I’ve been in marketing for over 30 years. I watched the mobile phone reshape how we communicate, and I saw the internet rewrite every rule of commerce. Both times, the business world split into two camps: those who moved and those who waited. The ones who waited paid for it, some with their businesses.
Four years ago, marketing got a gift: AI. And when I tell you I went all in, I mean all in—not because it was trending but because I recognized the pattern. This wasn’t a feature upgrade or a new platform to learn; this was a category shift, the kind that happens once or twice in a career. What I didn’t fully appreciate then is how much faster and more consequential this particular shift would become.
Here’s what separates this moment from every previous technology revolution in business history: while cell phones changed how we communicate, and the internet changed how we transact, AI is changing what humans are needed for. And it’s doing something no prior technology has ever done — it can walk, talk, listen, think and recreate itself. It’s already doing many of these things better than we can, and soon it will do them even better. That’s not a projection but rather a trajectory already in motion.
A Validation of Direction
Let me tell you about a room I was standing in earlier this year.
I was presenting at the Executive Connection Summit in Scottsdale. I laid out where I believe AI is heading: agents replacing cognitive roles, automation compressing headcount and purpose-built tools replacing off-the-shelf software. I told the room that traditional CRM, as we know it, wouldn’t survive in its current form. Think about what a CRM actually does: it records customer interactions, books meetings, logs follow-ups, stores communication history and tries to give your team visibility into relationships. Now consider that AI can already record every customer meeting, transcribe and summarize it in seconds, automatically create meeting minutes, book the next appointment, and draft and send follow-up communications. And it does all of it without being asked twice. The CRM was built to compensate for human memory and human inconsistency, and AI eliminates both. The platform isn’t the point anymore—the intelligence is.
One executive looked at me and said, “I think your ideas are far-fetched.” I nodded and left the session. What I didn’t know at the time was that while I was in that room making the case for AI’s future, Matt Shumer was publishing the essay that validated everything I had just said. On Feb. 9—the same day I sat down with Jennie Fisher of GreatAmerica for a fireside chat on AI at ECS—Shumer released “Something Big Is Happening” to the world. I didn’t see it until the following morning, when it already had millions of readers.
That essay has now been read by 80 million people. I’m not going to summarize it here, but you should certainly read it (shumer.dev/something-big-is-happening). Then send it to your leadership team. Send it to your family. Send it to every executive you know who’s still on the fence about whether this AI moment is real. Shumer published it in February 2026. The world it describes has continued accelerating every single day since.
Since that ECS presentation, I’ve heard from other attendees, one of whom told me, “I heard you speak, and you scared the crap out of me.” A vendor in the room gave me a nickname that has apparently stuck: the Mad AI Scientist. I want to be clear that I’m not doing anything exotic, and I’m not a researcher or engineer. I’m a marketing executive who made a decision four years ago to take this seriously, started building and hasn’t stopped. What feels alarming to some is simply what happens when you’ve been paying attention.
Where Shumer’s Essay Matters Most
Shumer cites data from METR that measures how many hours of expert human work an AI model can now complete autonomously, end to end. A year ago, that number was ten minutes. Now, the most recent measurement is approaching five hours of expert-level task completion, and that capability is doubling every four to seven months.
Anthropic CEO Dario Amodei has publicly stated that AI models “substantially smarter than almost all humans at almost all tasks” are on track for 2026 or 2027. He’s also predicted that 50% of entry-level, white-collar jobs could be disrupted within one to five years. These aren’t the words of a futurist blogger; this is the CEO of one of the two most consequential AI laboratories in the world.
Scott Galloway, the NYU Stern marketing professor and sharp analyst, has argued recently that AI is no different than prior technology waves—it destroys some jobs and creates others—and that we’ve survived this cycle before. With respect, I disagree on this single point. When Galloway’s historical framework was formed, no machine could write its own code, build the next version of itself or hold a conversation indistinguishable from a human. Now machines can do all three. We’ve never had to adapt to a technology that can think, reason, communicate and soon navigate the physical world with that same intelligence. That changes the comparison fundamentally. Every tool we’ve ever adapted to before extended human capability. This one replaces it.
Adapt—or Get Left Behind
I’ve spent the past year in conversations with executives running businesses from $3 million to over $8 billion in annual revenue. All of them—regardless of size, geography or vertical—are wrestling with the same reality. They know they need to act on AI. They’re watching enterprise-level layoffs ripple through the industries above them, and they’re wondering when the pressure reaches their level.
Here’s the honest answer: it already has. This industry has always been a late adopter of technologies including managed IT, digital marketing and cloud services. We were behind the curve every time. AI will follow that same pattern for most. The difference this time is the cost of waiting is higher, and the recovery window is shorter. Dealers who start building today will have a structural advantage within 18 months that will be very difficult for laggards to close. This is my fair warning to every executive I’ve worked with and respected over the years in this channel—the tsunami is coming. It’s moving faster than you think, and I care too much about the people in this industry to stay quiet about it.
Now let’s talk about how to build, because doing it wrong is nearly as dangerous as not doing it at all.
MIT’s NANDA Initiative published a study last year, “The GenAI Divide: State of AI in Business 2025,” that found 95% of enterprise generative AI pilots delivered zero measurable impact on profit and loss. Thirty to forty billion dollars invested across hundreds of deployments, and the vast majority produced nothing. That number doesn’t surprise me; most organizations deploy a tool, announce it internally and wait for results that never come.
At AIS, every AI project we launch must pass at least one of three filters:
- Does it make us more profitable?
- Can we sell it to our customers?
- Does it give us better insight into our business so we make smarter decisions?
If the answer to all three is “no,” we don’t build the project.
That discipline is how our internal LinkedIn outreach automation—a workflow I originally built for our own sales team—became a commercially available tool accessible to any dealer in the channel. I’m not a coder, but I was able to build it using the AI tools available today. We used it internally first, tested it under real conditions, improved it and only when it proved its value did we make it available externally.
Build for yourself. Prove it. Then sell it. That’s the only AI development model I’ve seen consistently work.
Reimagine Rather than Replace
Now I want to say something that requires more than strategy. It requires honesty.
This past year, we fundamentally restructured how AIS approaches content operations. What had been a traditional, labor-intensive content management function became an AI-driven content ecosystem—one capable of researching faster, managing full editorial workflows, generating images, building schema code and operating continuously at a scale that was impossible just a few years ago. The annual cost: under $1,000.
But I want to be clear about what that means, because there are two truths here, and executives need to hear both of them.
The first truth is one Marissa, who’s been part of our team and family for years, would tell you: her role didn’t disappear—it transformed. She now plays a more strategic role than ever before by overseeing, directing and refining the network of AI systems and workflows that power our marketing operations. The technology expanded what our team can produce. Her human judgment, brand stewardship and operational oversight are what make the system deliver actual business value. That evolution is real, and it matters.
The second truth is the one every executive in this channel needs to sit with: the traditional version of that role—the one defined by manual production tasks, repetitive content scheduling and execution-level output—has been replaced. Not paused. Not supplemented. Replaced. The position that existed two years ago no longer exists in that form, and it’s not coming back. That’s the honest version of what AI is doing inside businesses right now, including mine.
What I teach every person on my team is that the way we survive what’s coming isn’t by resisting the machine. It’s by learning to direct it with intelligence, curiosity and purpose. Rather than managing people the way we once did, we’re going to be managing agents, workflows, platforms and systems. The professionals who come out ahead will be the ones who skill up, take ownership of these tools and make themselves indispensable as the human layer that AI can’t replace—skills such as judgment, creativity, relationships and accountability. That’s not a consolation prize but rather the highest-value work in the organization. But you have to choose to go get it.
Looking Forward
Every business in this channel needs one thing right now: an AI architect. One person who owns the strategy, understands the tools and is accountable for moving the organization forward. I’ll spend the next article in this series walking through exactly what that role looks like—where to find the right person, what they should own and how to structure them for results.
Future articles in this series will cover the practical mechanics of prompting AI effectively, why going all-in is the only rational strategy remaining, what Agentic AI means for your sales floor and service operations, and how to evaluate and build AI tools that survive contact with your actual business.
Be sure to read Shumer’s essay, then ask yourself: if the water level has been rising around my business for four years, where does it stand right now? And what are you going to do before it reaches your chest?
