AI in travel

From 1980s yield management to real-time models: how AI demand forecasting travel pricing actually predicts peak fares today

Architecture of SAP Concur AI agents, real-world expense automation scenarios, and integration with corporate systems — from API to practical implementation cases.

How companies cut business travel carbon footprint by 40% without hurting operations: practical tools, calculations, and case studies for travel managers.

How AI agents reduce travel expense reporting time from 45 minutes to 2 minutes per trip. We examine the technologies, real-world cases, and step-by-step implementation plan.

How AI calculates the carbon footprint of business trips and suggests routes with minimal CO2 emissions. Analysis of algorithms, data, and real cases for travel managers.

We break down methods for calculating the carbon footprint of business travel, compare AI tools for Scope 3 reporting, and show how to automate ESG metrics in corporate travel.

AI agents now handle business travel expenses end-to-end: from pre-booking to closing reports. Learn how this technology is transforming travel managers' work today.

How artificial intelligence helps travel managers cut CO₂ emissions by 25–40% through route optimization, supplier analysis, and demand forecasting.

We examine specific travel management tasks that AI automates today: from booking to policy control. Real cases and savings metrics for 2025–2026.

Artificial intelligence algorithms analyze millions of flight combinations and find routes that traditional GDS systems miss. Learn how this technology works.