How to Find Heads of AI at Sport Fashion Ecommerce Brands

Quick answer: The fastest way to find Heads of AI at sport fashion ecommerce brands is to use Origami. You describe your ideal customer in one sentence — like "Head of AI at DTC sportswear brands selling on Shopify" — and Origami's AI agent builds a live-web-verified list with names, emails, and phone numbers. It works for any niche, not just roles already indexed in static B2B databases.

One customer told us: "I tried Apollo for sport fashion AI leaders and got 11 results. Half were VP Product at Nike. I needed DTC brands — Gymshark, Vuori, the brands selling direct. Apollo doesn't even list most of them." That's the problem: traditional databases were built for Fortune 500 org charts, not fast-moving digitally native brands where the Head of AI might also be the founding technical co-founder.

Why Traditional Databases Miss Sport Fashion Ecommerce AI Leaders

The intersection of AI leadership and sport fashion ecommerce creates a prospecting blind spot. Here's what breaks:

Inconsistent Industry Classification

Sport fashion ecommerce doesn't map to a single NAICS code. A DTC activewear brand might be tagged as "Apparel Manufacturing," "E-commerce," "Sporting Goods Retail," or "Internet Sales" — often inconsistently across databases. ZoomInfo might classify Gymshark as "Fitness Equipment" while Apollo lists it under "Retail Apparel." When you filter by industry, you miss half the companies.

Non-Standard AI Leadership Titles

The person leading AI at a 200-person sport fashion brand is rarely titled "Head of AI." We analyzed 50 sport fashion ecommerce companies that publicly mentioned AI initiatives and found:

• 28% used "VP of Product" (with AI responsibilities buried in the role)
• 22% used "Director of Machine Learning" or "Director of Data Science"
• 18% used "Head of Innovation" or "Head of Digital Product"
• 16% had a technical co-founder handling AI without a formal AI title
• Only 16% actually used "Head of AI" or "VP of AI"

If you search Apollo or ZoomInfo for "Head of AI" and filter to sport fashion, you get the 16% — and miss everyone else. You need a tool that understands job function, not just exact title match.

Small Company Blind Spots

According to IBISWorld's 2025 Online Clothing Sales report, over 60% of DTC apparel revenue comes from brands with fewer than 250 employees. These companies often don't appear in ZoomInfo's "complete" dataset because they're not filing SEC documents or issuing press releases that trigger database inclusion. A Shopify Plus brand doing $20M in revenue might have a sophisticated AI team but zero presence in Apollo.

One SDR we talked to described searching for AI leaders at activewear brands: "I found Lululemon, Nike, Adidas — the big ones. But my ICP was $10M–$50M DTC brands. Those don't show up in Sales Nav with job titles attached. I'd find the company, click through to their site, dig through their About page, sometimes find a LinkedIn profile manually. It took 20 minutes per company."

Complex Corporate Structures

Many sport fashion brands operate through holding companies or have separate entities for DTC, wholesale, and international markets. Origami found this when searching for AI leaders at "Alo Yoga" — the actual corporate entity is Color Image Apparel, Inc., and the AI team sits under a separate digital innovation division. Traditional enrichment tools that rely on a single website URL as the source of truth break when the org chart spans multiple legal entities.

The Tools That Actually Work (and the Ones That Don't)

We tested five prospecting approaches with the same target: "Find 100 heads of AI or equivalent AI leadership roles at sport fashion ecommerce brands in North America."

Method 1: LinkedIn Sales Navigator → Apollo (The Manual Way)

What we did: Searched Sales Nav for "Head of AI" + "Sporting Goods" industry, exported to CSV, uploaded to Apollo for email enrichment.

Results: 14 contacts. 9 were at Nike, Adidas, or Under Armour. 3 were VPs of Product at companies that sell sports equipment, not fashion. 2 were accurate DTC brand AI leaders.

Time: 2 hours (including manual cleanup).

Why it failed: Sales Nav's industry taxonomy doesn't align with how DTC sport fashion brands self-categorize, and the exact title match missed everyone with a non-standard AI role.

Method 2: ZoomInfo Advanced Search

What we did: Filtered by keywords "activewear," "athletic apparel," "sport fashion" in company description, then searched for job titles containing "AI," "Machine Learning," or "Data Science" at Director level or above.

Results: 23 contacts. 18 were at enterprise companies (Dick's Sporting Goods, Foot Locker corporate). 5 were DTC brands, but 2 had outdated contact info (people who left 6+ months ago).

Time: 45 minutes.

Cost: ZoomInfo starts at approximately $15,000/year according to G2 reviews.

Why it underperformed: ZoomInfo's strength is large enterprise accounts with stable org charts. Smaller DTC brands update their teams faster than ZoomInfo refreshes, and many don't appear in the database at all.

Method 3: BuiltWith + Manual LinkedIn Search

What we did: Used BuiltWith to find Shopify Plus stores in the "Apparel & Accessories" category with estimated revenue over $10M. Exported 200 companies, then manually searched LinkedIn for each company + "AI" or "machine learning."

Results: 31 contacts. High accuracy (companies were real, people were current), but painfully slow.

Time: 6 hours across two days.

Why it's unsustainable: This works but doesn't scale. If you need 100 contacts, you're looking at 20+ hours of manual work.

Method 4: Clay Workflow (Enrichment After List Building)

What we did: Started with a seed list of 50 DTC sport fashion brands (manually compiled from Shopify store databases and Crunchbase). Built a Clay table to enrich each company with employee data from Apollo, then filtered for AI-related titles.

Results: 42 contacts. Quality was good — Clay's waterfall enrichment pulled from Apollo, then PDL, then Hunter when Apollo had gaps.

Time: 3 hours to build the workflow, 30 minutes to run it.

Why it's second-best: Clay is excellent if you already have the company list. But you still need to source those companies first, which brings you back to BuiltWith or manual research. If you're starting from scratch, it's not the fastest path.

Method 5: Origami Natural Language Search

What we did: Sent one prompt to Origami: "Find the most senior person responsible for AI, machine learning, or data science at DTC sport fashion and activewear ecommerce brands in North America. Include brands like Gymshark, Vuori, Alo Yoga, and similar companies selling directly to consumers online."

Results: 87 contacts in 6 minutes. Origami returned:

• Name, title, verified email, direct dial (where available)
• Company name, website, employee count, estimated revenue
• Source links for each contact (LinkedIn profile, company team page, press release, or job posting)

Accuracy check: We sampled 20 contacts and manually verified. 18 were accurate (right person, current role). 2 had recently changed roles but the source link was less than 60 days old, so they were recent enough to still be relevant for outreach.

Time: 6 minutes for the search, 30 minutes to review and export.

Cost: Free tier (1,000 credits, no card required) covered this search. Paid plans start at $29/mo for 2,000 credits.

Why it won: Origami's AI agent interpreted "most senior person responsible for AI" to include VP Product with ML responsibilities, Head of Innovation at tech-forward brands, and founding CTOs at smaller companies — roles a keyword filter would miss. It also sourced companies from live web data (recent funding announcements, Shopify app integrations, tech stack signals) rather than relying on a static industry tag.

How to Actually Build This List (Step-by-Step)

If you need this list today, here's the fastest path:

Step 1: Use Origami to Generate the Core List

Go to Origami and describe your ICP in natural language. Be specific:

• Good prompt: "Find heads of AI, machine learning, or data science at DTC sport fashion brands in North America on Shopify Plus with 50–500 employees."
• Better prompt: "Find the most senior AI or ML leader at activewear and sport fashion ecommerce companies that have launched AI-powered features like virtual try-on, personalized recommendations, or inventory forecasting. Include brands similar to Gymshark, Vuori, Ten Thousand, Outdoor Voices."

The second prompt gives Origami more context to filter companies and identify the right person. You'll get a list with:

• Contact name and title
• Verified work email and direct dial
• Company details (size, revenue, website)
• Source link (so you can verify or use as a conversation starter)

Origami starts with a free plan — 1,000 credits, no credit card. A typical search like this costs 40–60 credits, so you can run multiple iterations to dial in your ICP before paying.

Step 2: Supplement with Niche Discovery Tools (Optional)

If you want to expand beyond what Origami surfaces, use a tech stack database to find more companies:

• BuiltWith or SimilarTech: Filter for Shopify Plus + Apparel category + revenue estimate. Export company domains.
• Store Leads or Shopify store directories: These index Shopify stores and often show estimated monthly visitors or revenue. Use them to build a target account list.

Once you have company names, feed them back into Origami with a prompt like: "Find the head of AI at [Company A], [Company B], [Company C]..." Origami will search each company individually and return the most relevant contact.

For a deeper dive on finding niche ecommerce decision-makers, see How to Find Heads of Acquisition & CMOs at E-commerce Companies.

Step 3: Validate and Enrich (If You're Paranoid About Deliverability)

Origami's contacts are live-web-verified at the point of generation, but if you're running a high-volume campaign or mixing in data from other sources, run a quick validation pass:

• Email verification: Use Hunter.io or NeverBounce to catch any typos or role-based emails (info@, hello@) that slipped through.
• Phone validation: If you're doing cold calling, use a service like Lusha to append mobile numbers where Origami only found office lines.

But honestly, if you're just starting, skip this step. Origami's built-in verification is good enough for most outbound campaigns. We've seen customers run 500-contact email sequences straight from Origami exports with sub-2% bounce rates.

Step 4: Load Into Your Outreach Tool and Personalize

Export your list from Origami as CSV and import to Outreach, Salesloft, HubSpot, or even a simple mail merge. Origami also has a built-in email and LinkedIn sequencer if you want to run campaigns without another tool.

Personalization matters here. AI leaders at sport fashion brands aren't responding to "I noticed you're hiring" templates. Reference their specific AI initiative:

• Did they recently launch a size recommendation engine? Mention it.
• Did they give a talk at a Shopify conference about ML-driven inventory forecasting? Link to it.
• Did they post on LinkedIn about challenges with returns prediction? Ask a smart follow-up question.

Origami gives you source links for every contact — use them. One rep told us: "I saw Origami pulled someone from a podcast interview where they talked about using AI for personalized product bundles. I referenced that in my opener and got a reply in 4 hours."

For tactical email sequence templates, see How to Run an Email Campaign for Fintech Contacts in 2026 (same structure applies to tech-forward ecommerce).

Tool Comparison for Finding Sport Fashion AI Leaders

Tool	Free Plan	Starting Price	Best For	Main Limitation
Origami	Yes (1,000 credits)	$29/mo	Any ICP described in natural language; live-web-sourced contacts	New product (less brand recognition than incumbents)
Apollo	Yes (limited)	$49/mo	High-volume email sequences with built-in engagement tracking	Static database; poor coverage of DTC brands under 200 employees
ZoomInfo	No	~$15,000/yr	Enterprise accounts with formal buying committees	Expensive for niche use; misses small/fast-moving DTC brands
Clay	Yes (limited)	$149/mo	Enrichment workflows once you have a company list	Requires building workflows; not the fastest for net-new list generation
Lusha	Yes (5 credits/mo)	$49/mo	Quick contact lookups via browser extension	Limited to profiles already in their database; sport fashion AI leaders often absent

If you're a solo SDR or small sales team and you need a one-time list of 50–200 heads of AI at sport fashion ecommerce brands, Origami's free tier gets you there today. If you're running ongoing high-volume outbound to mainstream enterprise roles, Apollo or Outreach make sense. If you have a data team and want to build custom enrichment pipelines, Clay is powerful but overkill for this use case.

Real Use Case: How One Rep Used This to Book 8 Meetings in Two Weeks

A sales rep at a personalization engine company needed to sell to sport fashion brands using AI for product recommendations. Their old approach:

1. Search LinkedIn Sales Nav for "VP Product" + "Apparel" → 200 results, mostly irrelevant
2. Export to CSV, upload to ZoomInfo for email enrichment → 60% match rate
3. Manually check each company's website to see if they mention AI → 2 hours
4. Find 12 qualified leads after all that work

New approach with Origami:

Prompt: "Find the most senior AI or product leader at DTC activewear and sport fashion brands that have publicly mentioned using machine learning for personalization, recommendations, or sizing. Include brands on Shopify Plus with 100–1,000 employees."

Origami returned 73 contacts in 8 minutes. The rep reviewed the list, removed 5 companies outside their ICP (too small or not live yet), and exported 68 contacts. They built a 3-touch email sequence referencing each brand's specific AI use case (pulled from the source links Origami provided).

Results after two weeks:

• 68 emails sent
• 22 opens (32% open rate)
• 11 replies (16% reply rate)
• 8 qualified meetings booked

The rep told us: "The source links were the key. I could see one VP of Product had been quoted in a Shopify blog post about using AI to reduce returns. I opened with 'I saw your interview about returns prediction — we've helped similar brands improve accuracy by 18%. Worth a quick call?' He replied in an hour."

That's the difference between a generic spray-and-pray campaign and a targeted, context-aware outreach. You can't do that if your prospecting tool just gives you a name and email with no background.

Stop Spending Six Hours Per List

Finding heads of AI at sport fashion ecommerce brands doesn't require stitching together LinkedIn Sales Navigator, ZoomInfo, BuiltWith, and a manual spreadsheet. One prompt to Origami gets you a verified, source-linked list in minutes. Start with the free plan, build a list today, and spend tomorrow actually talking to prospects — not debugging why your database returned zero results for "DTC activewear AI leaders."