This article is a contribution from Ian Jones, Chief Marketing Officer at Qualfon.
Customer expectations continue to climb. And the gap between companies that merely have a CX function and those that use customer experience as a competitive advantage keeps widening.
Some CX priorities are evergreen—there’s always work to do on satisfaction scores, efficiency, and quality. But 2026 presents a specific set of challenges that feel different from years past. AI has moved from experimental to operational. The pressure to transform is real, but so is the need to keep delivering on today’s metrics.
The companies pulling ahead aren’t doing anything mystical. They’re getting really good at three things, and those three things should be on every CX leader’s goal list this year.
Goal #1: Build a Connected Customer Experience (Not Just Connected Channels)
Most companies now offer multiple ways for customers to reach them—voice, chat, email, social, and messaging apps. Your customers can reach you however they want.
The real challenge is creating true orchestration across the entire customer journey—from the moment someone discovers your brand through marketing, into sales and conversion, through service interactions, all the way to fulfillment and retention. In most organizations, those functions still operate in silos. Marketing doesn’t know what Service knows. Sales can’t see the fulfillment issues that are eroding loyalty. Your contact center learns about product changes when the calls start coming in.
Your customers don’t experience your company in departments. They experience you as one brand, and they expect you to know what they told someone else yesterday, regardless of which channel they used.
What does this look like when a connected customer experience is working?
It’s data flowing seamlessly between every part of the customer journey. It’s a single view of the customer that’s accessible to everyone who touches that relationship—not just in theory, but in the actual systems people use every day. It’s the ability to personalize at scale because insights from one interaction inform the next, whether that next interaction happens in your contact center or your warehouse.
This requires more than technology. You need organizational alignment, process re-engineering, and often a fundamental rethinking of how different parts of your company work together.
Companies that have cracked this code didn’t do it overnight. They built it systematically, with proven processes and a clear understanding of how data, technology, and people need to work together. If you’re building this capability for the first time, there’s value in learning from organizations that have already done this work—not as a theory, but in live operations.
The 2026 goal:
Stop thinking in channels. Start thinking in systems. Stop optimizing individual touchpoints and start understanding how everything connects.
Goal #2: Implement AI Thoughtfully (Learn from Others’ War Stories)
The pressure to “do something with AI” is intense right now. Every earnings call, every industry conference, every conversation with your board—AI comes up. And the implication is clear: if you’re not moving on this, you’re falling behind.
But here’s what I’m seeing: the gap between AI experimentation and AI that actually delivers business value is wide. Really wide. And it’s littered with expensive pilot projects that never scaled, chatbots that frustrated customers, and tools that promised transformation but delivered complexity.
Everyone’s figuring this out in real time, including us. What separates the companies making progress from those spinning their wheels isn’t who has the most sophisticated AI models. It’s who has the operational discipline to know what’s actually working.
What does thoughtful AI implementation look like?
Start with use cases that have proven ROI—quality monitoring that can review 100% of interactions instead of 2%, simulation training that accelerates time-to-proficiency, agent-assist tools that surface the right information at the right moment. These aren’t moonshots. They’re practical applications that improve real metrics.
AI should augment your people’s capabilities, not replace their judgment. The best implementations I’ve seen use technology to handle the routine so humans can focus on the complex, high-value interactions that actually require empathy and problem-solving.
And here’s the part that doesn’t get enough attention: you need to understand your processes deeply before you automate them. AI applied to a broken process just gives you faster broken outcomes. Companies with decades of operational experience—who’ve refined their processes through continuous improvement—have a significant advantage here. They know what good looks like, so they can tell when AI is actually delivering value versus just generating impressive-sounding metrics.
The 2026 goal:
Implement AI that creates measurable business value this year, not someday. Partner with or learn from organizations that have the operational discipline to separate signal from noise. And remember: proven processes and experienced people are your best defense against expensive experiments that never deliver ROI.
Goal #3: Invest in Your People (Especially Your Frontline Leaders)
In the rush to automate, a lot of companies are underinvesting in the humans who actually make or break the customer experience.
This is backwards.
As AI handles more routine interactions, the human interactions that remain become higher-stakes. Your team is increasingly dealing with complex problems, frustrated customers, and situations that require judgment calls a bot can’t make. That’s a more sophisticated skillset than what traditional contact center training typically develops.
What does investing in your people actually look like?
Modern training programs that actually reduce time-to-proficiency—not just shorten classroom time, but get people performing well faster. We’re seeing simulation-based training cut ramp time significantly because people can practice difficult scenarios in a safe environment before they’re live with customers.
Career pathing that retains your best people instead of losing them to burnout or boredom. When your top performers see a future, they stay. When they don’t, they leave—and they take all their expertise with them.
Leadership development for your frontline supervisors and team leads. This is where most companies drop the ball. They promote their best agents into leadership roles and assume they’ll figure it out. But managing a team in the age of AI—coaching people who are using sophisticated tools, balancing efficiency with empathy, developing talent while hitting metrics—that’s a different job than it was five years ago.
Getting this right at scale is genuinely hard. It requires investment, yes, but also institutional knowledge about what actually works in workforce development. Systems thinking applies here too—your training, quality programs, performance management, and career development all need to work together, not operate as separate initiatives.
The 2026 goal:
Treat your people as the competitive advantage they are. Invest in their development with the same rigor you’re applying to your technology investments. And recognize that building this capability might mean learning from organizations that have spent decades getting it right.
Things to Consider: Making These Goals Real
These three goals aren’t small undertakings. Each one requires executive buy-in, investment, and sustained focus. So let’s be realistic about what’s achievable in one year.
First, scope matters. You’re not going to build a fully connected customer experience, implement AI across every process, and transform your entire workforce development program in twelve months. But you can make meaningful progress on each. Pick one breakthrough priority and two supporting initiatives. Make sure they’re connected—systems thinking applies to your goal-setting too.
Second, be honest about capability. Do you have the infrastructure, expertise, and bandwidth to build these capabilities from scratch? Some companies do. They have the technical talent, the operational maturity, and the time to learn through trial and error.
Others would benefit from working with organizations that have already climbed this learning curve. There’s no shame in that—it’s strategic thinking, not surrender. The question isn’t whether you’re capable of figuring it out eventually. The question is whether you want to spend two years learning lessons someone else has already learned, or whether you’d rather accelerate by partnering with people who’ve done this before.
Third, consider the hybrid approach. Even strong in-house teams can move faster by learning from partners who bring battle-tested processes, institutional knowledge about what actually works at scale, and experience separating hype from business value. You don’t have to outsource everything to benefit from someone else’s expertise.
The companies that will win in 2026 aren’t necessarily the ones with the biggest budgets or the most advanced technology. They’re the ones who are honest about their starting point, clear about their priorities, and strategic about how they build capability—whether that’s internal development, external partnership, or some combination of both.
About the Author
Ian Jones is Chief Marketing Officer at Qualfon, where he helps prospects discover how the company’s AI-assisted, person-centric solutions support the entire customer experience—from marketing and sales through service and fulfillment.
Before becoming CMO in 2024, Ian led Qualfon’s Integrated Solutions Group for four years and spent 28 years in advertising and marketing at agencies including Leo Burnett and BBDO. Based in Detroit, Michigan, he’s navigating the same CX transformation challenges his clients face.
Connect with Ian on LinkedIn.
