AI
Where AI fits in your marketing stack (and where it doesn’t)
AI is good at drafts, variations, sorting and summarising. It’s bad at judgement, accountability and knowing your customers. A grounded guide to using it without losing trust.
The Web Pundit Team · AI & Automation ·
Every marketing tool now has an AI button. Some of them are genuinely useful. Some are a chatbot in a trench coat. The question isn’t whether to use AI. It’s where in your workflow it helps, where it hurts, and who checks its work.
This is our working map. No percentages, no miracle case studies. Just where we’ve found AI earns its place and where we keep humans firmly in charge.
Where AI earns its place
First drafts and variations
AI is fast at producing a starting point: ten subject lines, five ad headline angles, a rough outline for a guide. That’s valuable, because a blank page is slow. But a first draft is exactly that. A person who knows the product and the customer turns it into something worth publishing.
Summarising and sorting
Large volumes of text are where AI shines: tagging support tickets by theme, summarising survey responses, clustering search queries into topics, pulling the main points from a long sales call transcript. It does in minutes what used to take an afternoon. A person still reads a sample to check the sorting makes sense.
Repurposing content you already own
Turning a webinar into a blog outline, a long article into social posts, or a product page into an FAQ draft. Because the source is yours and already approved, the risk is lower. You’re reshaping facts, not generating them.
Operational glue
Routing form submissions to the right team, drafting a first reply for a person to approve, cleaning up messy CRM fields, writing alt text drafts for a large image library. Small, repetitive jobs where a mistake is easy to spot and cheap to fix.
Where AI doesn’t belong (on its own)
Facts, figures and claims
Language models can produce confident, fluent text that is simply wrong. They can invent statistics, misquote sources and describe features your product doesn’t have. Anything factual that goes out under your name needs checking against a real source by a real person. No exceptions for ‘it’s just a social post’.
Strategy and positioning
AI can list options. It can’t know that your best customers chose you for the after-sales service, or that a competitor is about to cut prices. Positioning comes from talking to customers and making a choice. AI can help you organise that thinking. It shouldn’t make the decision.
Sensitive conversations
Complaints, refunds, anything involving health, money or personal circumstances. An automated reply that misreads the tone can turn an unhappy customer into a public one. Let AI draft and summarise. Let a person respond.
Fake social proof
Generated reviews, invented testimonials and synthetic ‘customer’ photos are dishonest, and in many places they also break platform rules and consumer protection law. They’re also the fastest way to lose trust once someone notices. Don’t.
Privacy is not optional
Before you paste customer data into any AI tool, find out where it goes. Does the provider store it? Use it to train models? Which country is it processed in? Business and enterprise plans from major providers often offer different data terms from free consumer versions. Read them.
- Strip names, phone numbers, emails and anything identifying before using customer text in AI tools, unless you have a clear agreement covering that data.
- Keep a simple register of which AI tools your team uses, and for what.
- If you operate in India, factor in the Digital Personal Data Protection Act, 2023, and take advice on how it applies to you. Other markets have their own rules.
- Tell customers when they’re talking to an automated assistant, and give them a route to a person.
Human review, built in
‘A human checks it’ only works if it’s a defined step, not a good intention. For every AI-assisted workflow, write down three things.
- Who reviews the output, by role.
- What they check: facts, tone, brand, legal claims, links.
- What happens when it’s wrong: who fixes it and how the workflow improves.
The reviewer must have the authority to reject the output, and the time to actually read it. A rubber stamp isn’t review.
Keep your brand voice yours
Left alone, AI writing drifts towards the same smooth, generic tone everyone else’s AI writing has. That’s a problem when your voice is part of why people choose you. Give the tool a short style guide: words you use, words you never use, sentence length, how you address customers, and two or three examples of your best existing copy. Then edit hard. If a paragraph could appear on a competitor’s site unchanged, it isn’t finished.
Search engines care about this too, in their own way. Google’s guidance says it rewards helpful, original content however it’s produced, and treats mass-produced pages made mainly to manipulate rankings as spam. Publishing hundreds of thin AI pages is a risk, not a strategy.
Start small, measure honestly
Pick one repetitive job that eats time and has a low cost of error. Write down how long it takes today and what good output looks like. Try AI on it for a month with review in place. Compare time spent and quality, honestly, including the time spent checking and fixing. If it helps, keep it and pick the next job. If it doesn’t, stop. That’s a result too.
AI is a very fast junior who never gets tired and never says ‘I don’t know’. Brief it well, check its work, and don’t let it sign anything.
The verdict
AI belongs in your marketing stack as a drafting, sorting and summarising engine, with people in charge of facts, strategy and sensitive moments. Protect your customers’ data. Make review a real step. Measure what it actually saves. Used like that, it gives your team time back for the work only they can do.
