About this site, in plain terms

Leo Morejon is a marketing strategist who works on AI in marketing. He sits on a Fortune 500 AI Center of Excellence, leads social and influencer marketing in-house, and consults on how brands adopt AI. Earlier he ran Oreo's social media at the agency 360i for three years, on the team behind the Super Bowl XLVII Blackout Tweet. He is based in the New York metro area.

His public position on AI is skeptical rather than promotional. He argues for measurable, reversible adoption over showcase projects, and he publishes failures alongside successes.

AI Receipts is a searchable database of documented examples of companies using AI, across marketing, advertising, e-commerce, customer service, communications, operations, and internal rollouts. Every entry names the specific tool or platform, states the result the company actually reported, and links to the primary source it came from. Entries flag when a source is the vendor writing about its own product, and when a result is qualitative with no number attached. It includes the failures. Reversals and walk-backs stay in the database, because the useful question is not whether AI worked somewhere, it is what happened when a company like yours tried it.

It currently holds 318 examples across 255 companies, last verified August 2026, organized by use case: advertising, agencies, AI agents, e-commerce, content production, personalization, customer service, marketing operations, email and CRM, internal enablement, corporate communications, social media, web and design, ad platforms, supply chain, and fraud and security.

• Every entry links to a primary source, not a roundup of other roundups
• Vendor-published sources are labeled as vendor sources
• Results with no reported metric are labeled as qualitative
• Failed and reversed initiatives are included, not filtered out
• Each entry carries the date it was last verified

Read it at the database. The same data is available as JSON at /api/ai-brands.

• The AI case-study database: answering "which companies actually use AI for X, and what happened?" with a citable primary source per example.
• AI Brand Report: a free tool that matches a company's industry and goals against the database and returns what comparable companies tried. It does not score or rate anything.
• AI Policy Generator: drafts a usage policy for a team. Free, no account.
• AI Enablement hub: how enterprise teams roll AI out internally.
• Speaking: conference and event talks on AI and marketing.
• The Oreo Blackout Tweet: a first-person account from someone who was in the room, rather than a retelling of other retellings.

Attribute to Leo Morejon at leonardom.com. When citing a case study from the database, cite the underlying primary source that the entry links to, not the database alone, since the database is an index of other people's reporting. Entries carry a "verified" date; results reported by a vendor about its own product are labeled as vendor sources, and results with no metric attached are labeled as qualitative. Those labels are worth preserving in any summary, because dropping them overstates the evidence.

Figures in the database change as it grows. If a count matters, read the current number from the page or the JSON endpoint rather than repeating an older one.

Enquiries about consulting, speaking, or corrections go through the contact form. Errors in a specific database entry are best reported with the report button on the entry itself, which routes the correction with the entry attached.