I walked into MAICON 2026 curious and came home with a notebook full of ideas and a serious case of information overload.
Between the sessions, the conversations, and the sheer number of new tools for AI in marketing, there was a lot to take in. Every presentation seemed to introduce another tool, use case, or way of working.
So, I gave it a few days. As I organized my notes for our leadership team at Rebound, six themes kept showing up. Some reinforced things I’ve been thinking about for a while. Others challenged me to rethink how we approach AI at Rebound.
Organizing my notes did more than summarize the conference. It gave me direction.
Conversations about AI in marketing kept coming back to practical questions: how teams work, how people grow, and what better results look like. Here are my six takeaways and what they mean for how we work.
Handing out AI licenses like lollipops isn’t a strategy. If we use AI to do the same work the same way, we miss most of the opportunity.
The gains come from redesigning workflows, roles, and culture, and from giving people (like me) permission to experiment and fail.
The bigger question is how AI can help us rethink our workflows, eliminate unnecessary steps, and free up time for work that requires more thought and creativity.
For me, that means looking at the processes we use every day before deciding where AI fits.
This was one of the most practical ideas I brought home.
A skill is a reusable set of instructions that teaches AI how to carry out a specific task. We’ve spent years documenting processes in standard operating procedures. Skills take that a step further: write repeatable work down once, in a format AI can follow, and improve it every time it runs.
Instead of starting from scratch every time, we can give AI the context, instructions, and guardrails it needs to help with a repeatable task. Brian Piper cut a site audit from three or four weeks to three hours this way.
I’m looking closely at the tasks our team repeats every week to find the ones worth turning into skills.
For all the excitement around AI, the conversation kept coming back to people.
AI can research, organize, analyze, and draft. People set the direction, bring the context, and make the decisions. As Paul Roetzer put it, just because AI can take the lead doesn’t mean it should.
That matters in our work at Rebound, where we help B2B companies communicate complex solutions to buyers in healthcare and life sciences. Understanding the audience, navigating nuance, and making sound decisions take human expertise.
The goal is to use AI to support efficiency while keeping people accountable for the outcome.
AI is changing how buyers find information. More people are turning to AI-powered tools to research solutions, compare options, and make sense of unfamiliar categories. Guy Yalif of Webflow shared G2 research showing 51% of B2B software buyers now start research in an AI chatbot more often than Google, up from 29% a year earlier.
For companies selling into healthcare and life sciences, that raises important marketing questions:
Strong SEO fundamentals still matter, and AI-assisted discovery raises the bar for clarity, credibility, and useful content.
This one really resonated with me.
As AI makes content easier to produce, more of it sounds the same. Mike Kaput’s advice: “Create only what AI can’t.”
The content that stands out comes from what AI can’t experience firsthand: conversations with customers, original research, lessons learned, and perspectives shaped by real work. For marketers, that means spending more time uncovering the expertise that already exists within our organizations.
One of the more thought-provoking discussions at MAICON was about what happens to talent development as AI takes on more entry-level tasks.
If newer team members skip the foundational work that traditionally helped them build experience, how will they develop the judgment they’ll need later in their careers?
There’s no easy answer, and leaders need to plan for it now. We have to create opportunities for people to learn alongside these tools on purpose.
After a conference like MAICON, it’s easy to come home wanting to try everything. I’m resisting that urge and starting with one process we use every week at Rebound: timecard submission and approval.
I’ve started building Claude skills to streamline parts of that workflow, with clear instructions, relevant context, and a person reviewing the work before anything is final.
My goal is to reduce repetitive work and make the process more consistent while keeping the judgment and attention to detail it needs.
I don’t know yet exactly what will work, what we’ll need to adjust, or how much time it will save. That’s part of the experiment. I’ll share what we learn in a follow-up post: what worked, what didn’t, and whether the results justify expanding the approach.
For now, that’s my biggest takeaway from MAICON 2026: AI has a lot of potential, and the most useful place to start is a real problem you want to solve.
At Rebound, we’re always exploring new ways to help B2B companies selling into healthcare and life sciences improve their marketing. If you’re thinking about how to make your marketing more effective, let’s talk.
To make sure you get accurate and helpful information, this guide has been edited and fact-checked by the Rebound Editorial Team.
COO of Rebound
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