For more than 20 years, internet marketing has generated billions of dollars for both small and large businesses.

As one of the first business school professors and lawyers to publish peer-reviewed research on internet recruiting and marketing, I have watched this evolution firsthand.

Traditionally, visibility online meant ranking on search engines, competing for keywords, and fighting for links & clicks. Later, social media platforms introduced demographic and behavioral targeting, showing targeted ads and content based on strategic variables.

That era, however, is rapidly changing.

Today, consumers increasingly turn to AI-powered systems such as ChatGPT, Gemini, Claude, Copilot, and Perplexity for direct answers, recommendations, and summaries.

These platforms will inevitably monetize results and eyeballs in one way or another, but the structural shift in how information is delivered is already irreversible. ^{[i] [ii]}

Because modern AI chats and systems are largely an extension of existing products and services offered by highly profitable FANG-level technology companies, the idea of a classic “Tech AI bubble” is overstated.

AI is being embedded into proven revenue engines such as cloud platforms, search, advertising, enterprise software, and consumer ecosystems, not built as speculative standalone ventures.

These companies are funding AI development with operating cash flow, using it to improve efficiency, deepen customer lock-in, and expand monetization.

As a result, AI functions as a value-enhancing layer on mature business models rather than a hype-driven gamble, making a broad AI bubble unlikely.

This expansion and transition from search, to social, to AI, has understandably created anxiety for small businesses.

Many ask how an AI could ever reference their company if they do not rank first on Google.

The answer lies in a new discipline known as Generative Engine Optimization, or GEO. GEO does not replace traditional SEO, but it operates on fundamentally different principles.

Rather than focusing on just keywords, rankings and backlinks, GEO generative AI systems rely on structured data, recognized entities, trust signals, and broad consensus across reliable sources.

In simple terms, AI systems internally assess whether a business is real, clearly defined, credible, and relevant enough to be safely included in an answer.

GEO or Generative Engine Optimization is the process of shaping a business’s digital presence so that AI systems can accurately understand, trust, and reference it when generating responses.

Unlike traditional search engines, AI does not browse the web in real time like a human user. Instead, it synthesizes information from structured and semi-structured data, reputable third-party sources, consistent descriptions across the web, and previously validated content.

GEO is, therefore, not about visibility among 10 blue links but about being recognized as a legitimate and verifiable entity within an AI’s knowledge framework.

For small businesses, GEO matters more than ever. These businesses face intense competition, limited advertising budgets, and diminishing organic reach.

GEO reduces reliance on paid ads, rewards specialization over scale, emphasizes credibility instead of hype, and compounds over time once entity trust is established.

Unlike traditional SEO, where large brands often dominate through sheer spending power, GEO favors clarity, expertise, and consistency—areas where small businesses can compete effectively and sustainably.

It is also important to confront a hard truth: most small businesses will never be named by AI systems. Generative AI is not a directory or a Yellow Pages replacement. It is an answer engine.

In most cases, AI references categories rather than individual firms, provides illustrative examples instead of exhaustive lists, and defaults to the safest and most verifiable entities.

This does not mean small businesses are excluded, but it does mean they must understand when and why AI chooses to name specific organizations.

Small businesses are most likely to be referenced when user intent is local or transactional.

Queries such as “reputable estate planning attorneys in Denver” or “best CPA firms for small businesses in Austin” prompt AI systems to draw from Business Profiles, local directories, professional licensing bodies, and consistent name-address-phone data.

In these scenarios, local clarity consistently outweighs national visibility. Other profiles of interest are: Apple Maps, Yelp, LinkedIn, D&C Dunn, public filings, and trusted business industry directories. ^[iii]

AI systems also strongly favor businesses that clearly occupy a narrow niche. A small firm with a precise specialization is far more likely to be referenced than a larger organization with a vague or generic description.

Examples include a boutique CPA firm specializing in crypto taxation for startups or a fiduciary wealth advisor focused exclusively on physicians nearing retirement. Specialization increases machine confidence, while generality introduces ambiguity—and ambiguity is usually ignored.

Third-party validation plays a critical role in GEO. AI systems place greater trust in what others say about a business than in self-promotional claims.

Mentions by professional associations, accreditation bodies, chambers of commerce, universities, trade publications, and government or nonprofit listings all function as powerful trust signals.

Even a small number of credible third-party references can significantly improve AI recognition. ^[iv]

Authoritative, well-structured content also matters, but not in the form of blog spam or keyword-stuffed articles.

AI systems rely heavily on explanatory materials such as FAQs, plain-language guides, definitions, and “how it works” pages. Content that performs well for GEO is clear, factual, professionally written, and focused on answering real questions. AI does not reward hype; it rewards clarity and coherence. ^[v]

Consistency across the web is one of the strongest yet most overlooked GEO signals. Businesses are frequently ignored when AI encounters conflicting descriptions, inconsistent services, or mismatched names and locations across platforms.

When inconsistencies appear, AI often discards the entity entirely as unreliable. Maintaining uniform descriptions across websites, directories, profiles, and publications is therefore essential. ^[vi]

Another powerful pathway into AI recognition is appearing in educational or professional materials.

Businesses referenced in white papers, academic or professional PDFs, industry guides, certification programs, or training manuals often enter secondary AI knowledge layers, where content is reused and paraphrased over time. This is how relatively unknown experts gradually become familiar entities to AI systems. ^[vii]

Small businesses should also be cautious about what does not work. Claims about “AI SEO hacks,” prompt stuffing, paid AI ranking schemes, plugin shortcuts, or keyword flooding are misleading.

At present, there is no legitimate paid shortcut to being referenced by generative AI. Any agency promising guaranteed AI citations is misrepresenting how these systems function.

A practical GEO strategy does not require complexity. Over a ninety-day period, businesses should define a single, clear entity description with one primary niche and geographic or industry focus.

All public profiles—such as Google Business, LinkedIn, industry directories, and professional associations—should be corrected and unified.

Publishing five to 10 authoritative pages that explain services, audiences served, processes, expectations, and common mistakes provides AI-friendly clarity. Securing a small number of credible third-party mentions through associations, trade publications, expert quotes, or local press further reinforces trust.

Above all, factual, consistent, and even “boring” content performs best. AI trusts boring; humans decide to buy later. ^[viii]

Generative AI will never replace localized directories like Yelp, online Maps, or Yellow Pages. Its purpose is to answer questions, not catalog businesses.

The organizations that succeed in this environment will not be the loudest or flashiest, but the clearest, most specialized, and most verifiable.

Generative Engine Optimization is not about manipulating AI systems. It is about becoming understandable to machines and trustworthy to humans at the same time.

For small businesses willing to prioritize clarity, authority, and consistency, GEO represents not a threat, but a lasting strategic advantage.

As a pioneer in internet recruiting analysis, I can confidently say that individuals and companies increasingly want to be seen in a positive light across AI-driven searches.

This alone is likely to increase search activity related to personal and business reputation management, including so-called vanity searches.

At present, AI platforms such as ChatGPT and Microsoft Copilot appear to rely heavily on web results, news sources, established lists or directories, and encyclopedic data.

These systems are powered by large language models, which are essentially vast databases trained on information up to a defined cutoff date.

Copilot, for example, demonstrates strong access to current news, while other platforms may lag in areas such as sports or real-time information.

Perplexity is particularly strong in research and citation-oriented queries, while Google Gemini continues to close the gap as Google attempts to recover search traffic it appears to have lost over the past eighteen months.

Today, a growing ecosystem of specialized AI platforms is transforming how professionals work in research, medicine, and law. In academic and scientific research, tools such as Gemini Deep Research, OpenAI Deep Research, Elicit, Consensus, Scholarcy, and PubMed AI accelerate literature review, evidence synthesis, and hypothesis development.

In medicine and clinical research, platforms like OpenEvidence, Deep 6 AI, Viz.ai, PathAI, and Watson for Oncology support diagnostics, clinical trials, and evidence-based care.

In the legal sector, advanced systems such as Lexis+ AI, Harvey AI, ROSS Intelligence, Robin AI, and Everlaw are reshaping legal research, contract analysis, and litigation workflows, signaling a shift from general-purpose AI toward domain-specific intelligence built for professional accuracy and depth.

Beyond search, generalized AI is advancing rapidly in fields such as contract analysis, medical research support, and financial modeling—while still respecting legal and medical compliance boundaries. In regulated industries like law, medicine, and finance, AI is increasingly useful for issue spotting, data analysis, and second-opinion frameworks.

However, access to historical and proprietary datasets from financial data companies like Bloomberg or Renaissance Technologies remains unclear.

At the same time, AI is making extraordinary progress in creative industries including music, publishing, film production, and visual art. While subject-matter experts remain essential for AI quality control, it is no longer necessary to play an instrument or use a paintbrush to produce high-quality creative work.

Having published more than one hundred books prior to the rise of AI, I can say with confidence that these tools are exceptionally powerful for deep analysis, comparison of ideas, and the repurposing of existing copyrighted content for the production of books, art, music, and publications.

In sum, GEO reflects a broader economic shift away from keyword manipulation and toward entity trust. The future of search belongs to those who understand that being known, consistent, and credible matters more than being loud. Staying visible and availing ourselves to customers is the nature of marketing and sales.

The key is letting customers know that you have products and services that are the solutions to their needs, and AI is going to be the biggest tool in sales for generations to come.

_______________
Commissioner George Mentz JD MBA CILS CWM® holds a Doctor of Jurisprudence (JD), and an MBA from ABA and AACSB Accredited programs. Mentz is the first in the USA to rank as a Top 50 Influencer & Thought Leader in: Management, PM, HR, FinTech, EdTech, Wealth Management, and B2B according to Onalytica.com and Thinkers360.com. George Mentz JD MBA CILS is a CWM Chartered Wealth Manager ®, global speaker - educator, tax-economist, international lawyer and CEO of the GAFM Global Academy of Finance & Management ®. The GAFM is a EU accredited graduate body that trains and certifies professionals in 150+ nations under standards of the: US Dept of Education, ACBSP, ISO 21001, ISO 991, ISO 29993, QAHE, ECLBS, and ISO 29990 standards. Mentz is also an award-winning author and award winning graduate law professor of wealth management of one of the top 25 ranked law schools in the USA and is founder of the ChE Chartered Economist ® certification & education programs. George Mentz has served as a White House Commissioner, and has served the Civil Service Commission for Police and Fire and the Airport Commission (Home of Space Force). Comm'r Mentz is one of the few lawyers who has ever earned Wall Street Firm licenses of Series 7,63, and 65 , served as a Judge for the ABA, has led civil litigation cases in fraud and defamation, as well as testified as an expert in FINRA/NASD financial arbitration.

^[i] Mentz, Dr./Jur. George & Whiteside, Dr. Richard (2003) — Internet College Recruiting and Marketing: Web Promotion, Techniques and Law

^[ii] Whiteside, Dr. Richard & Mentz, Dr./Jur. George (2003) — Online Admissions and Internet Recruiting: An Anatomy of Search Engine Placement

^[iii] Generative AI Models Are Sucking Up Data from All Over the Internet, Yours Included | Scientific American

^[iv] Why AI Search Will Soon Decide If Customers Ever Find Your Brand

^[v] What is AI Search: How It Works and Why It Matters

^[vi] (32) How To Rank in AI Search Results (GEO & AEO) | LinkedIn

^[vii] Search Engines are Using your Content to Train AI – Here’s How You Can Benefit - MediaOS

^[viii] AI search visibility comes from third-party mentions, not your site.