On a recent call, the head of marketing at a mid-sized B2B SaaS company walked me through everything his team did to solve the slowdown problem.
They had created a shared prompt library on Notion. They had published a brand voice guide. They would go through AI literacy training twice. They held monthly office hours where the most prolific AI users on the team answered questions. The CMO personally wrote a memo modeling thoughtful use of AI and gently reminded everyone that the goal was substance over volume.
However, the work kept coming. Half-finished briefs that feel like the first drafts of something better. Sliding platforms that felt good on the surface and disintegrated on the third shell. Newsletter text that hit the brief and missed the audience.
Workslop is the easy symptom to name. Diagnosing where it comes from is more difficult and is in a different level of the organization.
Where most business conversations stop
Research by BetterUp Labs and Stanford — the original HBR study from September 2025 and a follow-up in January 2026 – put the numbers in plain sight. Forty percent of employees have received work stoppages in the past month. Each instance costs just under two hours to clean. In a company of 10,000 people, the numbers are more or less approximate 9 million dollars a yeargone, to the correction of the work generated by the artificial intelligence that was supposed to save time.
The number that is most difficult for me comes from Asana’s State of AI at Work research. Only 19% of knowledge workers say they have clarity on the types of work AI should do in their role. This figure explains the rest of the data.
The dominant solution in the conversation right now is the one my call partner has been pushing for six months. Leaders should model the targeted use of AI. Teams should set clear guardrails. Individuals should develop what BetterUp calls a pilot mindset.
Human AI results should meet the same standards as results obtained solely by humans. Greg Kihlstrom’s recent article on MarTech extends the topic into marketing-specific territory, calling on marketing leaders to step up and define the lines of transition with IT, legal, and procurement.
This is all correct. None of this is wrong. And all of this places the burden on the same subject: the single prompter, the single leader, the individual mentality. This is the level that most teams have tapped into over the last 18 months, and the real solution lies elsewhere.
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Where the system is broken
Workslop is what happens when individual people produce AI-generated work and there is no connective tissue between them.
In an active marketing team, learning must happen quickly. The content specialist understands in the first week that this model needs a longer brief and a narrower persona to generate something usable. The designer realizes in the second week that this image tool wants the brand colors to be in hexadecimal, not in plain words. The email marketer realizes in week three that AI subject lines look generic unless they are given the last three subject lines that worked.
Each of these learnings is real. Each one was earned. In most marketing teams, none of this knowledge gets very far. The content specialist doesn’t know what the designer understood. The email marketer doesn’t know what the content specialist has learned. There’s no shared place where someone says, “This is what worked, here’s how I got there, try it your way and tell me what improves.”
What you end up with is a team of skilled people, each running their own small R&D project in parallel. Everyone improves in their slice. The team’s combined output still produces slowdowns because no individual’s learning never reaches the next person. When someone moves teams, that learning goes out the door with them.
This is the part of the worklop problem that no one clearly mentions. It’s a learning coordination problem and isn’t solved by another training session or sharper brand voice guidance. The problem is solved by building infrastructure that brings learning to people.
What the AI coordination fix looks like
In my book “Hyperadaptive,” I call this connective layer the AI activation hub. A hub is a small group of people within the organization, virtual, physical, or both, whose job it is to keep AI capabilities flowing through the rest of the team in both directions.
It’s a different thing than a help desk, a prompt library, or an AI ticketing inbox. Those are static repositories that you go to when you need to search for something. A hub is made up of people whose job it is to actively move learning within the team.
The practical vision, in a marketing context. A work hub does a handful of specific things.
- Stays updated and atomizes learning: Hubs translate what’s new and what works into bite-sized, role-specific content that ends up in the workflow, more like a two-minute Loom in a Slack channel than a wiki page that no one opens.
- Holds office hours and pairs people: Hubs facilitate live, hands-on experience. A hub member pairs a marketer with AI mastery with a marketer with business context, and the resulting work is better than either could accomplish alone.
- Maintains a usable knowledge engine: When engineering firm iMBrace built its own, it cut its information search time in half. This is the number worth paying attention to. The repository is live, queryable in natural language and continuously updated by the Hub itself.
- Measure where AI is and isn’t gaining ground: Hubs track what works and report that model to leadership. This is the piece that is completely missing from most Marketing AI Centers of Excellence job descriptions.
When was the last time your team built something that purposely enabled AI learning among members, instead of hoping it would happen to the coffee machine?
New job market data suggests marketing is starting to figure this out. Second a recent piece by Carilu DietrichSenior AI marketing roles are growing rapidly under names like AI marketing manager, AI marketing center of excellence manager and senior director of AI projects.
Posts related to GTM engineers on LinkedIn have more than doubled in six months, from about 1,400 in mid-2025 to more than 3,000 in early 2026. Marketing is inventing the real-time hub and giving it a different name.
The teams I see have understood the scope of the role correctly. They define the hub leader’s job as being about moving learning, pairing people, and making the team smarter on purpose. This is a different job description than “police timely quality and AI enforcement,” which is where most of these roles fall right now.
Where is this headed
The marketing teams that solve business problems over the next 12 months will be the ones that build the connective layer that brings learning between people, so when one marketer discovers something, the rest of the team will use it by the end of the week. This is the real solution. Efficiency follows. He always does.
