Hiring your first Head of AI is tricky. There are plenty of brilliant candidates out there, but there are also plenty who can talk a big game without actually having the experience to build, deploy, and maintain AI systems in a real business environment.
The goal of these questions is not to trip someone up for sport. It is to quickly figure out if the person sitting across from you has the technical depth, strategic thinking, and retail context to lead AI for your fashion brand.
If they stumble here, you can save yourself months of wasted time and a six-figure mistake.
1. “Tell me about an AI or ML project you delivered from concept to deployment. What was the measurable business impact?”
The good candidates will:
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Describe a real-world project in detail.
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Share the actual business problem it solved.
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Cite measurable results such as lift in conversion rate, improvement in forecast accuracy, or operational cost savings.
The pretenders will:
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Speak in vague buzzwords like “leveraged AI to improve business processes.”
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Fail to explain how success was measured or confuse correlation with causation.
2. “If we wanted to launch a personalization engine for our e-commerce site, what are the first three data sources you would prioritize and why?”
The good candidates will:
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Reference customer behavior data, transaction history, and product catalog data at a minimum.
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Talk about data quality, integration, and how these sources connect to the personalization logic.
The pretenders will:
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Suggest “using all available data” without explaining the tradeoffs.
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Skip any mention of cleaning or standardizing data before modeling.
3. “How would you handle the cold-start problem for personalization with new customers or products?”
The good candidates will:
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Discuss techniques such as collaborative filtering with lookalike modeling, content-based filtering, or hybrid approaches.
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Explain how they would blend AI with merchandising rules to ensure fashion context.
The pretenders will:
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Have no idea what the cold-start problem is.
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Suggest “collecting more data” without a plan for the interim.
4. “What are the top two AI risks you see for a fashion retailer, and how would you mitigate them?”
The good candidates will:
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Talk about bias in recommendations, over-reliance on automated forecasting, or compliance risks with customer data.
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Provide practical mitigation steps such as regular model audits, bias testing, and fallback rules for edge cases.
The pretenders will:
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Only mention generic AI ethics statements.
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Avoid concrete actions or policies.
5. “You have been hired and we have given you 90 days to make an impact. What are your first three priorities?”
The good candidates will:
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Outline a plan that balances discovery with quick wins.
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Mention specific deliverables such as a data audit, initial use case roadmap, and cross-functional alignment sessions.
The pretenders will:
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Say they will “spend the time learning the business” without committing to deliverables.
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Fail to tie their work to measurable outcomes.
Pro Tip for Interviewers
When asking these questions, do not jump in to “help” if the candidate is struggling. The pauses are telling. If they have really done the work, they will have no problem answering.
The Bottom Line
Fashion brands and retailers do not have the time or budget to hire an AI leader who is learning on the job at your expense. These five questions are not a full technical interview, but they will help you separate real AI leadership talent from buzzword enthusiasts before you waste months figuring it out the hard way.
If you pair these questions with the recruiting and compensation strategies from our last article, you will drastically increase your odds of finding a Head of AI who can deliver measurable runway impact instead of just runway talk.
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