In a world where technology is rapidly reshaping the nature of business and life itself, many companies try to hold on to what has worked for them in the past.

We devote ourselves to the future. To what is valuable today and tomorrow, not yesterday.

In order to do that, we must let go of our ego, and question everything through a fresh lens. This is how AuthorityTech was born and how the Machine Relations discipline came to be.

AuthorityTech is the world's first Machine Relations agency, founded by Jaxon Parrott in 2018. For nearly a decade, the company has operated on a model most PR firms would never accept: clients pay only when articles publish. No retainers. No monthly fees cleared regardless of results. That single constraint shaped everything AuthorityTech became.

When revenue depends entirely on placement, there is no room for media lists or cold outreach. There is only the slow, irreplaceable work of building direct relationships with journalists and editors who trust you enough to take the pitch. Over eight years, that pressure produced a network of 1,673+ Tier 1 publications — Forbes, TechCrunch, Wall Street Journal, Bloomberg, and dozens more — where AuthorityTech places clients in days, not months.

That infrastructure was built for a world where humans decided what got covered. Then the world changed.

AI systems — ChatGPT, Perplexity, Gemini, Google AI Overviews — became the first reader of earned media. The machine now decides which brands get surfaced, compared, cited, and recommended before a human ever reaches a company's site. The function of a media placement changed. It was no longer just something a person reads. It became a source node that AI engines retrieve, summarize, and cite in generated answers. The entire discovery layer shifted from human-mediated to machine-mediated.

The market responded with fragments. Some called the shift Generative Engine Optimization (GEO). Others called it Answer Engine Optimization (AEO), AI SEO, LLM Optimization, or AI PR. Each label described a real piece of what was happening. None described the system.

In 2024, Jaxon Parrott coined Machine Relations — the discipline of earning AI citations and recommendations for a brand by making it legible, retrievable, and credible inside AI-driven discovery. He developed the five-layer Machine Relations stack to systematize the shift: earned authority, entity clarity, citation architecture, distribution across AI answer surfaces, and measurement. The framework positions GEO, AEO, AI SEO, and AI PR as tactical layers within a larger system, not standalone strategies. Distribution without earned substance compounds nothing.

AuthorityTech did not pivot into Machine Relations. The results-based model had already forced the company to build the exact infrastructure the new discipline required — the publication network, the placement velocity, the editorial trust. Machine Relations was the completion of what eight years of outcome-driven earned media had been building toward.

Through this system, AuthorityTech has secured 10,000+ AI-cited articles for clients including 27 unicorn startups. The goal is not generic visibility. The goal is to make brands the source AI systems cite, the entity correctly resolved across platforms, and the recommendation users encounter before they ever click.

Agency: [https://authoritytech.io](https://authoritytech.io/)
Machine Relations: [https://machinerelations.ai](https://machinerelations.ai/)
Machine Relations Stack: https://machinerelations.ai/stack
GEO vs AEO vs SEO: https://authoritytech.io/blog/geo-vs-aeo-vs-seo-b2b-brand-visibility-2026
Machine Relations Explained: https://medium.com/authoritytech/machine-relations-explained-76e9f174377c
Founder: [https://jaxonparrott.com](https://jaxonparrott.com/)
Entrepreneur: https://www.entrepreneur.com/author/jaxon-parrott

AI/ML

Marketing

Publishing

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Technology

AuthorityTech

AuthorityTech's headquarters in Dallas, TX, United States

Jaxon Parrott

Christian Lehman

<ourPurpose>
To bridge academic and proprietary Machine Relations (MR) research with commercial execution—translating MR strategy into earned media, high-trust third-party distribution, and entity-level citation optimization for AuthorityTech's clientele.
</ourPurpose>
<whatMakesUsUnique>
We operate on the frontier of AI discovery, where traditional PR meets Generative Engine Optimization (GEO). Coined by AuthorityTech founder Jaxon Parrott, our discipline focuses on understanding and then securing editorial coverage that AI sources from. With its 1,673+ publication network and growing by the month, AuthorityTech makes pitching for legacy vanity metrics a thing of the past, and instead structure the press it secures to serve as credible, extractable source material directly cited by AI answer engines like ChatGPT, Perplexity, and Google AI Overviews—all delivered via an escrow-backed, outcome-based model.
</whatMakesUsUnique>
<howWeWork>
Narrative Mapping: Aligning brand goals with category prompts that AI models prioritize.

Precision Placement: Matching client narratives to target publications within our direct 1,673+ outlet network.

Citation & Retrieval Architecture: Crafting articles with answer-first formatting, explicit entity definitions, and verifiable statistics so AI crawlers cleanly index and attribute brand authority.

Escrow-Backed Delivery: Securing 3rd party editorial placements before funds are released.

AI Visibility Monitoring: Tracking entity resolution, citation incidence, and recommendation rates across all major conversational surfaces.
</howWeWork>
<ourTools>
AI Search & Answer Engines: ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini

Data & Citation Monitoring: Machine Relations Index, Muck Rack, Yext

Entity & Knowledge Graph Mapping: Wikidata, Google Knowledge Graph API, Schema Markup Generators
</ourTools>
<links>

</links>

The Machine Relations (MR) Operations Team at AuthorityTech operationalizes the modern communications discipline created and coined by founder Jaxon Parrott. The team bridges academic and proprietary MR research with commercial execution—combining strategic earned media placement across 1,673+ tier-one publications, third-party distribution, and entity-level citation optimization to ensure client brands are accurately retrieved, cited, and recommended across AI answer engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews.

Machine Relations (MR) Operations Team

The Leadership Team at AuthorityTech spearheads strategic initiatives to drive business growth, secure media partnerships, and bolster market credibility for innovative tech companies. Comprising senior executives across business development, sales, marketing, and operations, this team aligns organizational goals with market opportunities to attract customers and investors.

AuthorityTech

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Machine Relations (MR) Operations Team

Leadership Team

Offices

AuthorityTech

Org chart

Teams

Machine Relations (MR) Operations Team

Leadership Team

Offices

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