Council Post: The Best Culture Is Full Of Curious Beginners
tags:Eric Laughlin, CEO of Agiloft.
getty
There’s a sticky note on my desk, crinkled at the edges, that reads: “Push AI Internally Every Day.” I wrote it to myself two years ago when I began implementing internal AI initiatives. I’ve led the workshops, sent the reminders and made the case in every all-hands meeting. I’ve never taken the sticky note down, but its meaning has changed. It’s no longer a to-do, but a reminder of how far we’ve come.
That evolution highlights questions I’ve spent my career trying to answer: What does a company’s culture look like once automation and AI has eased the burden on repetitive parts of the job? What’s left for people to do, and who do they become when the grunt work doesn’t consume all their work hours?
I’ve realized that, when it is done right, this transformation can create a company full of curious beginners.
From Theory To Practice
Early in my career, my work at Thomson Reuters made it clear that success depends far more on the willingness of people than the tech itself. Google’s Project Aristotle findings solidified this for me. It identified psychological safety as a top five indicator of an effective team. If your team isn’t comfortable with who they are around, they will not take the risk to unlearn and relearn. Now, as the CEO of a fully remote workforce, I’m proud that the number one word for our culture is support—for both our customers and our people. When you intentionally foster an atmosphere driven by support, the confidence to learn something new comes easy.
In August 2025, we formally asked our employees to take the leap; to begin their journey in AI experimentation. We rolled out a company-wide enterprise-AI tool, marking a fundamental shift in how our team thinks, works and creates. Today, over 80% of our employee base uses AI solutions to automate workflows and, in turn, make time for strategic thinking and human connection.
AI is powering professional work everywhere, but you can’t just say, “Go use AI.” The workforce needs to feel inspired and that their leaders are 100% behind them in their development. In the age of AI, leadership goes beyond the power to dictate. I spent time experimenting and walking through a self-directed learning pathway. This was in part to make my own workday better, but more so to inspire my colleagues that if their non-technical CEO can do it, they can too.
We approached this roll-out by encouraging exploration, which allows the adoption to spread organically through practices like internal showcases and peer-led sessions, where teams across departments can share what’s working in their AI journey. It turns out that when there’s enthusiasm for new technology, new ways of doing work and new ways of existing within an organization, it tends to spread like wildfire.
Almost every week in our company all-hands, teams from solution engineering to marketing to HR to customer success are eager to showcase how they’re using AI in their workflows. The flood of chats, comments and positive reactions during these presentations made it clear that our teams want to learn more and adopt what they were being shown.
From Push To Pull
Several years in, the story is no longer about adoption, but what employees can do with that continued beginner mentality. They experiment. They are hungry to learn. They ask for more, and we scale the meaningful processes.
The habit I used to have to manufacture on that sticky note is now the baseline. I’m not pushing AI internally anymore; they’re pulling me towards it. Now I’m the one eager to learn what our AI operations team has put in place, and what our “AI Builders” program from the ops team has produced.
The beauty of this pull is it shows up differently for everyone but ultimately fosters the same level of curiosity. If I had to distill what’s actually built these habits across our workforce and how to build the beginner mindset, it comes down to these things:
Model it yourself.
Make a point of experimenting with AI every day and making it visible. When I ask my team to act like curious beginners, I’m asking them to join me, not take the leap alone.
Teach it inside the job.
Innovation happens more rapidly and successfully when the result isn’t theoretical. It happens when it helps you finish your work faster and more impressively so you can log off at night knowing you’re moving the business and your career forward. Our sales team is turning around RFP responses faster and spending more time with customers while our legal team is using our CLM platform to extract data and automate workflows.
Make it visible.
Peer-led sessions and internal showcases should be intentional. Encourage, reward and celebrate experimentation as a milestone of your company culture.
Scale the successful experiments.
Put real resources towards making successful experiments into everyday operating procedures. Knowing that something you are working on for yourself may impact your whole team is inspiring, especially for a team that values support culturally.
From Function To Transformation
Where people find themselves when repetitive tasks are scarce has little to do with title, tenure or skill, and more to do with the enthusiasm to test what’s possible. Once AI absorbs the grunt work, there’s room to ask “What else?” That sticky note on my desk is a reminder of who’s doing the pushing, and to be ready to continue to begin.
The deeper impact is on what experimentation does to how people see themselves. Technology changes what people do, but transformation changes how they understand their value. It takes a lot to accept that you are a beginner again decades into your career. Transformation demands transparency, which builds the trust necessary for employees to explore. This exploration builds the real dividend of taking repetition off of someone’s plate, to inspire curiosity and creativity. That’s a different kind of workforce that every leader should be trying to foster.
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