June 2 - 3, 2026
| Free CX Network Webinar Series
Day One - 2 June, 2026
10:00 am - 10:30 am
How a major groceries brand is redesigning customer service at scale with agentic AI
While many organizations have deployed chatbots powered by large language models (LLMs), not many have taken the next step toward agentic customer service. One major European groceries brand is one of the few that has. After rolling out more basic AI capabilities across customer service, the global grocers made a strategic decision to move toward agentic AI - systems capable of handling end-to-end service processes with greater autonomy and personalization.
In this session, we’ll be joined by representatives from the brand to explore how his team is transitioning its customer service and after-sales operations to agentic, with the first live deployments launching in the brand's native Germany. The focus is on high-volume and high-complexity service scenarios where customer frustration is highest and process complexity the most difficult to manage.
The session will also address the realities behind the ambition: navigating fragmented data, managing country-by-country process differences, aligning stakeholders across markets, and managing expectations internally that agentic AI is about improving CX and EX, not replacing people. This is an honest look at what it takes to operationalize agentic AI in a global organization.
Attendees will learn:
- How the grocery retailer is evolving from LLM-based chatbots to agentic AI in customer service and after-sales support.
- The operational and organizational challenges of teaching AI agents complex service processes.
- Key lessons on governance, internal alignment, and build-vs-buy decisions when scaling agentic CX globally.
10:30 am - 11:00 am
The end of segmentation? How agentic AI is enabling true hyper-personalization
The word “hyper-personalization” has been thrown around for years but, until recently, it generally just meant smaller cohorts. Content, special offers and marketing communications are still usually sent to varying cohorts, meaning it can sometimes miss the mark.
With agentic AI, however, true hyper-personalization is possible. AI agents can execute multi-step actions in real-time for each individual customer, optimizing journeys as they go and providing tailored recommendations. It is no surprise, then, that CX Network research found that agentic AI was the second-highest-ranking trends among practitioners, with just under one third of survey respondents stating that they are planning to invest in agentic AI in 2026.
In this session, we’ll be exploring what happens when brands move beyond the static segmentation models of old toward dynamic decisioning systems that can adapt to individual customers during their journeys. Rather than lumping customers into predefined groups, agentic AI interprets context and behavioural signals continuously, adjusting content and offers in real time. We’ll look at the practical and ethical implications of this evolution, asking what does true one-to-one personalization mean for data strategy and trust, and how can organizations avoid over-automation to ensure that this technology enhances customer relationships?
Attendees will learn:
- How agentic AI moves personalization beyond segmentation into real-time, individual-level hyper-personalization
- Which data and experimentation capabilities are required to support true hyper-personalization at scale
- How to balance automation, transparency and trust while delivering finely tailored customer experiences
11:00 am - 11:30 am
Proving ROI on AI investment – measurement, maintenance and stakeholder buy-in
CX Network research found that just under a third of practitioners are planning on investing in agentic AI in 2026, with a further 15 percent saying that they’ll be investing in conversational AI and chatbots, and a further 13 percent on AI and machine learning for business operations. According to Gartner, 77 percent of service and support leaders have reported pressure from other leaders to implement AI. With AI budgets – and AI pressure – on the rise, leaders are often asking “how do we know if this is working?”
In this session, we’ll be answering that critical question, delving into which metrics, tools and collaborators are the most useful when evaluating AI investment. We’ll also discuss how, once this data has been gathered, to best evangelize this information amongst the wider organization, with a focus on internal influencing and story-telling. Finally, we’ll explore how to build safe experimentation frameworks to empower teams to test, fail and reiterate improved AI projects. Using examples from leading brands that are currently focused on this, we’ll explain how make sure AI delivers – and keeps delivering.
Attendees will learn:
- The metrics that prove that your AI deployment is – or isn’t – providing ROI.
- Communicating AI and CX wins throughout the organization to foster collaboration and gain buy-in.
- Nurturing AI sandbox environments to test new implementations safely and create space for innovation in CX.
11:30 am - 12:00 pm
Vendors de-coded: The secrets to successful AI-vendor partnerships
When we asked our network how they acquire new AI capabilities in 2025, 74 percent said they worked with third party vendors. In 2026, however, this has fallen to 50 percent. Yet working with third-party vendors brings a number of benefits: it’s often quicker, easier, cheaper and save hours of internal work that would otherwise be spent developing in-house capabilities.
Decoding the vendor market can feel overwhelming, and working with tech vendors requires a particular skillset. With input from practitioners and consultants, in this session we’ll unpack the build-versus-buy debate, taking an honest look at the benefits – and shortcomings – of each approach, and evaluating their impact. We’ll aim to demystify the AI vendor landscape and illuminate the skills needed to form successful partnerships with solutions providers. Those undecided on build-versus-buy or who are unsure how to find the right tech partner – we’ve got your back!
Attendees will learn:
- The build versus buy argument unpacked: how to know what’s right for your business.
- How to maximize the benefits and mitigate the shortcomings of partnering with third-party solutions providers.
- The essential elements of forming and maintaining successful vendor partnerships.
12:00 pm - 12:30 pm
Back to basics: How to prepare your data for AI deployment
IBM found that concerns about data accuracy or bias is the leading barrier to AI adoption, while CX Network found that creating actionable insights from data is the fourth most significant challenge facing practitioners today. At the same time, CX leaders are under pressure to “do something with AI”, often before their data foundations are ready, which can result in pilots that stall, models that hallucinate and insights that can’t be trusted.
In this session, we’ll return to the data fundamentals. Before deploying copilots, agents or predictive models, organizations must ensure their data is structured, governed and accessible in ways that can support AI at scale. We’ll explore what “AI-ready data” really means in practice, from breaking down silos to addressing quality and ownership. We’ll also examine the cultural and operational work required to embed data discipline across teams, so AI investments are built on solid ground rather than shaky foundations.
Attendees will learn:
- The core characteristics of AI-ready data and how to assess whether your organization meets them.
- Practical steps to improve data quality, governance and cross-functional alignment before attempting to scale AI.
- How strong data foundations reduce risk and increase long-term ROI on AI investments.
