Artificial intelligence is reshaping how we travel, shop, and work, but it’s also exposing a hard truth: most AI systems are only as good as the data that powers them.
Clean data ensures AI models make accurate, trustworthy decisions. Without reliable, connected data, AI amplifies errors instead of solving them, leading to poor predictions and loss of consumer trust.
That tension came through clearly in Business Insider’s recent article, Planning a Vacation Was Already a Nightmare. Then Came AI. The piece explores how AI is transforming travel, from real-time pricing models to predictive trip planning, while also introducing confusion and skepticism. Travelers now find themselves wondering whether the “smart” systems serving them are designed to help them save money or to help companies make more of it.
As Andy Frawley, CEO of Data Axle, explained in the article, “You need foundational data for any of these LLMs to work or any AI, and how do you provide the most clean, standardized, complete, accurate set of data for the models to train off of?”
AI doesn’t fix bad data, it magnifies it. Companies think they have an AI challenge, when in reality they have a data challenge.
That insight applies to more than just airlines and hotels. Across industries, organizations are discovering that AI doesn’t solve data problems, it amplifies them.
“AI doesn’t fix bad data, it magnifies it,” Andy says. “Companies think they have an AI challenge, when in reality they have a data challenge. If the data isn’t accurate, complete, and connected, even the smartest model will make the wrong call faster.”
The same fragmentation travelers encounter in booking systems exists across every sector, from marketing databases, hospital records, financial CRMs, to supply chain inventories. Each contains pockets of high-value information that rarely speak the same language.
Recent research shows just how widespread the issue is:
These findings point to a shared vulnerability: AI models are accelerating faster than the infrastructure supporting them. The data feeding these systems is often outdated, incomplete, or duplicated undermines accuracy, personalization, and ultimately, trust.
What’s happening in travel is a microcosm of a much larger shift. The same forces driving dynamic ticket pricing or personalized itineraries are influencing everything from medical diagnostics to media recommendations. The question is no longer what AI can do, but whether it’s doing it well, and for whom.
In marketing, poor data quality means wasted spend and missed audiences. In healthcare, it can translate into misdiagnoses. In financial services, it can increase exposure to fraud. In each case, the risks compound when organizations lack unified, identity-resolved data.
As Andy puts it: “AI thrives on context. The ability to connect signals, to know that the same individual who searched for a family trip also booked a rental car, or that the same business showing intent signals online just updated its physical location, is what turns automation into true intelligence.”
Trust, not technology, will define the next phase of AI adoption. According to Gartner, by 2027 over 40% of AI-related data breaches will stem from misused or poorly governed data, often across borders (Gartner, 2025). That’s a governance problem, not a modeling one.
Clean, connected data is the antidote. When companies can verify where data comes from, how it’s updated, and how it links to real people or entities, AI becomes not just more accurate but more accountable. It turns opaque automation into transparent intelligence.
AI’s future isn’t about more algorithms. It’s about better ecosystems, where data flows seamlessly, securely, and with integrity.
At Data Axle, we see this as the foundation of ethical AI, one where models are trained on data that’s standardized, responsibly sourced, and reflective of real-world relationships.
“AI’s future isn’t about more algorithms,” Andy adds. “It’s about better ecosystems, where data flows seamlessly, securely, and with integrity. That’s how you earn trust at scale.”
The organizations that win in the age of AI won’t simply deploy the most advanced models, they’ll build the most reliable data foundations. Clean data enables models to learn faster, automate responsibly, and deliver insights that actually make sense in context. It bridges automation with human relevance.
In travel, that might mean anticipating a traveler’s needs before they articulate them. In retail, it might mean recognizing a customer across devices and interactions. In B2B, it means connecting the dots between decision-makers, buying signals, and organizational intent.
The common thread is precision. When the data is right, AI doesn’t just act, it understands.
AI is redefining every industry, but the winners won’t be those who adopt it first. They’ll be the ones who power it best, with data that’s complete, connected, and clean.
Read more in Business Insider’s full article: Planning a Vacation Was Already a Nightmare. Then Came AI
Courtney is a seasoned communications and public relations professional with 17+ years of experience working in both the public and private sectors in diverse leadership roles. As Data Axle’s Senior Public Relations Manager, she is intently focused on elevating the company’s media relations presence and increasing brand loyalty and awareness through landing coverage in top-tier media outlets.