Callum O'Brien, Program Director, CX USA Exchange 2026
Every platform you work with knows something, but none of them know everything. Every CX leader understands the frustration when disconnected systems and channel-specific optimization leave teams with conflicting insights instead of a complete picture.
How do you consolidate the data to create a single source of truth? And how do you connect the dots across your ecosystem to enable more confident decision-making and provide customer service teams with complete sets of information?
• How have leading organizations broken down data silos without overhauling their entire technology stack?
• What can you do to move beyond channel-specific optimization to create a more connected view of the end-to-end customer journey rather than individual touchpoints?
• Connecting the domains of customer, product, location and asset data to prevent conflicting insights
• Building cross-functional trust in your new single source of truth
With an influx of new tools, many companies and boards are lost in the hype and convinced that each new AI initiative will answer all their problems.
But the reality is very different: AI tools are only as effective as the data they learn from. Without accurate, accessible and well-documented datasets, even the most advanced AI solutions will struggle to deliver meaningful value.
• Understanding how leading organizations are structuring, managing, documenting and governing their data for AI success
• Creating the semantic architecture necessary to transform generic AI into highly accurate, domain-specific enterprise agents
• Exploring real-world examples of how businesses are connecting and consolidating their data ecosystems
• Benchmarking your data maturity against industry peers and uncovering what use cases are delivering value and where investment is being prioritized
One of the primary reasons that AI initiatives fail to scale is because organizations try to layer new technology onto Dark Age processes.
While it is possible to automate chaotic processes, to ensure it delivers meaningful, cost-effective and efficient improvements, leaders must simplify before introducing AI or more effectively guide AI to navigate the chaos.
• Identifying the workflows that should be redesigned before deployment to avoid costly rework, and where the complexity is simply part of the process
• Designing SOPs that enable automation to scale effectively without sacrificing consistency and customer outcomes
• Measuring impact through productivity gains, lower costs and better experiences
Most organizations have no shortage of customer data, yet many CX leaders still struggle to secure executive buy-in and investment. The challenge isn't collecting more data - it's translating customer insight into metrics that resonate in the boardroom.
Explore how to tell a more compelling story with your data and position CX as a driver of operational efficiency, revenue growth, cost reduction and business performance, not just customer satisfaction.
• What evidence most effectively influences executive stakeholders and boards?
• When do customer insights and satisfaction measures matter most, and when do other business drivers carry greater weight?
• How competitive benchmarks and market trends influence investment decisions.
• The role of operational efficiency, productivity, and cost-to-serve improvements in funding Customer Experience initiatives.
• Common pitfalls that prevent organizations from moving from pilot programs to enterprise-scale adoption.
• How leaders build coalitions across business, technology, and customer facing teams to sustain long-term investment.
• How do you define the ROI of experience: more revenue, more channel adoption or reduction of cost to execute?
Replatforming is essential for long-term growth, but it can easily disrupt customer journeys and stall delivery if not managed carefully.
The right implementation and support can help to accelerate delivery, so the transformation strengthens the customer experience rather than eroding loyalty.
• Uncovering tactics for influencing leadership to actively endorse the replatforming initiative to ensure teams remain aligned throughout the process
• Confirming cross-functional teams understand the positive impact the process will have on their work too
• How can you work around competing priorities that slow progress?
Customer trust was once built over months of consistently delivering on your brand promise but in today's saturated market, brands can't afford to wait that long.
With trust often acting as a lagging indicator, leading organizations are rethinking how they can create confidence from the very first interaction, and fast track trust.
• Uncovering the key to building trust into every interaction - embedding transparency, privacy and customer control into the experience rather than treating them as compliance exercises
• Helping customers understand how their data is used and how it benefits them
• Architecting robust guardrail gates for Agentic models to ensure trust is guaranteed
In 2027, it is becoming increasingly clear that the future of CX is not defined by the Agentic AI models we deploy, but by the people we empower.
Adopt the playbook of leading organizations who are building the skills, confidence and culture needed to turn Agentic AI investment into lasting business value.
• Moving beyond AI cost-cutting and lay-off narratives to identify where technology can augment, not replace, employees and workflows and create better customer outcomes
• Equipping teams with the skills and confidence to shift focus from repetitive tasks to higher-value tasks where they can deliver the greatest impact
• Designing new and robust frameworks for AI agent oversight
• Building trust and engagement by involving employees in the Agentic AI transformation journey
Every leader in this room has likely used some version of the phrase 'I just wish our systems would speak to each other'.