The AI Playbook Is Not a Tech Playbook

The companies winning at AI in travel are not the ones with the best models. They are the ones that treat AI as a transformation of how they work, not just what tools they use.

I have seen the opposite pattern too many times. A travel company announces an AI initiative. A team is assembled. A vendor is selected. A pilot launches. And somewhere between the pilot and the rollout, momentum stalls. Not because the technology failed, but because the organization was not ready for what AI actually demands.

The culture gap is the real gap.

When I co-created the Skift Data + AI Summit, one of the most striking themes was how few organizations had addressed the cultural dimension of AI adoption. Leaders were asking the right technology questions: which models, which data architecture, which vendors. Almost nobody was asking the harder ones. How do we retrain our workforce? How do we restructure our teams? How do we build organizational patience for something that does not deliver ROI in the first quarter?

The companies that have moved from "AI-curious" to "AI-native," as my co-author Mayank Gandhi and I described it, share three characteristics. First, they invested in building AI literacy broadly, not just in the data science team but across commercial, operations, and leadership functions. Second, they restructured to put data and AI at the center rather than treating it as a support function. Third, they accepted that the transition takes years, not quarters.

Democratization is not a feature. It is a strategy.

One of the convictions that has shaped my career is that the power of data and AI should not be reserved for the largest players. At Expedia Group, the vast majority of properties globally had no access to meaningful revenue management technology. The industry's most sophisticated tools were designed for and priced for large chains. Everyone else was making pricing decisions on instinct.

We built solutions that were accessible by design: intuitive interfaces, embedded insights, recommendations that did not require a revenue management degree to interpret. The result was adoption at a scale the industry had not seen. But the real breakthrough was not the technology. It was the mindset shift: believing that a 50-room independent hotel deserves the same quality of data-driven decision-making as a global chain.

Five questions every business must answer.

After the inaugural Skift Data + AI Summit, I synthesized five questions that I believe hold up across every advisory conversation:

1. Is your data ready? AI is only as good as the data it is trained on. Most travel companies have significant data quality challenges that must be addressed first.
2. Are you thinking multimodally? Text-based AI is table stakes. The real opportunity is in combining text, image, voice, and behavioral data.
3. How is your organization structured? If data and AI report through IT, you have already made a strategic choice, and probably the wrong one.
4. Are you being intentional about data ethics? Travel companies hold deeply personal data. How you steward it is as important as how you monetize it.
5. What is the cost of waiting? Every quarter you delay, the gap between you and your AI-forward competitors widens.

So what should you do?

If you are a CEO or board member, start with culture, not technology. If you are a mid-career leader, invest in your own AI literacy now. If you are an investor, look beyond the tech stack and ask how the portfolio company is changing how its people work.

The AI playbook is not a tech playbook. It is a people playbook, a culture playbook, and a patience playbook. The companies that understand that distinction will win.