Mark B. Huntley, J.D. is an entrepreneur, digital publisher, marketing executive, former attorney, and AI-search researcher whose career has focused on building businesses and understanding how companies acquire customers. His professional experience spans more than two decades across: Entrepreneurship, Digital publishing, Search engine optimization, Affiliate marketing, Customer acquisition, Marketing, Technology, Business operations, Content systems, Financial management, Sales, Regulated industries, Legal analysis, and Executive leadership.
Today, Mark's work is increasingly focused on one of the most important changes taking place in digital discovery: What happens when consumers and business buyers begin asking AI systems which companies they should trust, compare, and choose? Through 3D Chess Media, LLM Authority Index, CiteWorks Studio, and The 3D Chess Media Portfolio, Mark works across the measurement, strategy, publishing, and commercial sides of that transition.
Mark Huntley at a Glance
Current Work
LLM Authority Index AI search intelligence, competitive benchmarking, recommendation measurement, citation analysis, and market research.
CiteWorks Studio AI search strategy, Generative Engine Optimization, Answer Engine Optimization, citation architecture, entity clarity, authority development, and competitive positioning.
The 3D Chess Media Portfolio Development and operation of category-specific consumer and business research properties.
Professional Background
- 20+ years building, marketing, operating, and scaling businesses
- 500+ digital properties overseen in a senior strategy role
- 250+ writers, editors, analysts, SEO specialists, designers, developers, and other contributors across approximately 30 countries
- 2,000+ articles per month produced within a publishing organization he helped lead
- More than $2 million in monthly operating expenses managed within that organization
- Former senior executive of an organization that generated more than $50 million in affiliate commissions
- Co-founder of CreditKnocks.com, later acquired by FinMasters
- Former law-firm managing partner
- Juris Doctor
- Current researcher of AI recommendations, citations, source influence, competitive visibility, and AI-mediated buyer behavior
A Career Built Around Customer Acquisition
A recurring theme throughout Mark's career has been understanding the systems that connect: discovery to trust to comparison to conversion to revenue, The technologies and platforms have changed. The commercial problem has not.
Businesses still need to understand:
- How do customers discover us?
- Why do they trust us?
- Who are they comparing us against?
- What influences the final decision?
- What actually produces profitable customer acquisition?
Mark has approached those questions from several sides of the business. He has built companies. He has managed marketing. He has operated publishing businesses. He has managed salespeople. He has bought traffic. He has overseen SEO and content organizations. He has worked with developers. He has managed budgets. He has operated affiliate businesses. He has built and sold a digital publishing property. And he has spent years looking at the connection between visibility and commercial outcomes. AI search is the newest layer of that journey.
Current Focus: AI-Mediated Buyer Choice
Mark's current research focuses heavily on the difference between simply appearing in an AI-generated answer and actually influencing a buyer's decision. A brand can be mentioned frequently without being recommended. A website can be cited even when another company's product is recommended. A company can appear in most answers while consistently ranking behind its competitors. Those distinctions matter. Mark's work examines questions such as:
- How often is a company genuinely recommended?
- Where does the company appear in the recommendation order?
- Which competitors consistently make the shortlist?
- Which AI platforms favor different companies?
- Which sources are cited?
- Which sources repeatedly appear around recommendation events?
- How is a company framed?
- Which strengths or weaknesses are emphasized?
- Which high-intent buyer questions matter most?
- Where do AI systems agree?
- Where do they disagree?
- How does recommendation behavior change over time?
The broader objective is to understand whether AI systems are simply aware of a company or are actually advancing that company toward buyer consideration.
LLM Authority Index
Measuring the Market
At LLM Authority Index, Mark leads work around AI-search strategy, methodology, product direction, research frameworks, competitive analysis, and commercialization. LLM Authority Index studies how organizations are: Discovered, Retrieved, Mentioned, Cited, Compared, Framed, Ranked, Recommended, and Excluded. across AI-generated answers and emerging search environments. The platform develops research and measurement around areas such as: AI Recommendation Share, Recommendation coverage, Recommendation rank, Top-three placement, Rank-one placement, Citation visibility, Source influence, Competitor inclusion, Brand framing, Sentiment, Buyer-intent prompts, Comparison prompts, Alternative prompts, Trust prompts, and Use-case prompts.
Mark also works directly with developers to translate marketing and market-intelligence questions into: Data structures, Automated research workflows, Prompt architectures, Evaluation logic, Quality controls, Reporting systems, and Longitudinal datasets. The goal is to move AI-search discussion away from guesswork and toward repeatable measurement.
CiteWorks Studio
Applying the Research
Research is one side of Mark's current work. Implementation is the other. Mark founded CiteWorks Studio to help companies improve how they are understood, retrieved, cited, compared, and recommended across AI-driven discovery environments. CiteWorks Studio works across areas that can include: Generative Engine Optimization, Answer Engine Optimization, AI Search Optimization, Citation architecture, Source ecosystem strategy, Entity clarity, Semantic positioning, Content architecture, Competitive positioning, High-intent prompt research, Technical SEO, and Digital authority development.
The underlying commercial question is straightforward: If AI systems are recommending competitors instead of your company, what can actually be changed? LLM Authority Index is intended to help identify the competitive condition. CiteWorks Studio is intended to help address it.
Building the Consensus Research Model
Mark is also involved in developing the broader research methodology used across parts of The 3D Chess Media Portfolio. The Consensus Index concept asks multiple AI systems substantially the same defined question and compares their responses. The research can examine: Which companies appear, Which companies are recommended, Recommendation position, Areas of agreement, Areas of disagreement, Supporting reasoning, Citations, Source overlap, and Changes over time. An important principle behind the model is that: machine agreement is not the same thing as objective truth.
If six AI systems recommend the same company, it is accurate to report that six systems recommended that company. It does not automatically establish that six independent experts proved the company is objectively the best. AI systems may rely on overlapping: Sources, Training information, Search results, Publisher ecosystems, Reviews, and Company claims. The useful research question is therefore not: “Did AI prove this company is the best?”, It is: “What are major AI systems recommending, how consistently are they recommending it, and what information appears around those recommendations?”.
The 3D Chess Media Portfolio
The Consensus Index methodology is applied across category-specific research properties within The 3D Chess Media Portfolio. These include research properties covering markets such as: Aging in place, Consumer credit, Life insurance, Mortgages, Home services, Business software, Home improvement, Moving, and Web hosting. Operating multiple properties gives Mark and the 3D Chess Media team an opportunity to study how AI-mediated discovery behaves across very different markets. A senior researching a medical alert system may ask very different questions from a company selecting business software.
A homeowner selecting a contractor may evaluate trust differently from a business buyer evaluating a hosting platform. These differences make category-specific research important.
Before AI Search: Digital Publishing at Scale
Mark's current work in AI search is built on years of experience in large-scale digital publishing. As Chief Strategy Officer of a global digital publishing organization, his responsibilities included: Company strategy, Growth, Digital publishing, Content, Technology, Research and development, Analytics, Financial planning, Monetization, and Global execution. The organization included: more than 500 websites, thousands of affiliate relationships, more than 250 writers, editors, SEO specialists, analysts, designers, developers, and other contributors, operations spanning approximately 30 countries, and more than 2,000 articles produced per month.
Mark also managed more than $2 million in monthly operating expenses within that organization. That experience gave him exposure to the complete digital publishing chain:
search → content → publishing → technology → analytics → conversion → monetization → profitability
Those same disciplines are increasingly relevant as discovery begins moving from lists of links toward AI-generated answers.
Commercial Accountability
Mark's approach to marketing has consistently emphasized business economics rather than traffic or visibility for their own sake. During his senior publishing role, the organization generated more than $50 million in affiliate commissions. His professional history also includes responsibility for large operating budgets, automation initiatives, publishing economics, technology investments, monetization, and profitability. The distinction matters. The objective is not simply: more traffic, or more impressions, or even: more AI mentions.
The objective is to understand whether visibility contributes to:
- Buyer consideration
- Customer acquisition
- Revenue
- Competitive position
- Long-term enterprise value
Marketing becomes strategically important when it becomes commercially meaningful.
Building and Selling CreditKnocks.com
Mark also has direct founder-level experience building a digital publishing business. He co-founded CreditKnocks.com, a consumer-credit and personal-finance publication focused on helping consumers understand credit scores, credit repair, credit building, loans, debt, and related financial decisions. Mark wrote hundreds of consumer-credit articles while helping build the site's: Publishing strategy, Search architecture, Customer journey, Organic acquisition, Affiliate relationships, Monetization, Conversion systems, and Financial model.
CreditKnocks.com was later acquired by FinMasters.
FinMasters continues to maintain a portion of Mark's author archive and identifies him as a former contributor and co-founder of CreditKnocks.com. The experience gave Mark first-hand exposure to the complete lifecycle of a digital property: concept to content to traffic to monetization to growth to sale, That experience influences how 3D Chess Media approaches its current portfolio. A website is not merely a collection of pages. It is a business asset.
Published Work and Third-Party Recognition
Mark's work and professional history have also appeared outside businesses he owns. His consumer-credit commentary has been referenced by publications and organizations including: Forbes, Old National Bank, AllBusiness, and FinMasters. FinMasters continues to publish a number of articles from Mark's prior consumer-credit work and maintains his former-contributor profile. His more recent work includes published research, industry reports, case studies, methodologies, and analysis concerning: AI search, Generative Engine Optimization, Answer Engine Optimization, AI recommendation behavior, Citation visibility, Source influence, Digital publishing, Affiliate marketing, Competitive visibility, and Customer acquisition.
Entrepreneurial Background
Mark's entrepreneurial career began well before AI search or digital publishing became his primary focus. His experience has included building and operating businesses across: Promotional products, Title insurance, Law, Consumer finance, Digital publishing, Marketing, Affiliate media, and AI-search research and consulting. An early promotional-products business served colleges, bookstores, fraternities, sororities, clubs, and student organizations. At its peak, Mark coordinated approximately 50 independent commission-based sales contractors while managing areas including: Customer acquisition, Sales, Supplier relationships, Pricing, Margins, Production, Fulfillment, Institutional relationships, and Financial performance.
That experience established an operating principle that continued throughout his later work: Marketing is valuable only when the economics underneath it work.
Experience in Regulated Businesses
Mark has also operated in industries where accuracy, documentation, process, and risk management are particularly important. He previously owned and operated Chilton Abstract & Title Insurance, a title and title-insurance business. His responsibilities included: Strategy, Operations, Financial performance, Client service, Business development, Workflow, Vendor relationships, Documentation, Quality standards, and Operating risk. He later practiced law and served as a managing partner of a law firm. Those experiences contributed to a professional approach that emphasizes: Evidence, Documentation, Precision, Risk, Claims analysis, and Clear distinctions between fact, inference, and opinion.
Those disciplines are particularly useful in an emerging field such as AI search, where marketing claims can move much faster than the available evidence.
Legal Education and Former Legal Career
Mark earned his Juris Doctor degree from the Thomas Goode Jones School of Law at Faulkner University. After law school, he practiced law and later served as Managing Partner of Latham, Huntley & Associates, PC. His legal work and firm-management responsibilities included areas such as: Contracts, Evidence evaluation, Negotiation, Risk analysis, Dispute resolution, Business operations, Staffing, Technology, Marketing, and Client acquisition. His legal background remains relevant to the way he evaluates evidence, claims, contracts, risk, and business relationships.
However, Mark has not practiced law for many years. He uses the professional credential: Mark B. Huntley, J.D. The J.D. indicates his legal education and former professional background. It should not be interpreted as representing that he currently practices law or provides legal advice through 3D Chess Media or any of its properties.
From Search Engines to AI Answers
Much of Mark's career developed during the era when search engines were the primary gateway to digital information. A typical high-intent customer journey might have looked like: Google search to publisher article to company website to reviews to comparison to purchase, That journey still exists. But another path is emerging: ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, or another AI system to AI-generated shortlist to follow-up questions to citations and supporting evidence to company comparison to purchase, This shift creates a new commercial problem.
A company can spend years building: Search rankings, Content, Brand awareness, Reviews, Authority, Publisher relationships, and Website traffic. and still discover that an AI system is recommending someone else. Mark's current work is focused on understanding that gap.
Research Philosophy
Several principles guide Mark's current AI-search and digital research work.
Measure What Actually Happened
Research should record observed results rather than substitute what we expected to see.
Separate Mentions From Recommendations
Being visible is not necessarily the same thing as being preferred.
Separate Citations From Recommendations
A website can be used as a source while another company receives the recommendation.
Follow Buyer Intent
A casual informational query and a high-intent provider-selection query can have very different commercial significance.
Preserve Disagreement
Different AI systems often disagree. That disagreement is useful information and should not be hidden.
Distinguish Observation From Causation
A metric changing after an intervention does not automatically prove the intervention caused the change.
Label Models and Estimates Accurately
Modeled commercial value should not be represented as booked revenue.
Disclose Commercial Interests
Potential conflicts should be visible.
Allow the Research to Produce an Uncomfortable Answer
A research methodology that can only produce the desired result is not a useful methodology.
Building 3D Chess Media
3D Chess Media brings together much of Mark's prior professional experience. Digital publishing. Marketing. Affiliate monetization. Search. Technology. Data. Customer acquisition. Business operations. Entrepreneurship. AI-search research. The company's businesses are different, but they share a common focus: understanding how information influences commercial decisions. LLM Authority Index measures emerging AI-search markets. CiteWorks Studio works with companies trying to improve their position within those markets.
The 3D Chess Media Portfolio develops and operates publishing properties across specific consumer and business categories. Together, these businesses give 3D Chess Media the ability to study digital discovery from the perspective of: researcher, publisher, marketer, operator, and business owner.
Selected Current Areas of Research
Mark's current work includes research into:
AI Recommendation Visibility
How frequently is a company genuinely recommended rather than simply mentioned?
Recommendation Position
When recommended, where does the company appear?
Buyer Intent
Which prompts represent meaningful commercial decisions?
Citation Visibility
Which websites are being cited by AI systems?
Source Influence
Which sources repeatedly appear around recommendation events?
Competitive Inclusion
Which competitors consistently enter AI-generated shortlists?
Brand Framing
How do AI systems describe a company's strengths, weaknesses, and market position?
Cross-Platform Agreement
Where do major AI systems recommend the same companies?
Cross-Platform Disagreement
Where do their recommendations materially diverge?
Historical Movement
Which companies are gaining or losing recommendation visibility over time?
What Comes Next
Mark believes AI-mediated discovery is still at an early stage. The technologies will change. The interfaces will change. The companies leading today's AI market may change. The underlying commercial question will remain familiar: How does a business earn consideration when a customer is deciding what to buy? 3D Chess Media is being built around studying that question across the next generation of digital discovery.
Connect With Mark
Mark's current work can be explored through:
3D Chess Media Corporate portfolio and business development
LLM Authority Index AI search measurement, competitive intelligence, and market research
CiteWorks Studio AI search strategy and implementation
The 3D Chess Media Portfolio Consumer and business research properties
LinkedIn →
About the J.D. Credential
Mark B. Huntley holds a Juris Doctor degree and previously practiced law. He is not currently engaged in the practice of law and does not provide legal advice through 3D Chess Media, LLM Authority Index, CiteWorks Studio, or The 3D Chess Media Portfolio. The professional credential used across these properties is: Mark B. Huntley, J.D.