These are just some of the highlights. Watch the full discussion at the end of the article.
AI is not a magic switch
AI promises faster workflows, smarter decisions and more efficient operations, so it’s easy to see why so many companies are eager to adopt it.
But expectations can sometimes move faster than reality.
As Will Dent, CIO at AIThinkers, explained: “Some people rush into thinking AI is going to solve everything. The efficiency and speed you get once you understand the processes can be quite magical, but it takes a lot of work and effort to get to that point.”
The bigger challenge isn’t the technology itself. It’s making sure the right foundations are in place before AI is expected to deliver results.
Start with people, not technology
When people talk about AI, the conversation often starts with tools. The panelists argued it should start somewhere else entirely.
For Andrew Morelock, CTIO at BOND, the first step is making sure teams understand the technology before trying to build it into their work. “I would start by training your team and making sure everyone understands the basics of AI. You can’t run a business on a chatbot, so everybody needs a baseline understanding of how these tools work.”
But understanding AI is only part of the equation. It also depends on having the right data.
AI systems is only as good as the information behind it. Before it can help optimize things like scheduling or crew management, you need accurate, reliable data, along with the habits and processes needed to maintain it.
Clean data rarely gets the same attention as AI itself, but it’s often what separates meaningful results from costly mistakes. Get it right and AI can help improve decision-making. Get it wrong and small issues can quickly snowball.
Change attitudes before changing ways
Even with the right technology, data, and training in place, change doesn’t happen overnight.
As Dudley King, Founder & President of FlightBridge, put it: “Everybody knows that people don’t like change, even change for the better. You could have the best systems, but if somebody is used to picking up the phone and calling the FBO, it doesn’t matter how good your software systems are.”
That resistance isn’t a reason to avoid new technology. It’s a reminder that adoption takes time. Leaders need to help their teams build confidence, learn new workflows and get comfortable with a new normal before they can expect lasting change.
Technology works best with human expertise
Part of the hesitation around AI comes from a simple question: what happens to the humans?
It’s an understandable concern. But for most people, AI isn’t changing who does the work. It’s changing how the work gets done. Rather than replacing expertise, it’s helping teams spend less time on repetitive tasks and more time on the parts of the job that require experience and judgment.
That’s also why expertise remains such a big part of the equation. When asked how companies can feel confident in the output from AI, Will said: “First and foremost, you have to check the work. Domain expertise is key. You don’t replace the experts, but you enable the experts with technology.”
In other words, AI still depends on people who understand the business. That’s why the panelists encouraged people to focus less on having all the answers and more on building a culture of learning, as those who get the most out of AI will likely be the ones willing to learn, experiment, and adapt as they go.
After all, AI isn’t something that’s coming. As Andrew put it: “AI is not the future, it’s the today.”
The Node Talks panel, Building the tech foundation for tomorrow, was moderated by Alex Hanrahan, Senior Product Manager at Avinode Group, and featured the panelists:
Will Dent, CIO at AIThinkers
Dudley King, Founder & President of FlightBridge
Andrew Morelock, CTIO at BOND