Key takeaways
- AI Wednesdays helped Spitfire Inbound move from curiosity to confident AI adoption across the business.
- The biggest shift was not tool usage, but mindset: problem-first thinking, better prompting, and knowing when not to use AI.
- Short, consistent sessions made AI in the workplace feel accessible rather than overwhelming.
- Teams are using AI to improve efficiency, workflow automation, research, reporting, creativity, and decision-making.
- Human judgment remains central. AI supports the work, but people define the value.
Over six months ago in August of 2026, AI Wednesdays started with a simple intention: create space.
Space to learn, space to ask questions, space to experiment without pressure. And, maybe most importantly, space to admit that nobody quite had this figured out yet.
AI was already everywhere, with tools launching weekly. Internally, people were starting to experiment. Some felt energised by the possibilities AI created. Others felt left behind. Most people felt somewhere in between.
So instead of a small group developing an “AI strategy” or rolling out a training programme built on assumptions, we did what we tend to do best. We embraced our Curiosity Culture! We created something participatory rather than prescriptive.
We created a weekly time to learn and explore together. We’ve only been doing this for six months, and we’re already feeling the shift.
If you want to read the full origin story, we’ve covered it in this blog here.
From AI tools to AI thinking
One of our earliest realisations was that teaching specific tools would never be enough.
When it comes to AI tools, we’re spoiled for choice, and they’re constantly updating. So, trying to teach just one tool would limit us.
Instead, our sessions focused on something more relevant: how to think when using AI.
This means thinking about:
- The problem you’re trying to solve
- How to supply context
- How to structure a prompt
- How to evaluate an output
- How to recognise when AI is not the right tool to use
That last point came up often. Knowing when not to use AI is just as important as when (and how) to use it.
Brandon Holz reinforced this idea during our sessions. AI is not something to force into every task; it’s just one option in a broader toolkit, to be used deliberately.
“We don’t sell AI,” he said in one conversation. “We solve problems. AI is just a tool to help solve a problem.”
AI Adoption: Making change feel human
AI adoption isn’t only a technical challenge; it’s also a cultural (and psychological) one.
As new technology emerges, change management should follow.
People are wired to resist change, but we’re also driven by convenience. AI sits right in the middle of those. It promises speed and ease, but it also disrupts habitual ways of working and hard-earned expertise.
Here are a few ways we managed this change:
- Sessions were short.
- There was no expectation that everyone would suddenly become an expert.
- Participation was encouraged, not forced.
- Curiosity mattered more than competence.
Almost everyone described feeling more comfortable with AI with this approach.
For some, the biggest value was simply understanding the possibilities. For others, it was learning where and how to start. For most, it was realising they were already on the right track, and now had a shared language for it.
What AI experimentation can actually looked like
The sessions covered a mix of tools and ideas:
- NotebookLM was explored as a way to process information faster. Some team members even generated podcasts that sounded like genuine conversations.
- Breeze - HubSpot’s native AI tools have opened up conversations about where AI fits into marketing, sales, and service workflows. This empowered the team to explore innovative ways to help clients.
- Custom GPTs and Gems sparked excitement around repeatable, role-specific assistance. This sparked interest because it stretched how people thought about automation and prompting.
Across roles and departments, experimentation showed up in many ways:
- Strategy and consulting teams began using AI more intentionally for research, persona development, journey mapping, reporting insights, and go-to-market planning.
- Marketing and content teams leaned into AI to reduce time spent on repetitive tasks, freeing up space for creative and strategic work.
- Developers refined how they supplied context and evaluated outputs.
- Client-facing teams felt more confident answering AI-related questions because they were speaking from experience rather than theory.
- Teams were enabled to use Breeze within HubSpot to assist with day to day work and empower customers to adopt the technology further
What mattered was not that everyone used the same tools, but that they were thinking more clearly about where AI could support their work.
AI prompting is a business skill
One theme surfaced again and again as the golden thread: prompting.
Many team members mentioned becoming more deliberate about how they ask questions, structure requests, and provide context. This translated to better outputs and more consistent results.
Prompting also became a lens for better thinking in general. If you cannot clearly explain what you want, AI will immediately expose that gap. In that sense, AI became a mirror as much as a tool. It’s changed how we brief in work and communicate with each other. The same way we provide context and clarity to AI is influencing the context and clarity we give each other.
To put this into context, there’s a significant difference between a vague prompt like:“Write a blog about AI in marketing.”
And a structured prompt such as:“Write a 1,000-word blog for marketing managers in B2B technology companies, explaining three practical use cases for AI in campaign optimisation. Include examples, measurable outcomes, and a short FAQ section.”
The second prompt defines audience, scope, format, and outcome. The quality of the output improves because human thinking improved first.
No matter how good the prompt is, AI outputs must always be reviewed. We have repeatedly reinforced that AI can accelerate thinking, but it cannot replace human accountability.
Our responsibility
We all know that AI represents a genuine shift in how work happens. And that comes with excitement, but also fear, particularly for people whose identities and careers are tied to skills that now appear easy to replicate. We had honest discussions about creativity, authorship, and the discomfort of seeing technology produce outputs that once took years to master.
As a business, we have a responsibility to help people navigate this shift thoughtfully. And we do this by not ignoring the disruption it brings, and instead grounding the conversation in the human value each of us brings. In fact, our first AI session began with Sarah McDevitt and her talk on Relational Intelligence (RI).
But responsibility doesn’t stop at culture. It extends to data.
As outlined in our AI Manifesto, we recognise both the extraordinary potential of artificial intelligence and the very real risks that accompany it. AI adoption without clear principles could become reckless. However, AI adoption with clear values is transformative.
As an Elite HubSpot partner, we also align with HubSpot’s ethical AI framework. Tools such as Breeze Copilot, Breeze Agents, and Breeze Intelligence are powerful, but they are deployed within a responsible ecosystem designed around transparency and security.
In short, innovation and ethics are not opposing forces. At Spitfire, they are inseparable.
So, what’s actually changed after six months?
The most noticeable change is how we think about AI.
People are more intentional. We question outputs, we use AI to check accuracy and explore alternatives, we check AI’s accuracy.
Perhaps most tellingly, we’ve remained grounded in our Curiosity Culture. When a new tool or feature appears, the reaction is:
- “What could this help with?”
- “Is this worth testing?”
- “And if not, why?”
This is what an AI-ready company culture looks like.
Looking ahead
AI Wednesdays have always been about remaining adaptable and teachable.
The next phase will naturally become more applied:
- More focus on the tools embedded in the platforms we already use.
- We are already sharing internal use cases and will continue to do so.
- More refinement of our approach as the technology evolves.
- AI Wednesday training pods to enable more sharing, more confidence and more ethical and strategic application.
What won’t change is our underlying mindset: Curiosity over fear and solutions before tools.
Seven months in, and AI Wednesdays have helped us become an AI-literate, human-first agency.
They have helped us become a business that knows how to think clearly in a busy, fast-moving world.
Want to follow along as AI Wednesdays continue to evolve?
Subscribe to Spitfire Inbound’s YouTube channel for updates, experiments, and practical learnings!
FAQs:
How is AI changing the way we work?
AI is accelerating repetitive and preparatory tasks while fostering clearer thinking, more effective problem definition, and enhanced human judgment.
What did six months of AI Wednesdays teach Spitfire?
Sustainable AI adoption stems from a mindset and culture, not from chasing tools. Clear intent, good prompting, and discernment matter most.
How can AI tools improve daily work processes?
They can support workflow automation, research, reporting, drafting, and quality checks, allowing teams to focus more on strategic and creative work.
What is the impact of AI on jobs and workflows?
AI is augmenting roles rather than replacing them, shifting focus toward higher-value thinking and decision-making.
What does being an AI-ready business mean?
It means having the confidence, skills, and culture to use AI thoughtfully, critically, and responsibly as part of everyday work.
