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Agentic AI: Revolutionising Business Travel for Sustainability and Productivity

By James Dent, Chief Strategy & Sustainability Officer
& Niclas Stoltenberg Chief Technology Officer 

Introduction: What is Agentic AI?

Agentic AI (or Generative AI agents as they are also known) is a paradigm shift in artificial intelligence, instead of using AI to optimise a tech stack, the agents are the tech stack. By integrating LLMs (Large Language Models [Chat GPT]) with dynamic process domain models, Agentic AI goes beyond RPA’s (Robotic Process Automation) rule-based automation. AI agents can orchestrate complex, adaptive workflows that enhance productivity and sustainability in business travel. This allows for real-time decision-making and continuous process improvement, directly aligning with sustainability goals.

 

Transforming Business Travel: Smarter, Lower Emissions, and More Cost Effective

Agentic AI offers businesses the ability to automate and optimise travel management, streamlining processes that traditionally required manual intervention. Through its ability to evaluate dynamic pricing, availability, and the environmental impact of different travel options, AI agents can recommend itineraries that not only save money but also reduce emissions.

 

By integrating with calendar systems, AI agents can align travel with meeting schedules, ensuring that trips are necessary and efficient. 76% of global travellers said they look for travel apps that reduce the friction and stress of travel. With Agentic AI this whole planing and booking process can be completed, within the constraints of policy, budget, personal preferences and sustainability parameters, in one click. The result is a more streamlined travel process that boosts productivity as well as the traveller experience.

 

Cost Savings and Sustainability Through Lowest Logical Emissions

One of Agentic AI’s most compelling features is its ability to recommend travel options that offer the  Lowest Logical Emissions (LLE). This means it evaluates travel routes based on both cost and environmental factors, ensuring that companies choose the most sustainable option available without compromising on practicality or efficiency.

 

For instance, AI agents can suggest high-speed rail travel over short-haul flights when it results in significantly lower emissions. They can suggest route specific airline options based on the most efficient aircraft. It’s true that we could do this now, but if appropriately built AI agents are equipped with sophisticated algorithms to evaluate different options, balance trade-offs, and effectively respond to novel situations; ie allow a traveller to decide on the optimal method of transport given a set of variables. The major tech travel companies have been resistant to implement simple and effective sustainability product features for travellers, even though 76% of travellers want to see more sustainable options in the booking process. By using real-time data and analysing available travel options, it ensures businesses reduce their Scope 3 emissions—those indirect emissions from business activities such as travel.

 

Example Scenario

A SaaS tech company and the sales leadership team will attend SaaSr in San Francisco, USA.

Travellers: VP Sales - London Office, Head of Partnerships - London Office, Head of EMEA - Berlin Office

Tech Travel Company Work-Flow

Step 1
VP Sales informs the EA to make necessary arrangements. 

Step 2 
EA Slacks Head of Partnerships + Head of EMEA + VP Sales to understand trip preferences.

Step 3
EA starts to explore possible options on a booking platform

Step 4
EA manually attempts to find options based on dates, company policy, each traveller location, traveller preferences, cost, speed and Lowest Logical Emission (if available on the platform)

Step 5
EA creates draft trips for each traveller

Step 6 
EA sends 3 Slack messages and each reviews their trip

Step 7 
Travellers confirm booking via Slack

Step 8
Booking sent for approval to the 3 travellers

Step 9
Trip Booked

Agentic AI Work-Flow

Step 1
VP Sales informs the EA to make necessary arrangements. 

Step 2
EA creates calendar invites 

Step 3
AI Agents interpret 

    • Calendar invite
    • Trip dates + location
    • Travel policy
    • Traveller location
    • Traveller preferences
    • Trip cost
    • Trip time
    • Lowest Logical Emissions

→ booking generated

Step 4
Trip Booked

The Future of Business Travel

Agentic AI is set to revolutionise how companies manage business travel by delivering sustainability, efficiency, and cost savings all at once. With its capacity to suggest the Lowest Logical Emissions routes, integrate with calendar systems for smarter planning, and optimise costs.

 

 

For companies aiming to meet their net-zero commitments, reduce operational costs, and increase productivity, adopting Agentic AI will be essential. This technology not only enables businesses to streamline travel processes but also fosters a more sustainable and efficient way of working in the modern world.

 

 

References:
  1. ICAO, DEFRA, EPA Reports on Aviation Emissions Methodologies.
  2. Bernard Marr (2024), “Agentic AI: The Next Big Breakthrough That’s Transforming Business and Technology”.
  3. CDP (2022), Carbon Brief (2016).
  4. McKinsey & Company (2020), Transport & Environment (2023).
  5. Science Based Targets Initiative (SBTi) (2021).
  6. Masterman, T., Besen, S., Sawtell, M., & Chao, A. (2024). The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey. arXiv.https://arxiv.org/pdf/2404.11584
  7. Stroman, A. (2023). Generative AI agents will revolutionize AI architecture. InfoWorld.https://www.infoworld.com/article/2337474/generative-ai-agents-will-revolutionize-ai-architecture.html
  8. Marr, B. (2024). Agentic AI: The next big breakthrough that's transforming business and technology. Forbes.https://www.forbes.com/sites/bernardmarr/2024/09/06/agentic-ai-the-next-big-breakthrough-thats-transforming-business-and-technology/

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