The AI Adoption Ladder (And Why Most Marketers are Still at Level One)

In Episode 56 of Enterprising Minds, I laid out a concept of the AI Adoption Ladder, which is something I’ve been thinking about as I’ve been speaking to marketers about AI over the last few years. Each level reflects increasing complexity and capability—and each one has major implications for marketers trying to stay ahead.

Let’s unpack these levels—and what they mean for your strategy, your skill set, and how you might leverage AI moving forward.

Level 0 — Zero Exposure

You’ve heard the hype but never opened an AI app. You still Google for answers AI could generate in seconds, or maybe you’re only AI interaction is the Google AI Answers when you search.

Move next: Pick one model (ChatGPT or Claude) and give it a low‑stakes job you already do weekly—subject line ideas, meeting recaps, or a tighter LinkedIn summary. Ten minutes, tops.

Level 1 — Light Use, No Habits

You’ve dabbled: a draft here, a brainstorm there. You copy‑paste, fix the awkward bits, and move on. Helpful, yes—habit‑forming, no. Value stays sporadic because usage stays sporadic. At this stage it’s easier to stick with what works for you now than push through and do something in a new way.

Move next: Promote one recurring task to “AI‑first.” For example: every Friday, have AI turn raw notes into a one‑page status memo. Create a Slack thread—“What AI did this week”—so small wins compound into a workflow.

Level 2 — Deep Research, Context in the Loop

This is where the lights come on. You use AI to compress long research, pressure‑test strategy, and prep for high‑stakes conversations. You don’t outsource judgment; you augment it. (As Ruthi would say, you’ve got a trained coworker, not a robot overlord. As Alex likes to push, ask the brutal question and let the model argue back.)

Move next: Point AI at your real context. Feed it past briefs, performance reports, and customer language. Ask it to synthesize patterns, risks, and counter‑arguments—not just produce copy.

Level 3 — Workflow Integrations (Human‑in‑the‑Loop)

Now you chain tools and data so systems take first action toward a goal. Think: monitoring rankings, drafting weekly SEO updates, queuing lifecycle emails, or summarizing pipeline changes—then routing to you for approval. Autonomy stays bounded; guardrails do the heavy lifting.

Move next: Pick one process with clear inputs and definitions of “good.” Build a proof‑of‑concept using Zapier/Make plus an LLM. Insert checkpoints: confidence thresholds, exception queues, and a kill switch.

Level 4 — AI Agents - Not There Yet

In the episode of the podcast we discuss the definitions of workflows vs. agents. For me, an AI agent is where it’s taking actions on your behalf without the explicit instructions that are contained within the workflows level. It’s the difference between automation vs. autonomy. As of this newsletter, I don’t believe we are there yet, but we are getting awfully close.

Why This Ladder Matters Right Now

• Expectation setting: Don’t buy agent promises if your team is at Level 1.

• Road‑mapping: Invest in habits and workflows before autonomy.

• Quality bar: Measure thinking gains, not just time savings.

• Governance: Ship guardrails with the workflow, not after it breaks.

What to Do This Week

1. Self‑audit (10 minutes): Mark your personal level and one friction that keeps you there.

2. One upgrade: Choose a single task to make AI‑first for 30 days.

3. Context pack: Create a private “starter corpus” (five briefs, three reports, a glossary) to feed your model.

4. Mini‑agent: Automate one monitoring job with an approval step. Document the kill switch.

5. Ethics check: Publish a simple, public stance on recording and data consent.

—Dave

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