I’ve been leading AI team trainings for three years now. Every week, we hear the same request from marketing, PR, and communications leaders.
“We need custom AI training for our teams.”
They’re not wrong. AI is now embedded in how marketing gets planned, built, launched, optimized, and measured. It is shaping engagement, sales conversations, crisis response, and even how brand trust is formed in real time. Sitting this out is no longer an option.
But here is the uncomfortable truth.
Most of the organizations asking for AI training are not actually ready for it.
Not because their teams are incapable. They are smart, motivated, and already experimenting. Not because leadership is asleep at the wheel. Most leaders are actively trying to do the right thing.
The problem is simpler and more dangerous.
They are trying to train people on a system that does not yet exist because they have:
- No clear AI tech stack.
- No AI policies.
- No governance.
That is not an edge case. It is the norm.
And it is exactly where AI initiatives quietly start to wobble.
The Market Has Moved Faster Than Most Organizations
If you look at what is happening in AI for marketing right now, a clear pattern emerges.
Enterprise consultancies are rolling out agent-driven platforms that orchestrate entire marketing workflows. Startups are raising serious money to help brands optimize for AI agents rather than just human audiences. New data shows AI is no longer a side experiment for marketers. It is infrastructure.
At the same time, brands are experimenting publicly with AI’s cultural role, sometimes even poking fun at it, while others are racing toward autonomous systems that can plan, execute, and optimize campaigns on their own.
This is not AI for brainstorming taglines.
This is AI reshaping how marketing actually operates.
And yet, many organizations are still approaching AI adoption like it is a training problem rather than a systems problem.
Training Is Not the Starting Point. It Is the Multiplier.
This is usually the moment where someone says, “So are you saying we should not train our teams yet?”
No. Please train your teams. (And, let us do it!) Just do not make training the first or only step.
AI training is incredibly valuable when it has something solid to land on. Without structure, training becomes a confidence booster at best and a liability at worst.
It is like teaching people to drive before you have decided which roads are open, what the speed limits are, and who pays for the insurance.
When clients come to us asking for custom AI training, the first thing we do is slow the conversation down just enough to ask better questions.
- What AI tools are approved for teams to use today?
- Which models can be used for which workflows?
- Where is existing sensitive data allowed to live?
- What regulations exist in your industry?
- Who is accountable when AI gets something wrong?
In most organizations, these questions have not been fully answered yet.
That is not a failure. It is a reflection of how fast this space is moving.
The Hidden Cost of Skipping Tech Stack Decisions
One of the most common issues we see is a lack of a clearly defined AI tech stack.
Teams are experimenting everywhere. ChatGPT here. Copilot there. A design tool over here. A research tool over there. Personal accounts. Enterprise licenses. Free trials. Browser extensions that someone installed at midnight.
From the team’s point of view, it feels flexible. From leadership’s point of view, it feels invisible. From a risk perspective, it is a dangerous mess.
Without a defined stack, you cannot train consistently. You cannot protect data. You cannot measure impact. And you cannot scale.
This is where we step in to help clients vet and select the right AI tools for their specific workflows, use cases, and industries. Not the shiniest tools. The right ones.
The goal is not fewer tools. The goal is intentional tools that work together and support how teams actually operate.
AI Policies Should Fit the Way People Work
The second major gap we see is policy.
Most organizations either have no AI policy at all or have something that reads like it was written by legal for legal.
Teams do not need a thirty page document. They need clarity.
- Can I use AI for external communications; which tools and how?
- Can I use it in crisis response; which tools and how?
- Can I automate outreach; which tools and how?
- Can I paste customer data into this tool?
- What absolutely requires human approval?
When policies are unclear, teams guess. Some become overly cautious and avoid AI entirely. Others take risks without realizing it. Risks that can come back to bite your brand in a big way.
Neither outcome is good.
We help organizations create AI policies that fit their real workflows, industry regulations, and client or customer expectations. Policies that enable smart use rather than block it.
Then, we move to custom team training and design it to demonstrate and reinforce those policies in action.
Governance Is the Unsexy Part That Determines Success
Governance is not glamorous. No one puts it on a slide with fireworks.
It is also the difference between AI initiatives that scale and those that quietly stall.
Governance answers the boring but critical questions.
- How are new tools selected?
- Who approves new tools?
- Who monitors outputs?
- Who updates guidance as models change?
- Who owns success and failure?
Without governance, AI adoption becomes fragmented. Different teams move at different speeds. Quality varies. Trust erodes. Leadership loses visibility.
Training people on AI without governance in place is like installing a powerful engine with no brakes.
Why This Matters Even More in Marketing and Communications
Marketing, PR, and communications teams are not operating in a vacuum.
- They shape public perception.
- They respond in moments of crisis.
- They influence revenue.
- They touch trust directly.
When something goes wrong here, it is public and it moves fast.
That is why governance, tech stack clarity, and policies matter so much in these functions. Not to slow teams down, but to protect them while they move faster.
What Being AI Ready Actually Looks Like
Before AI training delivers its full value, organizations need a few fundamentals in place. We start all client trainings with these steps:
- A vetted AI tech stack aligned to workflows and risk tolerance.
- Clear, human readable AI policies that reflect how teams actually work.
- Governance that assigns ownership and accountability.
- Leadership alignment on where AI should be used and where it should not.
Once those foundations exist, training becomes a force multiplier instead of a patch.
Teams stop guessing. They stop duplicating effort. They stop worrying about crossing invisible lines.
The Opportunity Leaders Should Not Miss
The organizations winning with AI right now are not the ones rushing into training first.
They are the ones taking a step back to design the system around the training.
They understand that AI is no longer a side tool. It is becoming part of how work gets done. And that requires intention.
If your teams are asking for AI training, that is a signal. Not just that they want skills, but that they want clarity. The most helpful thing you can give them is not just training on tools, but a structure they can trust.
And yes, once that structure exists, the training finally sticks. That is where AI stops being a shiny object and starts doing real work.
Remember, AI won’t take your job. Someone who knows how to use AI will. Upskilling your team today, ensures success tomorrow. Custom in-person and virtual trainings are available. If you’re looking for something more top-level to jump start your team’s interst in AI, we offer one-hour Lunch-and-Learns. If you’re planning your next company offsite, our half-day workshops are as fun as they are informational. And, of course, we offer AI consulting and GEO strategies. Whatever your needs, we are your partner in AI success.
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