AWS and Amperity share practical lessons on preparing enterprise data for AI

• 21 Aug 2026
• TM Team
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AWS and Amperity share practical lessons on moving beyond batch processing, connecting known and unknown customer signals, and preparing enterprise data for AI.

Organisations seeking to make faster, more relevant customer decisions should start with focused use cases and build trusted, event-driven data foundations that can support real-time action across the enterprise, according to leaders from AWS and Amperity.

Speaking during the Architecting for Trusted, Real-Time Decisions session at Amperity’s Amplify 2026 conference, Steven M. Elinson, Director, AWS for Travel & Hospitality, and Thomas Koep, Vice President of Customer Strategy at Amperity, outlined how organisations can combine historical customer profiles with live behavioural signals.

Their central message was that real-time personalisation and revenue recovery are valuable starting points, but the larger opportunity is a governed customer context that marketing, operations, customer care and AI agents can all trust.

Why real-time customer context matters now

Travel and hospitality provide a particularly clear view of why real-time customer intelligence is becoming more important.

Elinson said the industry’s historical “look-to-book” ratio had grown from about 10,000 to one to 100,000 to one as metasearch and online travel agencies expanded choice.

In an agentic future, that ratio is predicted to reach one million to one as AI agents search and assemble combinations on consumers’ behalf. At the same time, a customer may have different personas depending on the occasion. Knowing who the person is therefore needs to be combined with an understanding of why they are engaging at that moment.

“It's not just enough to know who the person is; you have to know the occasion and why they're coming to visit you,” Elinson said.

The need is intensified by the perishable nature of travel inventory. An unsold hotel room, airline seat or cruise cabin cannot be held for later, and the lost booking can also remove opportunities for ancillary revenue.

Real-time personalisation and abandoned-cart recovery may provide an immediate commercial case, but Elinson said the more strategic opportunity is eliminating fragmented customer views.

Marketing, operations and customer care often hold different versions of the same traveller or guest. That fragmentation creates inconsistent experiences today and greater risk as AI agents begin making and executing decisions at scale.

“The future requires that we eliminate that and have a single version of truth. Although the revenue recovery pieces we're talking about today are important, it's this second piece, the unified truth, that's going to be most important in the agentic future that's coming,” Elinson said.

AI agents will require access to accurate profile information, the customer’s current journey, sentiment and relevant historical context. A shared, governed customer record allows human teams and AI agents to make informed decisions from the same foundation.