This article is a contribution from Jenn Di Tirro, SVP, BFSI Business Solutions at Qualfon.
CCW Orlando is always energizing. This year, the conversations around AI felt different. Less theoretical. Less vendor-driven. More honest.
When I moderated our panel, “AI War Stories and Real-World Wins,” my goal was simple. Move past the headlines and talk about what actually works, what clearly does not, and what leaders should understand before committing real dollars, real data, and real customer trust to AI initiatives.
What followed was one of the most candid discussions I have been part of in a long time. These are the lessons that stayed with me and the ones I believe every customer experience leader should internalize before making their next AI decision.
1. The best AI strategies do not start with cost-cutting. They begin with customer friction.
Every panelist echoed this in one form or another. When AI is framed primarily as a cost reduction lever, it almost always underdelivers.
The strongest use cases began with a simple question. Where are customers getting stuck? Long handle times. Repetitive transactional inquiries. Manual back-office delays that spill into poor front-line experiences.
When AI is deployed to remove friction rather than headcount, it earns organizational trust faster and scales more responsibly. Cost efficiencies follow when experience improves. They rarely lead the way.
2. The fastest wins are transactional and behind the scenes.
If you are looking for quick, lower-risk wins, do not start with emotionally complex customer interactions.
Panelists consistently pointed to highly transactional contacts and back-office intelligence as the fastest paths to value.
- Order status
- Account updates
- Payment processing
- Document classification
- Quality monitoring
- Knowledge retrieval
These areas allow teams to test, refine, and prove value without putting customer relationships at risk, which leads to the next lesson.
3. Most of the hard work is not AI at all.
This one resonated deeply.
The real effort happens long before a model is trained or a bot goes live. Data cleanup. Process gaps. Inconsistent definitions. Missing governance. Fragmented ownership.
AI simply exposes what was already broken.
Organizations that succeeded accepted this early. They invested in data hygiene, clarified workflows, and established governance before expecting AI to perform. Those who did not found themselves debugging foundational issues instead of innovating.
4. Start where customers cannot see you fail.
Several panelists shared almost-launch moments. Projects that looked ready but were not.
The smartest teams started behind the scenes with internal tools, agent assist, analytics, and workforce optimization. They allowed themselves to fail, learn, and iterate without customer impact.
AI maturity is built quietly. Public launches should be earned.
5. Expect complexity and invite it early.
AI initiatives attract attention from legal, IT, infoSec, HR, compliance, and procurement.
Successful programs did not avoid this complexity. They planned for it. They involved stakeholders early, aligned incentives, and clarified ownership. AI touches data, people, and policy at the same time. Treating it as a siloed technology project is a recipe for delay or shutdown.
6. AI does not replace people. It changes the work.
This may be the most misunderstood aspect of AI in customer experience.
AI removes low-value, repetitive work. What remains is higher-skill, higher-judgment, more human work. That shift requires better training, clearer career paths, and more engaged frontline teams.
Organizations that positioned AI as an agent empowerment tool rather than a replacement saw faster adoption and stronger outcomes.
7. Partner models are evolving.
For business process outsourcing providers, this moment matters.
Clients are no longer asking partners to simply run the operation. They are asking for deeper trust, stronger governance, and more sophisticated problem-solving. AI accelerates this shift.
The partners that win will be those who can co-own data strategy, compliance, and experience design, not just staffing models.
8. In regulated industries, AI must be governed like data.
There are no shortcuts here.
In highly regulated environments, AI governance must be as rigorous as data governance. Transparency. Auditability. Model oversight. Clear escalation paths. All are non-negotiable.
Panelists were clear…moving slower is often moving smarter when trust, compliance, and brand reputation are on the line.
9. Frontline involvement determines success.
One of the most powerful themes was the role of frontline teams.
AI insights only matter if people use them. When agents are involved in design, testing, and feedback, adoption accelerates. When they are not, even the best insights get ignored.
Frontline involvement turns AI from a dashboard into a decision tool.
10. Start with the customer. End with the customer. Always be ready to stop.
If there is one rule I walked away with, it is this.
Every AI initiative should begin with the customer and end with the customer. Leaders must also be willing to pull the stop cord if outcomes drift away from that purpose.
AI is powerful. Customer experience leadership still requires judgment, humility, and restraint.
The organizations getting this right are not chasing AI for its own sake. They are using it thoughtfully, responsibly, and always in the service of better experiences for customers and employees alike.
That is not just a good CX strategy. It is good CX leadership.
About the Author
Jenn Di Tirro is a senior sales and customer experience leader with more than 18 years of experience driving enterprise growth, complex transformation, and measurable revenue outcomes for global brands. She has spent the last decade at Qualfon, where she leads critical growth initiatives across multiple industries.
Known as a highly effective people leader and one of the CX industry’s most impactful new-logo hunters, Jenn combines team leadership with direct revenue ownership, personally originating and closing complex enterprise deals. She is recognized for her ability to align cross-functional teams around clear priorities, develop high-performing leaders, and translate client objectives into scalable, executable CX strategies that deliver real business impact.
Connect with Jenn on LinkedIn.
