When technology leaders ask me where an AI strategy should begin, my answer often surprises them: start from the beginning. I work with organizations across multiple industries, and the principle holds in each. Aviation offers a good look at why. Modernizing an airplane today is a multi-year effort; with the right foundation in place, I have seen it compress to under 12 months.
That foundation is documentation. Aviation is a mature industry, and it has evolved considerably over its lifetime. In my work helping airlines and manufacturers modernize, a crucial part of the process is reviewing the records from each upgrade across a five-, ten-, or twenty-year span. Incorporating AI into the tools and processes means accounting for documentation that reaches back to the 1970s: paper files first, then Excel and the early days of computing. Only from that base can an organization move confidently into the digital realm.
There are no shortcuts. The work has to start from the beginning.
The Digital Thread
The biggest hurdle is history. To upgrade an airplane, even a single component of one, engineers must understand every step that brought it to its current state.
This is where the digital thread becomes crucial: it ties together all the years of an aircraft’s evolution. With a digital thread and AI incorporated, an engineer could simply say, “Talk to me about the upgrade that went into play in 1998,” and the system would surface the technology involved, what was put in place, and any failures that occurred along the way. The entire history would be available on demand.
The current reality is harder to believe: much of that history lives on paper, and organizations often have to track down the people who did the original work. That is why the digital thread has become such a significant topic, and why its relevance extends well beyond the aviation industry into manufacturing at large.
Watch Out for the Know-It-Alls
When enterprises select an AI technology integrator, the first thing to watch for is the know-it-alls. That may sound counterintuitive; confidence and deep expertise are precisely what organizations look for in a partner. But confidence is not the same as understanding the business.
Working with organizations across multiple industries has taught me a consistent lesson: every company, even within a single industry, operates differently. Each one has evolved its technology, from the moment software first entered the business. So when an integrator arrives claiming to know the path from A to Z, it should give leaders pause.
Successful projects begin with both sides committing to an enormous amount of discovery. The work is monotonous and demanding, but when both parties invest in it, the project becomes far easier. In practice, the integrators worth trusting share a few traits:
- They invest up front. Rather than billing for discovery from day one, they commit their own time and funding.
- They admit what they don’t know. A strong partner will say, “We don’t know what we don’t know, and we’d like to really pull back the curtain of your technology organization.”
- They do their homework. An integrator who arrives without having researched the organization’s technology, history, and evolution has not earned the conversation.
- They ask before they prescribe. They may arrive with ideas about how to help an organization modernize, but the discipline is to hold those ideas and ask questions first. The ideas can then evolve based on the answers.
Don't Lose The North Star
An AI partnership succeeds over the long term when both parties keep their eye on the North Star. Whatever the organization, whatever the industry: as companies form and evolve, their leaders originally set out to accomplish a goal. They wanted to build something or to provide a service. The North Star cannot be lost as the work moves into the AI realm and proofs of concept begin taking shape. This becomes difficult in large enterprises, where individual business units can operate like companies of their own.
The responsibility goes both ways. An organization must hold onto its North Star, and the integrator must never push down a road that diverges from it; alignment has to be maintained deliberately. It might seem simple, but teams sometimes complete these projects only to ask, “Why did we do this?” That is what drifting from the North Star looks like.
Where AI Stands in Aviation Right Now
Aviation is among the more challenging industries for AI, and productively so, because a great deal must be taken into account: the operational reality that the plane has to fly, safety, security, and the fact that transportation crosses country boundaries and affects the entire world. Meanwhile, a tremendous amount of data moves through these machines.
The central question I hear from aviation leaders is this: how can an agentic system maintain the correct data processes? Without a process, and without AI tooling that builds rock-solid guardrails, an organization will find itself in trouble. That is why many leaders in this space remain hesitant.
The way through that hesitancy is deliberate sequencing. Today, my teams deploy AI processes and systems inside the internal environment, where they prove themselves against real operational work before earning access to more. What sits beyond that line is the most sensitive flow in aviation: a plane generates vast amounts of data whether in flight or not, tracking the health of the machinery and the movement of the aircraft, and that data flows to the customer environment. AI earns its way to that flow through demonstrated reliability, the same way any system in aviation earns trust.
The Human Side of AI Transformation
A question every leader faces is how to address AI concerns with honesty, while still building confidence in the future. It comes down to frequency: honesty here is less about a single difficult conversation than about consistent ones. What is encouraging is that leaders want to engage; I see it in forums and in conversation constantly. But it needs to happen at an even higher cadence. AI cannot come up over dinner or in a passing chat, then vanish from the conversation for two months. The dialogue cannot lapse.
The same holds for the relationship between an organization and its integrator; that, too, is sustained by honesty. Once a partner has earned trust, the organization should be willing to peel back the curtain and give that partner genuine visibility into its technology environment. There are many technology companies in the market, and caution is warranted. The signal worth watching for is investment: when an integrator puts forward time and funding, that is a partner willing to get into the mud. Like anything else, this comes down to relationships, and relationships take time to build.
Buckle In and Go
If there is one lesson from my fifteen years in this industry, it is this: remain a learner. The pace of change in AI demands the posture of a student, absorbing information constantly and treating every new development as material to master. The aviation leaders I work with embody this trait. When we sit down to discuss how to move the organization forward, they are fully engaged.
None of this is comfortable. New technologies and new processes arrive relentlessly, and leaders at every level feel the weight of keeping up. As a director, accountable both to the leaders I report to and the teams I lead, I have found that the only viable response is to confront that discomfort directly. In the language of psychology, when the choice is fight or flight, I choose to fight: to invest the time, sometimes after hours, until the unfamiliar becomes familiar.
We are entering a period in which the professionals willing to learn and experiment, to open a new tool and work through it firsthand, will separate decisively from those who hold back. For anyone who feels that hesitation, my counsel is: buckle in and go.
The same applies to the old fear of asking an uninformed question. That fear no longer serves anyone; the technology is too new for any of us to know it all. I will sit in leadership meetings and say, “Somebody walk me through this,” because intellectual honesty accelerates learning far faster than pretense. This transformation belongs to all of us. Carried alongside day-to-day responsibilities, and with an open mind, that mindset will make the next few years among the most rewarding of our careers.
