AI agents that learn: How to build systems that continuously improve themselves
Empower your teams to build AI Agents that learn from every interaction, autonomously adapt, and continuously improve without manual retraining.
RegisterIn a survey conducted by CX Network, 40 percent of CX leaders are planning to increase their spending on Agentic AI / AI Agents in 2026. However, 35 percent mentioned that demonstrating ROI is one of the main obstacles they’re currently facing.
Enterprises are racing to deploy AI Agents across customer service, marketing, and operations—but most systems plateau shortly after launch. As AI footprints grow, so does the operational burden required to maintain them.
The next wave of enterprise value will come from AI Agents that don’t stagnate—systems that learn from every interaction, adapt autonomously, and continuously improve while maintaining full governance and a human-in-the-loop.
Join us to learn:
- How to leverage real-time feedback loops to enhance routing accuracy, shorten resolution paths, and increase first-contact resolution
- What you need to design truly self-learning, outcome-driven AI Agents
- AI-powered workflows that automatically adjust without manual intervention or constant retuning
Speakers include:
Georgina Wilczek
Event Host
CX Network
Gemma Treadwell
Head of Customer Experience
A.P. Moller - Maersk
Tobias Braun
CCaaS Solution Specialist
Sprinklr
Tobias Braun is an energetic and passionate solutions consultant with experience in mapping business problems and technology into workable solutions in the Enterprise Software, Artificial Intelligence (AI) and Contact Center sector.
Sebastien Salou
Director EMEA, Solutions Architects
Sprinklr
Sponsored by
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