Getting Started with AI Marketing
What AI can genuinely do for a small marketing team today, what it can't, and how to start without breaking what works.
What AI is actually good at today
Three things, reliably: drafting content faster than a blank page allows, summarising performance data into something readable, and holding a consistent voice across more output than one person can write. Everything else — strategy, judgment, taste, knowing your customer — is still yours.
Where teams go wrong
- Publishing drafts. AI output is a first draft from a fast, well-read intern. Edit it or don't ship it.
- Volume as strategy. Ten mediocre posts lose to two good ones, and search engines increasingly agree.
- Tool sprawl. An AI writer plus a scheduler plus an analytics tool recreates the disconnection AI was meant to fix.
A sane first month
- Week 1: pick one channel and one content type. Generate drafts, edit hard, publish twice.
- Week 2–3: build the rhythm — same slots, same editing bar. Keep notes on what the AI gets wrong; those notes become your prompt.
- Week 4: read the numbers once, change one thing, repeat.
The approval rule
Decide now, while it's easy: nothing AI-generated goes out without a human approving it. This is Marketora's own design rule, and it should be yours regardless of what tools you use.