The Rush to Automation
The number one AI adoption killer?
Automating before you’ve proven what works. Automation is a lagging indicator of maturity.
In the past few weeks I’ve spoken with dozens of marketing leaders rolling out AI. Many are racing to automation to gain capacity and speed-to-market. Good aims, but without solid process, clear evaluation, and strong data governance, automation projects stall or produce mediocre, sometimes disastrous, outputs faster.
What makes the difference is knowing what should be AI-assisted versus when you’re ready for AI automation.
Four types of AI work
- Strategic and AI-assisted: high-impact planning, creative problem-solving, decision support.
- Tactical and AI-assisted: repeatable tasks with human oversight and improvement.
- Tactical and AI-automated: proven, rules-based processes with clear success metrics.
- Strategic and AI-automated: adaptive, org-wide programs informed by feedback loops.
Operating principle: assist, prove, automate
If it isn’t repeatable, well-governed, and low-risk, it isn’t ready for automation.
Before you automate, check the four Rs
- Repetition. Is the work frequent and predictable?
- Rules. Can success be expressed in clear rules and metrics?
- Risk. Are mistakes low-impact and reversible?
- Records. Do we have clean, governed data the system can rely on?
If any answer is no, start AI-assisted.
Next steps for the next 90 days
- Strategic and assisted: Use an AI thinking partner for your next quarterly plan; track time-to-decision and decision quality.
- Tactical and assisted: Standardize prompts and playbooks for one workflow; add human review and a feedback log.
- Tactical and automated: Automate one already-stable process; define metrics, guardrails, and an escape hatch.
- Strategic and automated: Wait until the first three are stable and data governance is in place; pilot in shadow mode (AI proposes, humans approve) first.
Which quadrant are you operating in most today, and which single workflow will you move next?