When I accepted an entry-level fundraising position in early 2025, I didn't realize I was about to experience another technological revolution from the front lines of the workplace.
But I've been here before.
Over the past three decades, I've witnessed the arrival of the internet, the rise of search engines, the transformation of journalism, the emergence of e-commerce, the blogging revolution, the growth of social media, and now the rapid expansion of artificial intelligence.
Along the way, I've been a student, journalist, educator, trainer, coach, and entrepreneur. I've learned new technologies, incorporated them into my work, and taught others how to use them. Often, just as I finished teaching one technology, another emerged that required me to start learning all over again.
Now, in my mid-50s, I've found myself starting over professionally at the very moment AI is transforming the workplace.
And I've discovered that starting over with 30 years of experience offers a remarkable advantage.
Here are three things I've learned.
1. Technological disruption is nothing new. What changes is how we respond.
I began my undergraduate education in 1990 and graduated in 1998. During those eight years, the way students researched, wrote, communicated, and completed assignments changed dramatically.
When I started college, research meant spending hours in libraries, navigating card catalogs, searching through printed indexes, and locating physical materials. By the time I graduated, the internet was fundamentally changing how information could be accessed.
The workflows I learned at the beginning of my education were already becoming outdated before I finished.
Later, as a journalist, I entered newsrooms during the early days of Google. I remember resistance to incorporating search engines into reporting workflows. Today, the idea of a journalist working without online research tools seems almost unimaginable.
As an international journalist, I also experienced the limitations of early digital communication firsthand.
Reporting from overseas wasn't simply a matter of uploading a story and photographs from a smartphone. Sometimes I had to return home before completing and submitting my work. Transmitting photography was particularly challenging, and even after submitting a story, there was the wait for the weekly magazine to reach readers.
Technology eventually transformed every part of that process.
What I learned from those experiences is that technological disruption rarely arrives as a clean transition from one way of working to another.
It arrives while people are still doing their jobs.
Old systems coexist with new ones. Employees develop workarounds. Organizations resist changes they don't fully understand. And eventually, practices that once seemed revolutionary become routine.
The professional advantage isn't necessarily knowing the newest technology first. It's recognizing that the way we work will continue to change and being prepared to change with it.
2. Artificial intelligence is a powerful tool, but it isn't a substitute for professional expertise.
Several months into my fundraising job, our team participated in an experimental training exercise using ChatGPT.
My boss had created an AI-based training scenario using our sales scripts, objection-handling techniques, and other materials.
We gathered in a room with a large screen, and employees took turns responding to simulated customer objections. The AI evaluated our responses and assigned scores based on our performance.
I remember watching that exercise with a mixture of fascination and horror.
As someone who had spent years teaching adults, developing learning experiences, and coaching people, I wondered whether AI was about to take over work that had previously required an experienced trainer.
Was this the future of professional education?
Would organizations eventually decide they no longer needed people with expertise in training and development?
That was my initial reaction.
But after more than a year of experimenting with AI, my perspective has changed considerably.
I've come to appreciate how useful AI can be for practicing communication, generating scenarios, providing immediate feedback, organizing information, and supporting individualized learning.
At the same time, I've become more convinced of the importance of the human expertise behind those applications.
An AI system can evaluate a response against a set of instructions. But who determines whether those instructions reflect effective professional practice?
Who decides what employees actually need to learn?
Who recognizes when a learner is struggling because of a misunderstanding, a lack of confidence, or an ineffective instructional approach?
And who evaluates whether a training exercise translates into improved performance in the real world?
These are questions that require professional judgment.
An AI-generated score might provide useful feedback, but a score alone doesn't establish whether meaningful learning has occurred.
The quality of AI-assisted work depends heavily on the knowledge, judgment, and experience of the people directing and evaluating it.
AI in the hands of someone who doesn't understand the underlying work can produce impressive-looking results that accomplish very little.
For professionals and organizations, this distinction is critical.
Before asking how AI can replace an existing process, we should understand why that process exists, what it accomplishes, and how we determine whether it's effective.
Otherwise, we risk using sophisticated technology to automate ineffective practices.
3. The most important skill in the AI era is learning how to learn.
Throughout my career, I've repeatedly experienced the same cycle.
I learn a new technology.
I experiment with it and discover how it can improve my work.
I begin teaching other people how to use it.
Then another technology emerges, and the cycle begins again.
As an educator, I eventually realized that teaching people a particular software application or digital platform was only part of my responsibility.
The larger challenge was helping them develop the confidence and skills to adapt when the technology inevitably changed.
That lesson has become even more relevant with artificial intelligence.
AI tools are evolving so rapidly that mastering a particular interface or application may offer only a temporary advantage.
The more durable skills are curiosity, critical thinking, experimentation, adaptability, and the ability to evaluate results.
These are skills that professionals can develop regardless of their age, position, industry, or technical background.
And they're skills organizations should be cultivating deliberately.
Instead of focusing exclusively on training employees to use particular AI products, employers should be helping people understand how to identify problems, examine workflows, ask effective questions, assess information, and determine where technology can genuinely improve performance.
That requires a different approach to professional development.
It also requires recognizing that employees bring valuable knowledge to technological transitions, even when they aren't technology specialists.
A person who deeply understands a business process may be better positioned to identify a meaningful AI application than someone who understands the technology but knows little about the work itself.
Ideally, organizations should bring those perspectives together.
The future belongs not simply to people who know how to use AI, but to people who know how to keep learning as AI changes what is possible.
Starting over doesn't mean starting from zero.
When I returned to an entry-level position, I brought decades of professional experience into a role that didn't necessarily require that background.
In some ways, that has been humbling.
But it has also given me an unusual opportunity to observe how technological change affects everyday employees, established workflows, organizational decisions, and professional learning.
I've seen AI introduced into a workplace from the perspective of someone expected to use it, rather than someone responsible for implementing it.
And I've been able to compare that experience with earlier technological transitions I've witnessed throughout my career.
Perhaps my biggest realization is that my professional history hasn't become less relevant because of AI.
It's become more relevant.
I've spent much of my adult life navigating the space between emerging technologies and the people expected to use them.
Today, I'm bringing those experiences into a new chapter of my career through Brianopolis Learning, where I'm exploring how education, communication, storytelling, and emerging technologies can help individuals and organizations grow.
Thirty years ago, I was learning how the internet would change the way I studied and worked.
Today, I'm learning how artificial intelligence will change the way we teach, communicate, create, and solve problems.
I don't pretend to know exactly where this revolution will take us.
But I do know something about what it takes to navigate one.
And I've learned that sometimes the best preparation for the future comes from having started over many times before.
