As generative and ML systems are involved in more customer touchpoints, responsible AI isn’t just a governance checkbox but a business imperative. With CX Network research finding that 43 percent of consumers expressed concern around AI ethics.

This session pairs insights from retail and regulated healthcare ecosystems to illuminate how responsible AI strategies differ by context, from mitigating bias in recommendation systems to building compliant and customer centric data governance strategies. Our speakers will explore where bias creeps in, how to define appropriate guardrails, and why responsible design must be embedded into product and operational lifecycles from the beginning.

Attendees will learn:

• What responsible AI really means in practice beyond high level principles.
• Approaches for embedding compliance and transparency into customer facing systems.
• How to balance rapid innovation with risk mitigation in diverse industry contexts.

73 percent of marketing teams now use generative AI regularly as teams look to boost efficiency and creativity across campaigns. Despite budget pressures, with marketing budgets tightening in many industries, generative AI enables teams to produce relevant content faster, increase personalization at scale, and deliver campaign insights to the wider team that were previously very labour intensive.

In the world of sales, generative tools are helping break down barriers between marketing and sales teams. By automating routine tasks such as lead qualification and content creation, companies who adopt can see measurable impact on performance.

In this session, we’ll be discussing the benefits of generative AI in sales and marketing, what to look for when partnering and how to ensure successful implementation and integration.

Attendees will learn:

• How generative AI is transforming marketing workflows from campaign creation to omnichannel personalization that resonates with users and drives conversions.
• The evolving role of generative AI in sales enablement, including how automated content, outreach and data driven insights can align sales and marketing teams for better results.
• Practical strategies for balancing automation with human oversight, ensuring brand voice consistency and responsible use of customer data as part of your broader CX strategy.

CX is entering a new phase where not all “customers” are human. So-called machine customers – AI systems that act autonomously on behalf of individuals or organizations – are beginning to search, purchase and address customer support without direct human involvement. Some are predicting that by 2030, machine customers will be responsible for 20 percent of revenue, which could fundamentally reshape how brands design CX and engagement models.

In this world, CX is no longer just about emotional connection or intuitive interfaces, it’s about machine-readable trust. Brands must optimize experiences not only for people, but for AI agents that prioritize speed, accuracy, transparency, and outcomes. Organizations failing to adapt to machine customers risk losing relevance and CX leaders may need to rethink everything from discovery and personalization to governance, consent, and brand differentiation.

In this session, we’ll look at the advent of machine customers, exploring the impact they could have on customer engagement and loyalty, and discussing strategies for businesses to stay ahead.

Attendees will learn:

• What machine customers are, why they’re emerging now, and how AI-to-AI interactions will reshape CX and commerce over the next decade.
• How to design customer experiences, data structures, and trust signals that work for both humans and autonomous AI agents.
• The strategic implications for personalization, pricing, loyalty, and brand differentiation when purchasing decisions are increasingly automated.

At the world’s largest online retailer, agentic AI isn’t a buzzword, it is a reality. In this case study, Rajesh Sura, Head of Data Engineering and Analytics for North America Stores at Amazon, will break down how he and his team moved beyond rule-based automation to build a multi-agent orchestration framework to transform vendor experience.

We will look at the conversational BI agents and fully autonomous dispute-resolution agents that proactively spot and resolve issues with zero human intervention resulting in faster resolution times, personalized recommendations for vendors and hundreds of thousands of hours of work saved for internal teams.

We will hear how Rajesh and his team designed an explainable agentic ecosystem, keeping humans in the loop at critical points. We will also unpack how AI can identify shipping inefficiencies and personalized marketing strategies, allowing vendors to act with a single approval click.

Attendees will learn:

• How to design and implement multiple AI agents to solve complex, high-volume challenges with minimal human intervention.
• Ways to combine personalization at scale with explainable AI to secure trust and adoption.
• The governance and access-control considerations organizations must consider before deploying agentic AI.