One of the strongest themes across the finalists was a focus on harnessing AI to address customer and employee pain points, and as a result, improve their experiences. Rather than implementing AI simply to automate interactions or reduce headcount, these organizations identified specific sources of friction and used AI to eliminate them.
Most finalists focused on reducing repetitive work for employees, helping them spend less time searching for information, documenting interactions or navigating multiple systems. Many targeted customer effort by simplifying access to services, reducing wait times and improving continuity across channels. The most advanced are using AI pervasively to drive improvements in employee and customer experiences.
The result is that AI becomes almost invisible. Instead of noticing the technology itself, customers and employees alike simply have smoother, more relevant interactions and achieve faster resolutions.
Treat AI as an employee enabler
Across nearly every finalist submission in the Level Up category, AI was positioned as a tool to augment and empower employees. This approach reflects the sentiment that employee engagement is a prerequisite for customer satisfaction.
Better-equipped employees make better decisions, handle interactions more confidently and deliver more empathetic service. This often improves customer outcomes indirectly by making employees more successful.
To that end, several finalists deployed Genesys Cloud Copilots that provide real-time knowledge, recommended actions, conversation summaries and contextual guidance. Others use AI to automate quality management, identify coaching opportunities or surface customer sentiment.
These capabilities consistently deliver two benefits. First, they reduce cognitive load for employees by reducing manual work and making information easier to access. Second, they improved consistency, helping newer employees perform more like experienced team members while enabling supervisors to scale coaching and support.
Many finalists emphasized that AI delivers the most value when it connects experiences across channels rather than solely optimizing individual touchpoints.
Increasingly, customers move between interaction channels and between self- and assisted service for information or issue resolution. The organizations achieving the strongest outcomes are ensuring context follows the customer throughout that journey.
These finalists use AI to preserve interaction history, summarize prior conversations and automatically transfer context when customers move between channels or escalation points. Many are also using AI-powered routing to connect customers with the best available resource based on intent, customer history, value or issue complexity.
The result is a more continuous experience where customers no longer need to repeat information and employees begin interactions with greater context and confidence.
This approach transforms AI from simply optimizing a collection of touchpoints into an orchestration engine.
Another common theme among finalists was the use of AI to transform operational data into actionable, real-time insight.
Many finalists are using speech and text analytics, sentiment analysis and interaction intelligence to identify emerging issues, uncover friction points and continuously improve experiences.
Several described moving beyond traditional quality management approaches that rely on small interaction samples. Instead, they’re evaluating dramatically larger volumes of interactions, allowing them to identify trends faster and coach employees more effectively. And some are using AI to improve forecasting, workforce planning and resource allocation, ensuring that customer demand and staffing decisions remain aligned. This also allows for agile responses to unexpected changes in demand.
This shift from retrospective reporting to real-time decision-making can create a powerful advantage. With AI-powered analytics and reporting, these organizations can now identify problems earlier, act faster and continuously optimize experiences based on customer behavior.
Perhaps the most important lesson from this year’s finalists is that AI maturity is about continually leveling up. Several organizations described a deliberate progression from basic automation toward increasingly intelligent, contextual and adaptive experiences.
Many began by simplifying their technology environments, consolidating systems or creating unified platforms. Once those foundations were in place, they expanded into copilots, predictive routing, intelligent automation, advanced analytics and emerging agentic AI capabilities.
This incremental approach allows them to build confidence, prove value and create momentum for future innovation, while also enabling them to prioritize compliance, data privacy and security.
A blueprint for leveling up
The finalists in the 2026 Level Up category demonstrate that AI success comes from applying AI thoughtfully across the experience ecosystem to create better outcomes for customers, employees and the business.
Their approaches differ, but several principles consistently emerged:
- Start with experience challenges, not technology
- Use AI to empower employees and customers
- Connect journeys across channels and touchpoints
- Turn customer and operational data into actionable insight
- Build capabilities that support continuous improvement
Together, these organizations are showing what it means to level up; adopting AI to orchestrate experiences in ways that are more connected, intelligent and empathetic.
As AI capabilities continue to evolve, these finalists are helping define what the future of customer and employee experience will look like — and providing a roadmap for others to follow.
