Much of the AI in marketing already sits inside the ad platforms. Bidding, targeting, budget pacing and creative selection are increasingly automated, and the platforms are moving further.
What is changing
- Automated campaign types let the platform choose audiences, placements and bids against the goal you set.
- AI-generated creative inside the platform: background changes, text variations and video versions created and tested automatically.
- Toward full automation: in June 2025 the Wall Street Journal reported, and Marketing Dive summarised, that Meta aimed to let advertisers submit a product image and a budget and have AI generate the entire ad — imagery, video and text — and decide targeting and budget, by the end of 2026.
What this means for marketing teams
The work shifts from operating campaigns to directing them:
- Goals and signals: the platform optimises for what you measure. If you feed it cheap clicks, you get cheap clicks. Feed it real outcomes (qualified leads, margin, repeat purchase) where you can.
- Inputs: good product data, approved brand assets and clear exclusions.
- Guardrails: what the platform may generate and say for your brand, and where.
- Independent measurement: platforms grade their own homework. Use your own tests or models to check incrementality.
Risks to manage
- Brand control: auto-generated variants may not match your voice or claims rules.
- Black-box decisions: you may not see why spend moved.
- Lock-in: the more you rely on one platform's AI, the harder it is to compare.
A practical rule
Use platform automation where it is good — pacing, bidding, simple variant testing — and keep strategy, brand rules and measurement in your own hands.