A Smarter Approach to AI Adoption in Hospitality and Travel

Artificial intelligence is no longer an emerging conversation in travel technology. It is an active line item in every executive budget discussion. Yet amid the rush to deploy AI features, chat interfaces, and automation tools, a quieter question is surfacing in boardrooms: Which AI investments will actually endure?

Across the hotel and travel ecosystem, the pressure to innovate is intensifying, on track to grow to $75.66 billion in 2030 at a compound annual growth rate (CAGR) of 29.9%. In fact, according to Deloitte’s 2025 Travel Industry Outlook, more than 70% of hotel executives are prioritizing AI investment. 

At the same time,  a recent survey reported that  56% of hospitality respondents say AI accuracy needs much improvement before it can be fully trusted, and only 28% of hospitality/travel respondents qualify as “AI leaders.”

These data points frame the central tension facing the travel industry: enormous potential, but fragile foundations.

For DerbySoft, the response has not been to chase the latest AI headline. Instead, the company is pursuing a disciplined approach designed to balance urgency with caution — embedding AI where it meaningfully improves travel commerce operations rather than layering it on as a marketing flourish.

The Cost of Moving Too Fast

Travel distribution is not a laboratory environment. It is a live, revenue-critical ecosystem where inaccurate rates, mismatched content, or misapplied automation can immediately impact conversion, margins, and brand trust.

A Skift Research report found that AI is expected to reshape travel planning and operations significantly, but executives remain cautious, citing integration complexity and uncertain ROI as primary concerns.

The caution is well-founded. Hotels and distributors already operate within highly interconnected systems;  CRS, PMS, channel managers, distribution networks, and content feeds. Introducing unvalidated AI tools into this environment can create fragmentation rather than efficiency.

DerbySoft’s strategy reflects this operational reality. Rather than releasing “dime-a-dozen” AI products to match competitive noise, the company is prioritizing:

• Customer validation before productization

• AI features that solve measurable business problems

• Integration into existing operating models

• Responsible adoption that reduces risk of rapid obsolescence

This philosophy aligns with DerbySoft’s broader messaging: move steadily, integrate thoughtfully, and position AI as part of a larger travel operating model.

The ROI Imperative

Executives today are not asking whether AI is transformative. They are asking whether it pays.

According to PwC’s Global AI Study, AI could contribute up to $15.7 trillion to the global economy by 2030, with significant value driven by productivity gains and product enhancements. Yet enterprise leaders increasingly require proof of ROI before scaling investments. An IBM Institute for Business Value report found that only 25% of AI initiatives deliver the expected ROI at scale.

This skepticism is particularly strong in hospitality, where margins are tight and technology budgets must justify measurable performance improvement. The market is not looking for more fragmented AI tools. It is looking for a trusted, integrated AI platform that supports the broader travel commerce ecosystem.

Executives are wary of deploying multiple isolated AI utilities that create operational silos. They want:

DerbySoft’s expansion plans,  including AI mapping enhancements and rate parity tools,  reflect this integrated philosophy. These capabilities are designed to improve efficiency and accuracy behind the scenes, strengthening distribution confidence rather than simply generating AI-themed headlines.

Competing on Substance, Not Storytelling

In an increasingly crowded AI landscape, many competitors are leading with bold narratives about transformation. Chatbots, copilots, predictive dashboards, and generative content engines dominate conference panels.

DerbySoft’s differentiation lies in restraint.

By validating customer demand before development and embedding AI within core workflows, we position ourselves as a trusted partner rather than an experimental vendor. The focus remains on solving structural problems in travel commerce; rate accuracy, content consistency, distribution confidence, and conversion optimization.

This measured approach may not generate the loudest announcements, but it addresses the long-term question that matters most:

Will this AI still be valuable five years from now?

The Emerging Standard for AI in Travel

Travel technology is entering the next phase in AI adoption.

The companies that succeed will likely share three characteristics:

1. They treat data quality as foundational.

2. They integrate AI into operating models rather than layering it on top.

3. They align innovation with measurable business outcomes.

DerbySoft’s current trajectory is positioning itself within this emerging standard.

At a time when AI initiatives are being defined by urgency, restraint may prove to be a competitive advantage.

AI will undoubtedly reshape travel commerce. The question is not whether to participate. It is how to participate responsibly.

For DerbySoft, the answer is clear: move carefully, validate rigorously, integrate deeply, and build AI that earns trust, not just attention.

About the Author

Duane Overgaard is the Divisional CEO, Hospitality,  of DerbySoft. With over 30 years of experience in the hospitality industry, he has a diverse skill set that includes account management, business development, and contract negotiation. Duane has held various leadership positions at renowned companies such as Sabre Corporation, Wyndham International, and Hilton Hotels & Resorts, where he has demonstrated expertise in hotel management and marketing strategy. He is known for his strong team-building and competitive analysis skills. Duane is currently based in the Dallas area of the United States.