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Change is hard, even when it promises something better. I learned that firsthand when my doctor suggested a new technology to manage my diabetes. I hesitated at first. Not because I doubted the science, but because trust takes time. That same careful consideration is what I see in financial institutions evaluating AI today, and it’s not a weakness. It’s wisdom. 

I’ve lived with Type 1 diabetes for most of my life. Managing it requires constant attention, discipline, and trust in the tools and people around me. A few years ago, my endocrinologist recommended I switch to a continuous glucose monitor (CGM), a device that tracks blood sugar in real time and offers far more insight than traditional finger pricks. 

At first, I was reluctant. Not because I didn’t believe in technology, but because I wasn’t ready to change routines that had kept me safe for decades. I had questions. I had concerns. I needed to understand how it worked, what risks it carried, and whether it would truly improve my health. 

Only after asking every question and feeling confident in the answers did I make the switch. 

The result? My glucose control improved dramatically. I understand my condition better, and I manage it more safely. The technology didn’t replace my judgment, it enhanced it. It gave me real-time visibility into trends and outcomes, alerting me before danger struck and helping me steer toward better decisions. 

The Same Dynamic Exists with AI in Financial Services

Financial institutions face a similar situation. Leaders see the potential: better insights, faster decisions, more personalized experiences. Yet many proceed carefully, and they’re right to. 

Banking is a trust-driven, highly regulated industry. Every decision is scrutinized, and every misstep has consequences. I’ve heard banks say, “Your technology is interesting, but we won’t be first to use it.” That’s not resistance, it’s prudence. And it’s understandable. 

Regulation Shapes Culture

Financial institutions operate under strict regulatory frameworks. From UDAAP to AML to Fair Lending, the rules are clear: protect consumers, ensure fairness, and avoid unintended harm. These guardrails are table stakes, and they shape organizational culture. They create a bias toward risk avoidance, which can slow innovation, even when that innovation could improve outcomes for both customers and shareholders. 

This is the tension: the desire to innovate is paired with the responsibility to stay compliant and protect trust. 

The Path Forward: Expert Guidance and Outcome-Based Adoption

Just like I needed my endocrinologist to guide me through the transition to a CGM, financial institutions need expert partners to help them adopt AI responsibly. That means understanding how the technology works, how it aligns with regulatory expectations, and how it can be implemented without compromising safety or fairness. 

It also means asking hard questions: 

These aren’t barriers. They’re the foundation of trust. 

And here’s the key: AI isn’t just about automation. It’s about improving outcomes. The CGM didn’t just give me data; it gave me foresight. It helped me avoid danger and make better decisions. Financial institutions can do the same. With the right tools, they can simulate potential outcomes before decisions are made and steer toward better ones. 

Final Thought

AI can be used safely and productively in financial services. But it requires time, research, and the right guidance. Institutions that approach adoption deliberately, with curiosity, caution, and expert support, will be the ones that unlock real value. 

Because caution isn’t the enemy of progress. It’s part of the process. And when paired with outcome-driven thinking, it becomes a powerful catalyst for change.  

I’ll never forget how it felt to get a mortgage to buy my first house. Although I worked in banking and personally managed our mortgage business, it was nonetheless quite anxiety provoking. I had confidence in myself, but how would I pay back a loan that was more than twice my current income?  What if my career trajectory didn’t proceed as I envisioned? Did I overextend? What was the right mortgage for me? Should I buy down the interest rate by paying upfront points? What hidden closing costs could alter my carefully planned budget? I had so many questions and concerns. 

My decision wasn’t just a financial calculation. It was a deeply personal decision. And while I had access to plenty of tools and calculators, what I really needed was someone who could help me think through the “what ifs.” Someone who understood my situation walked me through the options and helped me feel confident in the path I was choosing. 

Financial Products Are Complex by Design

Many financial products, including mortgages, insurance, credit cards and investment vehicles, are complex by nature. They have to be. These products are built to perform a wide array of functions and must account for numerous scenarios, preferences, and risk profiles. That complexity is necessary to make them flexible and effective. 

But with complexity comes a burden. Customers are asked to make decisions that are both rational and deeply emotional. Digital tools can support the rational side, such as comparing rates or calculating payments. But they often fall short when it comes to building confidence.  

The Role of Human Advisors

This is where human advisors still matter. A good advisor doesn’t just explain the product. They understand the person. They can sense hesitation, ask the right questions, and help customers think through contingencies. They bring empathy, experience, and reassurance, especially in moments that carry emotional weight. 

Looking back on my own experience, what I needed most wasn’t just information. I needed trust and empathy. I had to weigh several options, each with its own trade-offs, and think through how they might play out in different life scenarios. It wasn’t just about interest rates or repayment terms. It was about feeling confident in a major financial decision. And it was a person, not a tool, who helped me work through those questions and reach that point of confidence. 

AI Enablement vs. Autonomy

AI has a role to play. It can support advisors with better insights, faster analysis, and more personalized recommendations. But it is not ready to replace the human connection, especially in high-stakes decisions. 

Customers are generally comfortable when their advisor uses AI tools to support decision-making. What they are not ready for is a fully autonomous experience where the human is removed from the process. In emotionally charged or complex financial decisions, people want to deal with a human being. 

There is a meaningful difference between AI enablement and full automation. Automation is fine, even preferred, for simple transactions like checking balances, confirming due dates and reviewing recent transactions. But in sensitive scenarios like taking out a mortgage or buying the right insurance coverage at the right price, customers value empathy, real-world understanding, and the ability to talk through contingencies. These are things digital tools alone cannot yet provide. The human element remains essential. 

Final Thought

Financial institutions that get this balance right, combining AI’s capabilities with human empathy, will be the ones that earn trust. Because at the end of the day, financial decisions are not just about logic. They are about life. And that is something only people can truly understand. 

New York, NY – October 22, 2025 – Afiniti Inc., a global provider of artificial intelligence and customer experience optimization today announced its partnership with Five9, the intelligent CX platform provider. The collaboration will give Five9 customers access to Afiniti’s AI Pairing technology within the Five9 Intelligent Cloud Contact Center, helping organizations improve conversion rates, boost agent performance, and drive measurable business outcomes.

Afiniti’s AI Pairing technology uses behavioral and contextual data to match customers with the best available agents in real time, improving satisfaction, efficiency, and measurable business outcomes across every interaction. Partnering with Five9 brings these capabilities directly to the Five9 Intelligent Cloud Contact Center, extending the reach and value of both platforms and helping enterprises drive stronger results at scale. 

Afiniti’s solution is also available through the Five9 Marketplace, click here to view the listing, providing customers with streamlined access and seamless deployment.

“We are excited to welcome Afiniti to the Five9 Marketplace,” said Amanda Miller, Director of ISV Partnerships at Five9.
“By integrating Afiniti’s AI-driven pairing technology with the Five9 Intelligent CX Platform, we are empowering enterprises to create more personalized, impactful customer experiences that drive stronger business results.”

Eyal Brami, VP of Partnerships at Afiniti, said: “We are excited to bring Afiniti’s behavioral pairing technology to the Five9 ecosystem through this new partnership. By combining our AI-driven capabilities with the power of the Five9 Intelligent CX Platform, we are enabling enterprises to deliver smarter, more personalized customer experiences that drive measurable improvements to both revenue and operational performance.”

About Afiniti

Founded in 2006, Afiniti is the world’s leading provider of AI solutions that optimize customer interactions across industries. Afiniti’s patented Pairing technology identifies and predicts patterns of interpersonal behavior to connect customers with the agents most likely to deliver positive outcomes. Trusted by global enterprises in telecommunications, financial services, healthcare, and more, Afiniti has generated more than $2.2 billion in incremental annual value worldwide. To learn more, visit www.afiniti.com.

What Leaders Must Ask Themselves
As you read this, I’d encourage you to reflect: How much are you using data and AI to tailor perceived value for each customer today? And if not, how long before someone else does?

Over three decades in financial services, from banking to cards, rewards, insurance and now technology, I’ve seen one principle prove itself time and again: to acquire, deepen and sustain relationships, customer value must outweigh costs. But as the saying goes, “beauty is in the eye of the beholder” – perceptions of value are always personal. Some customers calculate every dollar of benefit. Others care just as much about exclusivity, service quality, the sense of being recognized or the trust that the institution will be there in the time of need. 

The Problem with ‘Average’ Value

Traditionally, financial institutions tried to solve for perceived value through benefit bundles: packages of features, coverages, perks, annual fees and loyalty programs that, on average, meet the needs of a target segment. But marketing to the average needs of target segments is blunt and often costly. What delights one customer will be irrelevant to another, yet bundle costs are borne either way. And when companies lean too heavily on one type of value, purely rational, purely emotional, or purely relational, they miss what truly drives loyalty.  

What has changed is that we no longer need to operate in a segmented world. With today’s analytics, true one-to-one personalization at scale is possible. The future isn’t about designing bundles that work for the average; it’s about ensuring each customer sees and feels the parts of that bundle that matter most to them. 

AI: From Bundles to Personalization 

AI changes this equation and the future. Today, advanced analytics make it possible to tailor value at the level of the individual. AI enables institutions to detect both broader tendencies as well as time and situation specific signals and personalize the entire customer experience. 

Think of a premium credit card that comes with over 100 different benefits. Historically, customers had to sort through them on their own. Today, AI makes it possible to highlight the benefits that matter most to each customer; the right travel perk when they’re booking a trip, the right dining benefit when they’re reserving a table, or the right insurance protection when they’re considering a big purchase. That reinforcement should happen dynamically at every intersection: logging into a website, browsing in an app, or calling customer service. And those signals won’t remain static. They will shift over time as needs, circumstances, and behaviors change. 

Consider the experience of a customer shopping for auto insurance. In the past, pricing was based on broad categories, like “young drivers” that often missed individual nuance. Today, AI enables insurers to personalize every step of the journey. Telematics and connected vehicles allow for tailored pricing based on real driving behavior. Digital assistants help customers select deductibles, limits, and add-ons in real time, based on their unique risk profile. And when it comes to service, carriers can now deliver high-touch support precisely when it matters most. As one industry expert put it, “Every node on the journey can feel like a path for one.” 

This is the real challenge for leaders: how will you deliver more perceived value to deepen customer relationships? The question is whether you are personalizing how those bundles are communicated and experienced. Best-in-class companies will continue to offer comprehensive packages, but they will use AI to tailor and reinforce the message so that each customer feels the value proposition was designed specifically for them. 

Looking ahead, this ability to personalize value at scale will determine which institutions thrive. Customers are increasingly comparing financial products not only to other banks or carriers, but to the best digital experiences in their lives. They will expect financial services to anticipate their needs, adapt instantly, and deliver value in ways that feel both rational and deeply personal. 

Washington, D.C. – October 9, 2025 – Afiniti, Inc., a global provider of artificial intelligence and customer experience optimization, today announced the appointment of Chris Karp as Chief Growth Officer.

Karp has transitioned from Afiniti’s Board of Directors to join the company’s executive leadership team in a full-time capacity. In this pivotal role, he will oversee the growth functions – including Client Services, New Business, Marketing, Commercial Strategy, Partnerships, and New Product Go-To-Market – unifying them under one vision. His leadership and deep industry experience will accelerate Afiniti’s transformation as the company leverages its industry-leading AI pairing solutions into a broader suite of outcome-centric optimization solutions designed to increase customer retention, sales conversion, and revenue growth for enterprises.

Chris brings a unique set of skills and experience to Afiniti. He scaled and led an innovative customer service operation at Chewy, was Chief Customer Officer and EVP of Operations at Auctane where he helped to lead AI strategy, and held senior leadership roles at RealPage and Tektronix Communications. Across these roles, he built high-performing teams, delivered strong financial results, and consistently drove client-first innovation.

“Chris’s deep understanding of contact center operations and the leading-edge AI products that drive measurable client value will be vital as we expand our capabilities and continue to enhance customer experience journeys,,” said Jerome Kapelus, Chief Executive Officer of Afiniti. “His leadership and strategic vision will play a key role in helping us strengthen client relationships, increase sales conversion, and drive sustainable revenue growth.”

“Afiniti’s outcome-driven AI technology has a unique opportunity to redefine how enterprises unlock value from customer interactions,” said Chris Karp. “I’m excited to join full-time to help scale our growth and bring the next generation of AI optimization solutions to market.”

About Afiniti

Founded in 2006, Afiniti is the world’s leading provider of outcome-driven AI technology that optimizes customer interactions across industries. Afiniti’s patented AI Pairing solution identifies and predicts patterns of interpersonal behavior to match each customer with the most compatible agent for desired business outcomes. Trusted by global enterprises in telecommunications, financial services, healthcare, and more, Afiniti has generated more than $2.2 billion in incremental annual value worldwide. To learn more, visit www.afiniti.com.

Media Contact
info@afiniti.com

When we talk about the state of customer experience today, the spotlight often shines on shiny new digital tools and agentic AI. The promise is appealing: more automation, more self-service, fewer calls. 
But here’s the question I keep coming back to: are we actually reducing the number of calls by fixing the underlying problems, or are we just creating more ways for customers to chase solutions when something breaks? 
Two Paths to Fewer Calls

At its core, there are two ways to prevent calls to a contact center: 

Eliminate the defect or root cause of the issue that forces the customer to seek help in the first place. 

Build self-service or digital tools that let the customer resolve issues without calling. 

The first path is harder but far more rewarding. Preventing defects delivers a better experience and builds trust, because customers don’t need to seek help at all. The second path can also improve experience if it reduces effort and solves problems effectively. But it’s only a true improvement if it works. 

Unfortunately, there’s also a third option we’ve all seen: simply hide the call center phone number. That’s not a strategy, it’s avoidance. 

The Appeal of Digital Solutions

In the past five years, agentic AI and advanced digital channels have captured headlines. Many predict they’ll rival or even replace the call center. 

But I’ve been around long enough to remember that twenty years ago, experts said websites and apps would soon make call centers obsolete. Fast forward to today: call centers remain central to customer support. Why? Because defects and complex issues persist, and when they do, customers must still turn to people for resolution. 

A Zero-Sum Game?

Technology cuts both ways. It can enable elegant self-service, but it can also create new reasons for customers to call. 

Think about the countless data breaches where sensitive information gets exposed online. That very technology meant to streamline experiences ends up creating a whole new set of problems customers must resolve by phone. 

So, we have to ask: has the focus on building more channels distracted companies from fixing the root causes that drive calls in the first place? Or has the complexity of modern products and services simply created more points of failure? 

The Real Priority

Reducing calls by fixing defects is not just an operational win, it’s the foundation of a better customer experience. Digital tools and AI matter, but they shouldn’t overshadow the basics: reliable products, thoughtful processes, and deliberate design that prevent the need for a call at all. 

Because at the end of the day, the ultimate measure of success isn’t how many customers you deflect into self-service. It’s how few of them needed help in the first place. 

Wrapping Up This Series

This piece concludes my five-part series exploring the evolving role of the contact center in customer experience. From voice as a trust channel, to perception, persistence, consistency, and now defect reduction, each post looked at a different dimension of what truly shapes outcomes. 

While this series has come to an end, the conversation is far from over. Customer expectations keep rising, and the intersection of digital tools, AI, and human service will continue to evolve. I look forward to sharing more reflections on what’s changing, and what should never change, in the world of customer experience. 

In theory, digital channels are supposed to make customer interactions easier. But when data doesn’t persist across those channels in real time, the burden falls squarely on call center agents. Instead of jumping straight into problem-solving, they spend valuable time piecing together a puzzle, trying to figure out what the customer has already done before picking up the phone. 
The Real-World Experience

Think about the last time you tried to resolve an issue online or complete a purchase through an app. Maybe it worked and you were satisfied. But what if it didn’t? 

If you ended up calling for support, was the agent aware you’d already tried to fix things digitally? Could they pick up right where you left off? Or did you have to start over, explaining everything from scratch? That’s a frustrating experience for any customer — and it puts the agent at a disadvantage from the first hello. 

Why This Keeps Happening

We’re in a multi-channel world. Customers move between stores, websites, mobile apps, and contact centers. But companies often can’t keep up with that movement. 

A customer might wait in a store without being helped. They might browse online to seek an answer to a problem. Or they might add something to their cart and abandon it when checkout fails. When they call for help, the agent often doesn’t see any of that. No context. No continuity. Just a fresh call and a frustrated customer. 

The 9:15 p.m. Friction Point

Imagine this: It’s late, and you’re online trying to complete a purchase. A message pops up: “Please call us or visit a store to complete your order.” But the stores are closed. So, you call. 

The IVR reminds you that “most transactions can be completed online,” then tells you there’s an eight-minute wait. After twelve minutes, you reach an enthusiastic agent. But she has no record of what you just did online. No visibility into your cart. You’re starting from zero. 

Agents Deserve Better

This lack of real-time data access creates double jeopardy. Customers are already frustrated that the digital channel didn’t work. Then they’re forced to repeat themselves, which escalates the frustration. 

For agents, it means less time solving problems and more time retracing steps. For customers, it means more friction and less trust. Neither side wins. 

Proactive Progress, but Still Gaps

To be fair, companies have made progress with proactive triggers: outage alerts, billing notifications, and delivery updates are good examples of reducing friction before a customer picks up the phone. Many also capture website and app interactions and write them into databases, though often with a lag. 

But the gap remains: most organizations still haven’t mastered feeding all that interaction data into the agent’s desktop in real time. That’s the missing link between digital channels and human conversations. 

The Bottom Line

It’s not easy to build systems that write customer activity into databases fast enough for agents to see it in real time. But until that gap closes, we’re relying on agent persistence rather than data persistence. 

And as customer expectations rise, “pick up where I left off” isn’t a nice-to-have anymore. It’s the baseline. 

In my next blog, I’ll explore why consistency across these interactions is just as critical as persistence — and how the two together can make or break the customer journey. 

What is customer experience, really?

My favorite definition comes from Bruce Temkin:

“The perception that customers have of their interactions with an organization.” 

That one word “perception” changes everything.

The Hidden Variable in Every Call 

In the contact center, two people can go through the same exact process, hear the same words, get the same resolution, and walk away feeling totally different. 

One person may feel heard. The other may feel dismissed. 

One may feel loyal. The other frustrated. 

That’s perception. And it’s shaped by more than what’s said or done on the call. It’s shaped by the entire customer experience leading up to that point.  

Maybe they have a product that didn’t work at a critical time. Maybe they already tried a digital channel. Maybe they’ve bounced around. Maybe they didn’t even want to call in the first place. 

By the time someone reaches a human, their perception can already be formed and often, it’s not great. 

Why This Makes Live Calls So Hard 

Let’s be honest: call centers weren’t traditionally built for this level of nuance.

Most are set up to route calls based on intent, “I want to buy something,” “I have a billing problem,” “I need to cancel.” So, you group agents into skills-based queues, give them training and tools, and try to match the issue with the solution.

But here’s the challenge: perception doesn’t always follow intent. It’s personal. It’s contextual. It’s the question behind the question.

It’s invisible in the data unless you know where to look. And the data is often not available in the call center, especially when a customer moves among other channels before making a call.

Perception is a Factor We Can’t Ignore 

The contact center is often the last stop in someone’s journey and the best chance to fix a broken perception of the customer’s interactions with a company.

That’s a lot of pressure.

But it’s also an opportunity. If we understand how unique and subjective every call really is, we can stop optimizing just for efficiency and start designing for impact.

It doesn’t mean adding more steps. It means helping agents do what they’re already trying to do: make someone feel heard, understood, and taken care of.

One perception at a time.

I’ve spent the past 20 years immersed in customer experience, and what makes my perspective a little different is that I’ve lived it from all sides. I’ve led contact center operations firsthand. I’ve built and run end-to-end CX programs, from voice of the customer to journey mapping and operational feedback loops. And I’ve been on the solution partner’s side too, helping organizations adopt AI solutions to improve their contact center performance.
That mix lets me bring a holistic view when I work with clients and prospects. At Afiniti, I’m not just talking about technology for its own sake. I’m focused on solving real problems, because I’ve been in the chair and I know what it takes to make change stick.
We’ve Come a Long Way 

Over the last two decades, organizations have invested heavily in broadening how customers engage, through self-service tools, mobile apps, agentic AI, and more. These advances have brought real benefits: lower effort, faster resolution, and greater customer control. 

That’s a good thing. Customers want options. And companies have rightfully responded by expanding digital channels. 

But despite all that progress, many customers still pick up the phone. 

What Hasn’t Changed 

Even with excellent digital tools in place, there are still moments when people need to speak to someone. And when they do, those moments are rarely simple. 

What remains in the contact center today are the emotionally charged, high-value, or complex interactions that digital channels often can’t fully resolve. That means the calls that do reach a human agent matter more than ever and they’re harder than ever to handle. 

It’s not a volume game anymore. It’s a quality game. 

Why the Contact Center Deserves Renewed Attention

These moments, when someone calls you because nothing else worked, are critical. They’re often the difference between retaining a customer and losing one, between resolving an issue and deepening customer frustration. 

And yet, the contact center is still too often treated as an afterthought, even as the nature of the work becomes more demanding. 

If you’ve already made great strides in digital experience, this isn’t a call to rewind the clock. It’s a reminder not to forget the value of the voice channel. It’s still where trust is won and lost. 

Agents Need Support, Too 

Because today’s calls are more complex, agents need better support. It means giving them the tools, training, and context to respond with clarity and empathy. 

I got into customer experience during the Sprint–Nextel merger back in 2005. I was asked to help lead part of the integration. At the time, the contact centers were struggling. High call volumes, frustrated customers, and unhappy agents. We pulled together a task force to figure it out. 

What we uncovered changed the way I think about CX. 

It wasn’t really a contact center issue. It was a wider customer experience problem. Customers weren’t calling us just to talk. They were calling because something had gone wrong. Their bill didn’t make sense. Their coverage was poor. They didn’t understand the contract they just signed. The contact center was left trying to clean up the mess. 

That was a turning point for me. I stopped seeing contact centers as support functions and started seeing them for what they really are: the front line of trust. 

The Metrics That Matter 

Years ago, during my time at Sprint, we used dropped calls as a measure of network quality. The logic was sound, until we noticed elevated churn in areas with “good” coverage. 

It turned out some customers had stopped making calls altogether in places where the signal was bad. Our metric was clean, but it masked a problem. 

That experience taught me to always ask: are we measuring what really matters? Are we looking beyond the numbers and understanding the full story? 

That mindset applies to CX today more than ever. 

One Last Thought 

The contact center is not a relic of the past. It’s a vital channel in a multichannel world. And as interactions become more complex and emotionally loaded, it’s time to give it the attention it deserves. 

If you’ve made great strides in digital experience, keep going. But don’t forget what happens when your customer calls and needs help. That’s still one of the most important moments in the customer journey. 

Featuring: Jessie Burgess, Former EVP & CIO, G6 Hospitality
Use Case: AI-Powered Call Center Optimization

With over 1,400 properties and 30 million annual guests, G6 Hospitality operates in a high-volume, high-stakes environment. To maintain quality at scale, the company turns to best-in-class partners, especially when it comes to specialized technologies like AI. 

That’s where Afiniti comes in. 

“Afiniti is AI behavioral pairing technology that uses data intelligently to pair our customers calling in with agents based on likely fit.” 

For Jessie Burgess, former EVP & CIO at G6, the solution was clear: integrate advanced technology without disrupting day-to-day operations. 

Seamless Integration, No AI Expertise Required 

Afiniti’s technology fits directly into G6’s existing Avaya-based platform and routing operations—no overhaul needed. 

“We didn’t have to be AI experts to deploy it. There are no scripts to learn. It runs transparently.” 

Within the first year of going live, G6 saw a 4% increase in reservations when the system was on. And with continuous A/B testing running every half hour, the impact isn’t just noticeable – it’s measurable. 

More Bookings, More Satisfied Agents 

At its core, Afiniti enhances what G6 already does best: connecting with customers. The AI doesn’t replace agents – it empowers them. 

“It’s 17,000 more times they get a chance to sell.” 

Better pairings mean guests get what they’re looking for faster, while agents are more engaged and effective in their conversations. 

Results You Can See 

The G6-Afiniti partnership is built on one thing: performance. 

“Afiniti was just right for us because they’re real. Measurable. Monitored.” 

With continuous optimization, data-backed insights, and results-driven execution, G6 has transformed its contact center into a revenue-driving, experience-enhancing engine. 

Key Takeaways 


Want to see how outcome-based AI can transform your contact center?

Get in touch with us today.

See the full interview here.