Compete Using AI
Automate repeatable work and reinvest your attention in distinctly human value.
- Difficulty
- Moderate
- Time to result
- ~ongoing to results
- Steps
- 6
- Confidence
- 94%
The framework reframes AI from a competitor into a source of leverage. Begin by decomposing a role into repeatable tasks and higher-order responsibilities. Automate bounded, predictable tasks such as research, editing, variation generation, or routine production, while retaining human oversight where quality and context matter. The resulting capacity should not merely produce a larger volume of average work. Reinvest it in customer understanding, original ideas, creative judgment, relationships, and persistent skill-building. This creates a reinforcing loop: better fundamentals improve the instructions and evaluation supplied to AI, while AI provides more opportunities to test ideas and accumulate experience. The goal is to become a more capable marketer whose distinctive human contribution grows as routine execution becomes cheaper.
Origin
Extracted from Marketing Against The Grain during Kieran Flanagan's analysis of whether AI will automate 95% of the work marketers currently outsource.
Core principles
- 01Treat AI as leverage rather than an opponent
- 02Expect repeatable tasks to become automated
- 03Protect work built on judgment, creativity, and human interaction
- 04Reinvest saved time in customer understanding and higher-level work
- 05Keep developing fundamentals instead of using AI to produce more mediocrity
How to run it
- 1
Decompose the Role
Write down the tasks you perform daily, weekly, and monthly. Separate repeatable activities from work requiring judgment, relationships, or original thinking.
Pro tip Describe each repeatable task in terms of its inputs, process, and expected output.
Watch out Do not label an entire job automatable merely because some of its tasks are repetitive.
- 2
Select a Bounded Automation
Choose one recurring task with clear success criteria and test whether AI can complete or accelerate it.
Pro tip Start with research, transcription, editing, summarization, or controlled content variations.
Watch out Avoid beginning with high-stakes work whose errors cannot be reviewed or reversed.
- 3
Evaluate Against the Real Standard
Compare AI-assisted output with the strongest work competing for the same audience, not merely with your previous process.
Pro tip Score both efficiency and production quality before expanding the workflow.
Watch out A faster output is not valuable if it is too generic to earn attention.
- 4
Preserve Human Judgment
Keep people responsible for customer context, conceptual thinking, provocative viewpoints, humor, emotional resonance, and final approval.
Pro tip Use AI to produce options while a skilled marketer selects, combines, and improves them.
Watch out Do not publish unreviewed output simply because it is technically complete.
- 5
Reinvest the Capacity
Spend the saved time on customer conversations, strategic problems, creative concepts, relationships, and higher-level execution.
Pro tip Schedule the reclaimed time explicitly so routine work does not expand to consume it.
Watch out Using AI only to multiply average content can weaken differentiation.
- 6
Keep Building Reps
Continue practicing the timeless fundamentals that let you direct and assess AI effectively. Improve the workflow as tools progress from assistants toward more autonomous collaborators.
Pro tip Review the automation regularly because capabilities and quality thresholds change quickly.
Watch out Do not let convenience replace perseverance or subject-matter competence.
In the wild
A marketer maps a weekly article process and delegates research collection, transcript cleanup, and headline variations to AI. The marketer retains the customer interviews, core argument, examples, and final edit, then uses the saved hours to test stronger positioning with customers.
→ Routine production becomes faster while the published work gains stronger insight and differentiation.
A growth marketer uses an AI workflow to compile recurring channel data and draft a standard report. Instead of manually assembling slides, the marketer investigates anomalies, interviews sales, and proposes experiments based on the findings.
→ Reporting consumes less time and produces more decisions rather than merely more documentation.
Common mistakes
Competing Against the Tool
Rejecting AI as hype leaves the marketer performing tasks that increasingly capable tools and AI-enabled peers can complete faster.
Scaling Average Output
Using AI to generate more mediocre content increases volume without creating the quality, originality, or emotional resonance needed to compete.
Abandoning the Fundamentals
AI cannot compensate reliably for weak customer knowledge, poor judgment, or an inability to recognize an effective strategy.
Is it for you?
Best for
It is best for marketers whose roles contain substantial repeatable work but still require customer insight, creativity, and collaboration.
Not ideal for
It is not ideal for people seeking fully autonomous output without experimentation, supervision, or continued skill development.
From the transcript
“there's two ways to really think about that and interpret that is that you are competing against AI or you are competing using AI”
“AI will 100% automate repeatable tasks that is a guarantee”
“that's why I think it's really important to figure out what are the repeatable tasks you do today that you can start automating with AI”
From the episode
Will AI Automate 95% Of What Marketers Do?