THIS MONTH'S FIELD SIGNAL

After the AI Hype, What Comes Next?

Over the past few weeks, I’ve heard a version of the same concern from multiple communications and marketing leaders.

For the last year or two, AI was something you said on earnings calls. It was a signal—to investors, to analysts, to the market—that you were forward-looking, serious about productivity, not asleep at the wheel.

And for a while, that was enough.

One senior executive I spoke with described it this way: two and a half years ago, if you mentioned AI three times on an earnings call, your stock went up. Every CEO took note. Of course they did. In a world of shrinking markets, supply chain volatility, and labor uncertainty, leaders were searching for productivity wherever they could find it.

Then along came AI.

It looked like acceleration. It looked like margin protection. It looked like growth. So the narrative moved quickly. Faster, in many cases, than the internal reality.

Now we’re in a different phase. Investors aren’t reflexively reacting to the mention of AI. They’re asking for evidence. Customers want to know what’s actually changed. Boards are asking what the return looks like.

And communications and marketing leaders are inheriting a new mandate: translate aspiration into proof.

This isn’t a critique of “AI washing.” The executives I’ve spoken with are thoughtful people with good intentions. But the reality is that investor narratives often emerge first, while the implications for employees—how this changes work, roles, identity, opportunity—are more complex and often take longer to unfold.

That sequencing gap is where tension now lives.

AI has shifted from signal to scrutiny. And scrutiny requires substance.

FROM THE FIELD

A Real-World Example

A communications leader at a large global company told me recently that their CEO had been consistently highlighting AI in public forums. The strategy made sense. The company needed to show it was leaning into productivity in a tougher macro environment.

Inside the organization, though, the story was less clear.

Pilots were running. Small teams were experimenting. Some promising use cases had emerged. But they were still pockets—isolated wins, not scaled shifts.

At the same time, employees were reading headlines about workforce reductions in other companies. Even when leadership’s intent wasn’t “slash and burn,” the word productivity landed that way.

“If we can’t clearly articulate what AI is actually doing for us,” she said, “people will assume the worst.”

That’s the tension.

Externally, there’s pressure to show momentum. Internally, there’s uncertainty about what’s real, what’s changing, and what it means for people.

And without clarity, scrutiny turns into skepticism.

QUESTIONS FROM THE TRAIL

Ask Yourself

1. If your CEO had to explain, on one slide, what AI is concretely doing for your business today—not next year, not aspirationally—what would be on it?

2. Where are you promising future AI value externally that hasn’t been clearly defined internally?

3. When leadership uses the word “productivity,” what do your employees hear?
   

ONE SMALL NEXT STEP

Recognize This Pattern?

If you’re a marketing or communications leader trying to reconcile external AI messaging with internal reality, a useful next step isn’t another tool. It’s clarity.

Clarity on:

• What AI is actually changing in your workflows

• What you can confidently say externally

• And where your narrative may be outrunning your capability

I offer a complimentary 45-minute AI Narrative Alignment session to help leaders pressure-test their AI narrative and identify one concrete next move.

No pitch deck. Just an honest conversation.

TOOLS FOR THE TRAIL

Google NotebookLM

The AI landscape is evolving so quickly you could spend all your waking hours experimenting with tools — but who has the time? I’ll occasionally share tools I’m experimenting with — not as endorsements, but as supporting actors

Lately I've been using Google NotebookLM for translating raw materials into compelling narratives and more digestible content. Here's an example of an infographic it created for me in just a couple minutes based on one of my recent articles:

What I like about it: you can drop in a variety of source content (e.g. transcripts from meetings or earnings calls, analyst notes, internal strategy decks, webinar recordings, messaging documents) and ask it to identify patterns, summarize themes, or generate ready-to-use content including presentations, videos, podcasts or infographics. Unlike some AI tools, it doesn’t invent facts; it works from the source material you give it. You can also ask it to follow your brand guidelines when creating content.

What I don't like about it: It's not designed for editing. There's no option to revise the videos, podcasts or infographics it creates — you have to create entirely new versions — so detailed prompting is key if you want to create content for external use. While the paid version will allow some editing of presentations, it creates each slide as a monolithic image, so you're dependent on the tool to make even minor text edits.

Tools can help you move faster. But in this phase of AI adoption, credibility is the real currency.

A quick note: You’re receiving this email because we’ve connected at some point about AI, leadership, or communications/marketing, and I thought you might find these field notes useful. I’ll send this about once a month. If it’s not helpful, you can unsubscribe anytime using the link below—no hard feelings.