How AI Automation Is Changing The Landscape Of Travel Industry?

New Delhi: Artificial intelligence is increasingly redefining the travel industry’s operating model, with companies turning to automation to reduce costs, improve turnaround times, and build leaner, more scalable businesses. The shift marks a departure from the traditionally manpower-intensive approach that has long dominated travel planning and booking services.

Against this backdrop, Delhi-based HECT India Private Limited is betting on automation to build a leaner, more scalable travel business—challenging the conventional service-heavy framework.

The bootstrapped company, which spent nearly a decade in offline conferences and event management, has restructured its operations to deploy a proprietary AI ecosystem focused on India’s middle-class travel segment. The shift marks a transition from a service-led setup to a product-driven platform, underpinned by a cumulative technology investment of ₹18 crore.

Automation as a cost lever

At the core of HECT India’s transformation is a clear thesis: automation can significantly compress operational costs in a high-volume, low-margin industry.

The company has invested approximately ₹7 crore in the current fiscal year alone to build systems that automate itinerary planning, pricing analysis, and multi-vendor bookings. These functions—traditionally dependent on large teams—are now being executed through machine learning models and integrated workflows.

According to the company, this automation-first approach has already helped it avoid over ₹100 crore in potential operational expenses, highlighting the growing role of AI in replacing repetitive, coordination-heavy processes.

“The travel industry in India has historically relied on manpower-heavy operations, which increases turnaround time and cost inefficiencies,” said founder Gaurav Sharma. “Automation allows us to build a lean operational structure that can scale without a proportional increase in headcount.”

From legacy operations to AI-led infrastructure

Founded in 2015 as a B2B events and conferences firm, HECT India’s pivot in 2025 represents a structural overhaul rather than a surface-level digital upgrade. The company has leveraged a decade of domain data—from vendor negotiations to travel logistics—to train its AI systems on real-world patterns specific to Indian consumers.

This transition also reflects a broader trend among small and mid-sized enterprises: replacing human-led coordination layers with algorithmic decision-making to improve efficiency and margins.

Building a full-stack, AI-driven platform

HECT India is now preparing to launch an integrated travel platform that consolidates flights, hotels, buses, and tour bookings within a single interface. A key feature is a conversational AI layer designed to function as a virtual travel consultant—capable of evaluating itineraries in real time based on pricing dynamics and logistical feasibility.

The company’s focus on middle-class consumers, particularly from tier-2 and tier-3 cities, aligns with the current demand surge in domestic travel. By combining automation with cost sensitivity, the platform aims to deliver faster decision-making and lower price volatility.

Competitive pressure in an AI-first market

However, HECT India’s push into AI-led travel comes amid intensifying competition. Established players such as MakeMyTrip and global platforms are rapidly integrating generative AI into their ecosystems, leveraging scale and extensive datasets.

For a bootstrapped player, the challenge will be differentiation—particularly whether its proprietary AI systems can deliver superior cost efficiency and personalisation without the marketing muscle of larger incumbents.

A test case for lean digital transformation

HECT India’s transition underscores a larger shift underway in the travel sector: from labour-intensive service models to automation-driven, lean operations. As the company moves closer to its platform launch, its performance may serve as a bellwether for how smaller firms can compete in an increasingly AI-native marketplace.

If successful, the model could offer a replicable blueprint for MSMEs seeking to reduce overheads while scaling through technology rather than workforce expansion.

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