in live flows. With Maestro, Operata is staking a claim as a neutral layer of truth across a fragmented stack. If you are evaluating CCaaS, Voice AI, or Customer Service AI, instrument first. The winners will see across domains in real time, correlate what matters, and act before customers feel the pain.

The Bottom Line

In a world where AI and humans share the same journey, visibility is power. The future belongs to teams that see clearly, act quickly, and learn continuously. Are you one of them?

Join the Conversation

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For CX leaders, that means a new generation of agentic AI—intelligent systems that don’t just assist employees but anticipate customer needs and take meaningful action. Welcome to the age of Connected Intelligence.

1) Webex AI Quality Management: One Console for Human and AI Performance

Cisco unveiled Webex AI Quality Management (QM), a supervisor tool that unifies coaching and improvement across both human agents and AI agents in a single platform. It combines AI-assisted scoring, real-time insights, and personalized coaching for humans with actionable recommendations and optimization for AI agents—all natively in Webex Contact Center. Planned GA: Q1 2026.

Why it matters: Moves beyond compliance checklists to continuous experience improvement and de-risks AI adoption with a single supervisory view.

Related coverage: Agentic AI in the Contact Center: How Cisco Is Redefining Service

2) Webex AI Agent & Cisco AI Assistant: From Assistive to Agentic

Webex AI Agent enables autonomous and guided self-service, tapping tools, systems, and experts as needed—created and tuned in the new AI Agent Studio. Cisco AI Assistant boosts live-agent productivity with suggested responses, real-time transcription, and summaries mid-call and at wrap-up. These are available for cloud and on-prem customers, with a beta for 50 + languages targeted for Q4 2025.

Starting in Q1 2026, Webex plans support for multi-agent collaboration via A2A and Model Context Protocol (MCP)—so Webex AI Agents can interoperate with third-party agents and external data sources under enterprise controls.

Why it matters: Faster, more accurate resolutions with AI that can act, not just advise—while preserving governance.

Related coverage: How Enterprises Are Using Webex AI to Drive Real CX Results

3) Salesforce: Orchestrating Journeys Inside Service Cloud

As part of Salesforce’s BYO CCaaS program, Webex Contact Center for Salesforce deepens the integration so organizations can orchestrate experiences using combined Webex and CRM data. Interactions can be managed inside Salesforce via Service Cloud Voice and Bring Your Own Channel, powered by Webex AI and Agentforce. Early access now; planned GA Q1 2026.

Why it matters: Reduces swivel-chair workflows and gives agents contextual, AI-enriched insights where they already work.

Watch: Webex and Salesforce Redefine CX Integration

4) AWS Lex: Smarter Virtual Agents, Available Now

Integration with Amazon Lex (the same tech behind Alexa) lets teams build natural voice and chat interfaces for Webex Contact Center and Contact Center Enterprise. Use cases include AI receptionist capabilities to deflect / route calls, improved intent recognition, and acceleration of live-agent resolutions. Available now.

Why it matters: Accelerates self-service design and improves containment while maintaining a natural customer experience.

See also: Cisco Expands AI Integrations with Amazon Lex and AWS

5) Epic: Connecting EHR Context to the Contact Center

Epic integration brings EHR context into customer interactions so care teams and agents can deliver tailored, compliant support inside Epic. Available now.

Why it matters: Reduces handoffs and rework in healthcare journeys where context, compliance, and empathy are critical.

Read: How Cisco and Epic Are Transforming Patient Engagement

6) Webex AI Quality Management in Context

For those tracking the broader AI strategy across Cisco’s collaboration and customer experience stack, UC Today’s coverage dives deeper into the company’s Connected Intelligence theme and agentic vision.

Read more: WebexOne 2025: Cisco Bets Big on Agentic Collaboration

7) Market Expansion: India and KSA on the Roadmap

Cisco plans to expand the Webex ecosystem with locally hosted solutions for performance and compliance. In Q2 2026, Cisco targets Webex Calling data centers in Mumbai and Chennai and the launch of Webex Contact Center services in India, with future expansion planned for the Kingdom of Saudi Arabia.

Why it matters: Local hosting improves latency, call quality, and regulatory alignment for global CX programs.

More coverage: WebexOne 2025: Connected Intelligence Takes Centre Stage

Leadership Perspective

“You win or lose your customers every single day through the quality of the experiences you deliver. AI is the key to delivering amazing customer experiences at scale.” — Jeetu Patel, President and Chief Product Officer, Cisco

Bottom Line for CX Leaders

• Unify oversight: Manage human and AI performance in one supervisory plane with Webex AI QM.
• Operationalize agentic AI: Deploy AI Agent and AI Assistant to act, summarize, and follow up securely.
• Integrate the journey: Use Salesforce, AWS Lex, and Epic to collapse data silos and remove friction.
• Prove value fast: Target containment, cycle times, and CSAT with production-grade use cases.
• Plan for scale: Leverage multi-agent interoperability (A2A, MCP) and regional hosting to grow responsibly.

Hollywood Meets the Helpdesk

Reynolds kicked off with a self-own (classic). When asked which role best prepared him for business, he deadpanned: “Green Lantern. Regret builds character.” Cue laughter — but also, point taken. CX leaders know the sting of failure. He spun it into a bigger truth: failure isn’t the villain, wasted failure is. Or in his words: “Make mistakes, just don’t waste them.”

If that doesn’t sound like CX transformation in a nutshell — where customer journeys are patched together like Frankenstein until someone admits the IVR is torture — nothing does.

Constraint is the Superpower

Reynolds’ biggest theme? Constraints. He’s obsessed with them. Budget cuts, tight deadlines, scrappy marketing — all the stuff enterprise leaders complain about. “Constraint forces you to think asymmetrically,” he said, before mocking studios that throw 50,000 CGI horses at a battle scene just because they can.

For CX pros, that’s the reminder that throwing more tech at a problem won’t fix the experience. Sometimes it’s about doing more with six horses — or in our world, six well-designed customer journeys.

Gut vs. Data: Fight!

Reynolds dismantled the myth of data-driven creativity:

“Our biggest viral hits? Data would’ve killed them. Gut will never go away.”

That’s a call-out to every CX leader obsessing over dashboards while ignoring the human. Numbers matter — but instincts, stories, and emotional connection win loyalty. And that’s what your customers remember.

Deadpool on AI (and Nutella)

Yes, he went there.

“AI is like Nutella for breakfast — too much and you’re going to feel sick.”

Cue knowing nods across the hall. He loves AI (it cleaned up his ADR when a marching band sabotaged a shoot), but he warned that optimisation without reflection kills originality.

For CX? Same lesson. AI chatbots, agent-assist, voice analytics — great. But if you don’t stop to actually listen to your customer, you’ll optimise yourself into oblivion.

Wrexham, Community, and CX

Reynolds’ most heartfelt moment came when he pivoted to Wrexham AFC:

“It’s not about me or Rob. It’s about the town.”

His point? True loyalty is born when people feel ownership. Fans became storytellers, authors of their own redemption arc.

CX leaders, take note: stop broadcasting, start co-authoring. Give your customers the pen, and they’ll write the loyalty story for you.

The Finale: Deadpool Meets Customer Experience

Reynolds’ keynote was part comedy set, part MBA crash course. But under the sarcasm, the message was deadly serious:

• Don’t waste mistakes.
• Constraints fuel creativity.
• Storytelling trumps analytics.
• Tech is a tool, not a religion.
• Community beats ego, every time.

In other words: business, Hollywood, and CX all run on the same script — humanity, humour, and the guts to break a few rules.

WebexOne 2025 Coverage

• Cisco Doubles Down on AI-Powered Contact Center at WebexOne 2025
• Smarter Conversations, Healthier Outcomes: Valeris’ Webex Contact Center Story
• Why the Future of AI in CX Depends on Leaders Who Can Say ‘No’
• No More Boxes: Webex’s Open Approach to Customer Experience Integration
• Ryan Reynolds at WebexOne 2025: Hollywood, Business, and CX with a Side of Sarcasm
• Connected Intelligence and the End of the Drudge Work, Says Nate Brown

“Quick parts quick, low parts meaningful. Automate the drudge work, yes. But what do we earn from that? The chance to let our people use their gifts, not just resolve tickets but proactively guide customers to success.” – Nate Brown

Beyond the Buzzwords

It’s a strangely radical thought in a week dominated by AI-first demos. While Cisco’s announcements around AI Quality Management and AI-to-AI collaboration had the room buzzing, Brown sees the real story as one of balance: elevating human capability by taking the friction out of the mundane.

There’s also something strikingly candid about Cisco’s position at this year’s event. Rather than claiming to have solved the future, Webex leaders leaned into honesty about the disruption underway. In Brown’s words:

“It’s refreshing. They’re being vulnerable about the realities. This technology truly disrupts business as usual, and we have to talk about that.” – Nate Brown

The Organisational Shift Ahead

That disruption isn’t just technological; it’s structural. Brown foresees organisational rethinks in the year ahead — the blurring of IT service management and CX, the convergence of sales and support, and the inevitable leadership reshuffles required to embed AI across workflows.

Yet he’s far from pessimistic. For Brown, the idea of Connected Intelligence isn’t simply about silicon and servers — it’s about trust, openness, and inclusion. Webex’s willingness to invite in Zoom, Epic, and Microsoft — not exactly natural bedfellows — is, in his view, a “huge” moment for interoperability.

From Fear to Fulfilment

The real question, then, isn’t whether AI will change the game. It’s whether organisations are ready to evolve their people, processes, and priorities to make the most of it. Brown’s advice to CX leaders? Take fear seriously, give employees clear pathways to upskill, and remind them what their role looks like after AI has stripped away the noise.

Or as he puts it with a wry smile:

“Don’t just ask what’s being taken away. Ask what’s being given back.”

More WebexOne 2025 News

• • Cisco Doubles Down on AI-Powered Contact Center at WebexOne 2025
  • Smarter Conversations, Healthier Outcomes: Valeris’ Webex Contact Center Story
  • Why the Future of AI in CX Depends on Leaders Who Can Say ‘No’
  • No More Boxes: Webex’s Open Approach to Customer Experience Integration
  • Ryan Reynolds at WebexOne 2025: Hollywood, Business, and CX with a Side of Sarcasm

The business problem: front-line agents are drowning in tabs, toggles, and tool fatigue. Leaders want faster resolution, deeper relationships, and lower costs—but complexity is stealing the oxygen from great service. Meanwhile, AI hype risks turning strategy into demo theatre.

At WebexOne 2025 in San Diego, we sat down with Vinod Muthukrishnan, VP & COO, Webex Customer Experience (Cisco), and Matt Kravitz, VP of Product & Chief Customer Officer, Salesforce Service Cloud, to probe a simple question in true journalistic fashion: will a tighter Cisco Webex Customer Experience–Salesforce partnership finally give agents one screen, one truth—and give leaders a safer on-ramp to agentic AI?

Start with People, Then the Platform

Both leaders argue that while AI is accelerating, humans still handle the vast majority of interactions. Complexity—more than call volume—is the silent killer of CX. The immediate prize: reduce swivel-chair work, surface context at the moment of need, and let people lean into conversations that matter.

Connected Intelligence in Practice

The partnership centres on deep CRM + contact centre integration: think Salesforce’s data, automation, and service console fused with Webex Contact Center’s telephony, routing, and channels. For the rep who lives in Salesforce, calls and channels appear natively; for operations, journeys and policies stay coherent across systems.

• One workspace: reduce context switching and cognitive load.
• One truth: unify customer data, history, and next best action.
• One path to AI: introduce automation where it helps, not where it hurts.

Agentic AI: From Demos to Deployment

It has never been easier to build a slick AI agent demo—and never harder to deploy responsibly at scale. The pair frame agentic AI as an operating model, not a gadget: start with truth (your data), choose the right metrics (customer outcomes over “containment”), and phase automation where it augments people.

• Could vs Should: just because you can automate a step doesn’t mean you should—especially for moments that benefit from human empathy (e.g., cancellations or complex changes).
• Good vs Bad Deflection: remove friction for trivial tasks, but invite conversations when there’s value in the dialogue.
• Guardrails First: safety, security, and governance are prerequisites, not patches.

What the Integration Means Day to Day

For agents: fewer systems, richer context, faster time-to-resolution. For leaders: clearer visibility from marketing to service, cleaner data for AI, and a pragmatic runway to automate the right journeys in the right order.

Top Tips for CX & Tech Leaders in 2025

1. Master the basics: stabilise data, journeys, and KPIs before scaling AI.
2. Apply the “Could vs Should” test: prioritise human-in-the-loop where trust and value are at stake.
3. Fix agent experience first: a unified console beats a dozen dashboards.
4. Instrument outcomes: optimise for customer value, not containment.
5. Phase-in agentic AI: milestone by milestone, with governance baked in.

More WebexOne 2025 News

• Cisco Doubles Down on AI-Powered Contact Center at WebexOne 2025
• Smarter Conversations, Healthier Outcomes: Valeris’ Webex Contact Center Story
• No More Boxes: Webex’s Open Approach to Customer Experience Integration
• Ryan Reynolds at WebexOne 2025: Hollywood, Business, and CX with a Side of Sarcasm
• Connected Intelligence and the End of the Drudge Work, Says Nate Brown