Hiring in the Age of AI
A practical guide to recruitment in ecommerce and DTC - written for hiring managers and candidates.
6 stages · ~15 min read
WHAT'S YOUR GOAL?
This guide flips between two views. Choose the one that fits you.
Guide to Hiring in an AI World
If you're scaling a brand, the people you hire can make or break your growth, so it's one of the most important things to get right. AI can help with a lot of it, as long as you use it in the right places.
This guide walks through each stage of the recruitment process, from writing the brief to making the offer. For each stage we cover where AI is worth using and what to watch out for.
Our view is that AI should support your hiring decisions, not make them for you. That also keeps you on the right side of fairness. An algorithm screening out candidates on its own is where discrimination risk creeps in, so keep a human involved wherever a decision affects someone's chances.
We recruit for scaling ecommerce and DTC brands including Oner Active, Cowshed, Hera, The Beauty Crop, Wonderskin and Lapland, and our approach has always been people first.
Brands we've recruited for
Planning
AI earns its keep at the planning stage. Cost and headcount modelling gives you a fast budget sense-check. Drafting tools turn rough notes into a workable brief and advert in minutes - consistent format, SEO-friendly, ready to edit.
Rubbish in, rubbish out. Budget models are only as sharp as the numbers you feed them, and AI-drafted briefs miss the nuance of the role and your culture. Treat the output as a first pass, then edit hard for the specifics that make your brand yours.
Do this
Sourcing
Multi-board posting tools push a role out in one click. AI sourcing - LinkedIn Recruiter, Boolean builders - widens the net for passive talent and shortens the search.
Reach isn't the same as fit. Multi-board tools blunt your targeting; AI sourcing surfaces plenty of noise alongside the signal. The best DTC and ecommerce candidates still come through targeted channels, category communities and warm networks. AI covers ground - it doesn't replace category knowledge.
Do this
Case study
Wonderskin - filled roles in under 4 weeks
Wonderskin needed new people, fast. Through a combination of targeted outbound and category-specific networks, we found the candidates they needed in less than four weeks.
Screening
Volume is the real problem. AI screening chews through hundreds of applications fast and applies your criteria consistently. Transcription and summary tools cut screen-call admin. Matching scores speed up shortlisting.
This is where bias creeps in. Models trained on past hiring data replicate past patterns - quietly filtering out good candidates on university, career gaps or phrasing. Summaries lose tone. Ranking feels like a black box. Use AI as a first-pass filter with a human on the borderline cases - not as the final decision.
Candidates are polishing their CVs with AI too, so 'perfect on paper' means less than it used to. Treat AI screening as a filter, not a verdict.
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Interviewing
AI note-taking with sentiment and keyword flags gives you a consistent record and a lot less admin. AI-generated competency questions build a structured second interview. AI reference checks turn around faster than chasing referees yourself.
The downsides are human. Sentiment tools misread tone. Candidates don't love being scored by a machine. Scripted questions kill natural flow. AI reference checks miss the red flags a person would probe. Use the tools to remove admin - keep the judgement with people.
Do this
Offer & Contract
AI salary benchmarking replaces guesswork with data. AI contract generation gives you fast, consistent templates. AI document verification speeds up right-to-work checks and cuts manual error.
Benchmarks go stale, contract templates carry errors, and document checks throw false positives and negatives. Legal review and a real person on right-to-work sign-off are non-negotiable, however slick the tooling.
Do this
Case study
Oner Active - senior leadership across Product, Data & Performance
A long-standing partnership where we've placed senior leaders across Product, Data, and Performance Marketing as the brand scaled.
Onboarding
AI-driven portals and chatbots keep new starters engaged through pre-boarding and answer the FAQs on demand. Sentiment surveys at 30, 60 and 90 days flag disengagement before it turns into a resignation.
Overuse it and onboarding feels cold. A chatbot is no substitute for a proper human welcome, and sentiment data misses the context behind the score. Automate the repetitive stuff so your team has more time for the human moments that decide whether the hire stays.
Do this
Further reading
How this looks in practice
Oner Active - scaling senior leadership
How we built a long-term partnership placing leaders across Product, Data & Performance Marketing.
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The Beauty Crop - who to hire first
Helping a growing beauty brand work out the sequence of hires that unlocked their next stage.
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Lapland UK - first COO appointment
Executive search for a first-time COO role at one of the UK's most distinctive experience brands.
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Work With Us
Hiring for your ecommerce or DTC brand?
If you're hiring at an ecommerce or DTC brand and want recruitment support that understands the category and the tooling, that's exactly what we do. We've placed talent at Oner Active, Sculpted by Aimee, Hera, The Beauty Crop, Wonderskin, Lapland and more.
The Growth Foundation Talent Team