Enterprise AI Deployment Checklist

01Define the first surface

Resist the platform-wide rollout. The fastest path to value is one high-leverage surface with a clear owner and a single measurable outcome — an app upsell slot, a disruption-rebooking flow, or a call-center assist.

Write the success metric down before anything else: conversion, attach rate, handle time, or revenue per session. If you can't name the number, you can't prove the project.

02Confirm data & integration readiness

List the source systems the surface needs — reservations, loyalty, content, operational state — and confirm read access and freshness for each. Identify how a traveler is recognized across them.

Decide early whether the surface needs write-back (booking, redemption) or read-only recommendations; the former raises the integration and governance bar.

03Clear security & governance up front

Engage security at the start, not at procurement. Confirm deployment model (VPC, SSO), data handling, logging, and the commercial and regulatory rules every recommendation must respect.

Define guardrails: what the system may offer, what it must never promise, and when it escalates to a human.

04Scope a measurable pilot

Run on a slice — a route, a segment, a percentage of traffic — with a holdout group so lift is attributable, not assumed. Keep it short enough to learn and long enough to reach significance.

Instrument everything: inputs, decisions, actions, and outcomes, so results survive scrutiny from revenue management.

05Measure, then scale

Review against the metric you wrote down. Expand surface by surface as lift and trust accumulate, reusing the same reasoning layer instead of rebuilding per channel.

Each new surface gets cheaper, because the integration and governance work is already done.

06See it on your stack

Globaleur is the reasoning, personalization, and commerce layer for travel enterprises — integrated alongside the systems you already run. Request a demo and we’ll map a phased rollout for your team.