Generic AI writes generic marketing. Industry context is the whole game.

Ask a frontier model to “write a promotional email for our clinic's new weight-management program” and you'll get fluent, confident copy — that may casually violate health-claims rules, ignore that patient testimonials are regulated, and miss that in this category, trust signals outperform urgency tactics roughly always. The model isn't weak. It's uncontextualized. Marketing competence is mostly context.

What industry context actually contains

• Regulatory boundaries. Health claims, financial promotions, alcohol, supplements, anything touching minors — each has rules where “oops” is expensive. A marketer who doesn't know them isn't junior; they're a liability.
• Benchmark sanity. Is a $90 CPL good? In enterprise B2B software, often excellent; in local home services, a disaster. Without sector benchmarks, an AI can't tell triumph from failure — and will optimize toward the wrong one with great efficiency.
• Channel-category fit. TikTok works for B2C impulse and surprisingly well for trades recruiting; LinkedIn earns its CPMs in B2B and wastes them in e-commerce. Strategy is mostly knowing these priors before spending to rediscover them.
• The playbook library. What sequence actually moves a 90-day-consideration buyer vs. an impulse one; which proof points matter in fintech vs. fitness. Experts aren't smarter — they've seen more games.

The maturity dimension

Context has a second axis: your stage. The right advice for a company doing its first paid campaign (“one channel, one offer, learn the mechanics”) is opposite to the right advice at $300K/month (“incrementality testing and saturation curves”). Generic AI gives stage-less advice — usually a blurry average of beginner and advanced that serves neither.

How to evaluate any AI marketing tool on this

Three questions. Does it ask your industry and actually change behavior based on the answer — different benchmarks, different compliance gates, different channel priors? Can it cite why (“category benchmark for your sector is X”) rather than asserting? And is the expertise evaluated — does the vendor test the system against sector-specific scenarios, or just ship a system prompt with your industry name in it? The last one separates trained from costumed.

Where Mayaa fits

This is the heart of how Mayaa is built: every agent is trained on thousands of digital-strategy models across ~20 industry sectors and three maturity levels — playbooks, benchmarks, and compliance rules retrieved per client, enforced at the point of action (a non-compliant claim gets blocked before it reaches your approval inbox, not after it ships). Each agent passes sector-specific evaluations before it's allowed to serve that sector. Generic AI is a great intern. Trained AI is a hire.