Rail travel is not standardized across different countries. Customer expectations, terms and conditions, service levels and ticket types vary massively across different localities. This is difficult for non-domestic travellers; most train companies design apps, websites and journeys for the domestic traveller, making several assumptions about base knowledge along the way.

In this session, we'll explore how a global travel tech company has deployed AI to enable the team to unify CX worldwide while keeping down operating costs. AI is fed common customer queries and answers by a dedicated team that constantly monitors and reviews the deployments. Critically, the company hasn't lost sight of the key elements of service that need to remain in human hands. Agent hiring is highly selective: agents are truly experts in their fields and take pride in their work. High retention rates reflect this, with several agents having been with the business for more than 25 years.

In this session, our expert speaker will join us to explain why the organization chose AI as the best way to unify global CX without losing sight of the value of human interaction in customer service.

Attendees will learn:

• Key use cases for AI in customer service in a global operation, and how to get stakeholders on side.
• Where AI fits into a robust customer feedback loop that builds trust with customers and drives experience improvements.
• Navigating AI implementation while maintaining a good agent experience and aiding contact center retention.

Chatbots are one of the fastest adoption stories in tech history, with use cases rare as recently as 2020 where they are now everywhere one looks. Generative and agentic AI chatbots can standardize CX, create cost savings and streamline customer journeys while retaining brand identity and warmth. In fact, more than two-thirds of CX organizations believe that gen AI can help to create warmth and familiarity in service and 69 percent believe it can actually humanize interactions. Despite this, when we asked our community where customers encounter generative AI during a typical journey, the number one and two most popular responses were 'generative bots in support' and 'we do not currently use generative AI'.

In this session we'll unpack where this adoption gap comes from, addressing common concerns and roadblocks to capitalizing on generative and agentic chatbots in customer service. We'll explore real-world case studies, looking at what worked well and sharing key learnings to equip attendees with an action plan for deployment.

Attendees will learn:

• Use cases for generative and agentic AI chatbots in customer service and where to find the quickest wins
• Measuring the success of AI deployments in customer service and how to collaborate with your customers to improve
• What next? Using AI interaction data to close the loop and improve overall customer journeys

The rise of AI workforce management (WFM) that uses predictive analytics to anticipate call volumes and align staffing with demand to reduce over- and under-staffing is, in many ways, a huge leap forward for contact center leaders, who used to have to do it manually. Features such as self-scheduling, shift bidding and overtime volunteering give agents more flexibility (something 9 out of 10 agents say is important when choosing a job) and free up managers to focus on strategy and agent engagement. Despite this, more than 40 percent of contact centers still don't use WFM technology. Advancements in AI for customer service further complicate things. Many interactions are now automated but the fact is that contact centers still need agents to run, with several now-infamous cases of companies trying to replace all of their agents only to rehire them shortly after.

In this session we'll walk through the ways AI-powered WFM technology can help alleviate the pressures of manual scheduling while accounting for the increase of customer-facing AI. We'll look at the key challenges facing contact center leaders in the age of the AI revolution and identify where WFM technology can help.

Attendees will learn:

• A blunt examination of current workforce management challenges facing contact center leaders today
• How to identify which AI-powered WFM tools will help alleviate stress and free up managers to focus on strategy and engagement
• How to leverage AI WFM tools to increase agent engagement and reduce turnover

Most organizations still treat the contact center as a cost center to be minimized but leading brands are flipping the script, using customer interactions and contact center data as a source of revenue and business-critical insights.

• How to reframe the contact center's role from cost center to growth center
• The KPIs you need to track to link CX with revenue and retention
• Real examples of turning service interactions into loyalty and advocacy