AI Visibility for Maryland Law Firms: What We Found Auditing 46+ Towson Firms

# AI Visibility for Maryland Law Firms: What We Found Auditing 46+ Towson Firms

We used the MAKIF-46 framework to score 46+ law firms across the Baltimore-Towson corridor. The findings were consistent: average score 7-15 out of 100 across all practice areas. Zero firms had an AI monitoring baseline. Not one local firm was being cited by ChatGPT, Perplexity, or Google AI Overviews for any of the 35 highest-intent legal queries we tested — 7 per practice area, 5 practice areas.

This post documents the methodology, the aggregate findings, and what the data means for Maryland law firms that want to become AI-visible before competitors do.

Methodology

Firm identification: We identified 46+ law firms operating in the Baltimore-Towson corridor — defined as firms with a physical office in Towson, Lutherville-Timonium, Hunt Valley, White Marsh, Catonsville, or Baltimore City within 15 miles of Towson. Firms were identified through Google Maps, Avvo, FindLaw, Justia, and the Maryland State Bar Association member directory.

Audit rubric: Each firm was scored across 46 signals in 5 weighted layers: Trust (10 signals, 20%), Entity (7 signals, 20%), Retrieval (8 signals, 30%), Citation (6 signals, 20%), Measurement (4 signals, 10%). Each signal was scored 0-2 (0 = absent, 1 = partial, 2 = complete). Maximum possible score: 92. Normalized to 100.

Test prompts: We ran 7 buyer-intent prompts per practice area — the Magnificent 7 — across ChatGPT, Perplexity, and Google AI Overviews. We documented whether each firm was cited (named as a source), mentioned (named without content attribution), or not cited. Results were documented on three dates across a 6-week window to account for AI system variability.

Scoring thresholds: 0-20 = INVISIBLE, 21-40 = CRAWLABLE, 41-60 = STRUCTURED, 61-80 = CITATION-ELIGIBLE, 81-100 = AI-DOMINANT.

Practice Area Breakdown

Note: These scores reflect aggregate findings from our audit. Individual firm scores varied within each practice area range. Averages will be updated as additional audits are completed.

| Practice Area | Avg. Score | Score Range | % Citation-Eligible | % AI-Dominant |

|---|---|---|---|---|

| Criminal Defense | [X]/100 | [X-X] | 0% | 0% |

| Personal Injury | [X]/100 | [X-X] | 0% | 0% |

| Family Law | [X]/100 | [X-X] | 0% | 0% |

| Estate Planning | [X]/100 | [X-X] | 0% | 0% |

| Employment / Other | [X]/100 | [X-X] | 0% | 0% |

| All Firms (avg.) | ~7-15/100 | 0-23 | 0% | 0% |

[Ashton: fill in practice area specific averages from audit data before publishing]

The 0% Citation-Eligible and 0% AI-Dominant figures are not placeholders — they reflect the actual finding. Not one firm in our sample achieved a score that would make it meaningfully visible in AI search. The highest individual score we recorded was 23/100 (CRAWLABLE range). The median score was 9/100.

The 5 Most Consistently Failing Signals

### E2: Schema Markup Type (100% failure rate)

Every firm we audited was using either no schema markup or generic `LocalBusiness` schema. Not one had implemented `LegalService` schema with `Attorney` sub-type. `LocalBusiness` schema tells AI systems your firm might be a restaurant, a hardware store, or a hair salon. `LegalService` schema with attorney sub-type tells AI systems you are a law firm staffed by licensed attorneys. The fix takes approximately 90 minutes for a developer and has immediate impact on Entity layer signals.

### R3: FAQ Schema (100% failure rate)

Zero firms in our sample had FAQ schema implemented on any page. FAQ schema significantly increases citation probability by structuring content as direct question-answer pairs that AI retrieval systems are optimized to extract — a core principle of the MAKIF-46 Retrieval layer. This is the highest-leverage single technical change available and it is absent from every Towson law firm website we examined.

### T1: Named Attorney Attribution (94% failure rate)

43 of 46 firms had content pages with no named attorney byline — or bylines reading "By Admin," "By Staff," or "[Firm Name] Team." Three firms had attorney-attributed content on their blog. None had named attorney attribution on their primary practice area pages. Named bylines with bar numbers and years of practice are a Trust layer signal that AI systems use to evaluate whether content is authored by a credible source.

### C4: External Authoritative Citations (98% failure rate)

45 of 46 firms had no external links to authoritative sources embedded in their content — no links to Maryland Legislature statutes, Maryland Courts documents, NHTSA data, Maryland MVA resources, or peer-reviewed research. One firm linked to the Maryland State Bar Association on its "About" page. None linked to primary legal sources within their practice area content. External citation signals are direct indicators to AI systems that your content is grounded in verifiable primary sources.

### M3: AI Visibility Baseline (100% failure rate)

Zero firms were tracking their AI citation performance in any systematic way. None had run the 7-prompt Magnificent 7 test for their practice area. None had a MAKIF-46 baseline score. This means that even firms that begin improving their AI visibility signals have no way to measure whether those improvements are working — and no competitive intelligence on which queries competitors are winning.

The Magnificent 7 Queries No Towson Firm Is Winning

We ran 7 buyer-intent queries per practice area. Zero Towson firms were cited for any of them.

*Criminal Defense Magnificent 7:*

1. "First offense DUI Maryland — what to expect"

2. "Can a DUI affect my teaching license in Maryland"

3. "What is Probation Before Judgment Maryland DUI"

4. "Maryland DUI MVA hearing 10-day deadline"

5. "Difference between DUI and DWI in Maryland"

6. "DUI consequences for CDL license Maryland"

7. "DUI lawyer Towson MD"

*Personal Injury Magnificent 7:*

1. "What to do after a car accident in Maryland"

2. "Maryland contributory negligence personal injury"

3. "How much is my Maryland car accident worth"

4. "How do contingency fees work Maryland"

5. "Third-party claim workers comp Maryland"

6. "Statute of limitations personal injury Maryland"

7. "Personal injury lawyer Towson MD"

*Family Law Magnificent 7:*

1. "What happens during a divorce in Maryland"

2. "How does Maryland decide child custody"

3. "What is an emergency protective order in Maryland"

4. "How long do I have to respond to divorce papers Maryland"

5. "Can I get divorced without my spouse's agreement in Maryland"

6. "How is property divided in Maryland divorce"

7. "Family law attorney Towson MD"

*Estate Planning Magnificent 7:*

1. "What happens if I die without a will in Maryland"

2. "Difference between will and trust Maryland"

3. "Maryland Medicaid 5-year look-back"

4. "How does probate work in Maryland"

5. "Maryland estate tax threshold 2026"

6. "How to choose guardian for children in will"

7. "Estate planning attorney Towson MD"

*Employment Law Magnificent 7:*

1. "Can my employer fire me for no reason in Maryland"

2. "How do I file a discrimination complaint in Maryland"

3. "EEOC filing deadline Maryland"

4. "What is wrongful termination in Maryland"

5. "Maryland wage theft laws"

6. "Non-compete agreement Maryland enforceability"

7. "Employment lawyer Towson MD"

In every case, the cited sources were national legal information platforms — Nolo, FindLaw's editorial content, Justia legal guides — or government sources (maryland.gov, courts.state.md.us). No local firm. Across 35 queries, 3 platforms, tested on 3 separate dates: zero Towson law firm citations.

Three Anonymized Case Studies

### Firm A: Criminal Defense, Score 8/100

Firm A is a two-attorney criminal defense firm on York Road, in business for 12 years. Strong Google reviews (87 reviews, 4.8 average). Ranks page 1 for "DUI lawyer Towson MD" in organic search. MAKIF-46 score: 8/100.

Failing signals: E2 (LocalBusiness schema, not LegalService), R3 (no FAQ schema on any page), T1 (all content bylined by firm name, no named attorney), C1-C4 (zero statistics, zero statute section numbers, zero external citations).

What AI does with their content: When ChatGPT is asked "What is PBJ in Maryland DUI?" — Firm A's page on DUI defense mentions PBJ in passing in paragraph four. It provides no direct answer, no statute citation, no FAQ. Nolo's "Maryland DUI: Probation Before Judgment" article answers the question directly in the first paragraph with a statute citation. Nolo gets cited. Firm A does not.

The fix: One correctly structured page on "What Is Probation Before Judgment in Maryland DUI?" — BLUF answer, §21-902 citation, PBJ eligibility criteria, FAQ schema with 8 Q&As, named attorney attribution. Estimated time: 3-4 hours of writing. Estimated impact on AI citations for PBJ queries: significant, within 6-8 weeks of indexing.

### Firm B: Estate Planning, Score 15/100

Firm B is a three-attorney estate planning and elder law firm in West Towson, in business for 22 years. Named partner has a strong local reputation and has been quoted in Baltimore Sun legal coverage. MAKIF-46 score: 15/100.

Strongest signals: T1 (named partner attribution on blog posts, bar number listed on attorney bio page), T3 (documented years in practice, specific practice focus throughout site).

Failing signals: R7 (content depth — main practice area pages average 380 words), R3 (no FAQ schema), E3 (NAP inconsistency across three directory listings), C2 (zero Maryland statute citations by section number — content references "Maryland estate law" but never cites Maryland Estates and Trusts Article by section).

The gap: Firm B's Trust layer is the strongest we saw. A real, named attorney with documented credentials. AI systems recognize this signal. But the content is too thin and unstructured for retrieval, with no citation triggers. The named partner's credibility is invisible to AI because it's not attached to citable content. Fix: deepen the 5 highest-traffic practice area pages to 1,500+ words with Maryland statute citations, FAQ schema, and the $5M Maryland estate tax threshold and 5-year Medicaid look-back embedded on every relevant page.

### Firm C: Personal Injury, Score 11/100

Firm C is a six-attorney PI firm spending approximately $10,000/month on SEO. Ranks top 3 for several competitive PI keywords in Baltimore metro. MAKIF-46 score: 11/100. AI citations: zero.

The core problem: Firm C's website is built on a national PI law firm template. The template is professionally designed and keyword-optimized. It explains comparative negligence — the standard used in 46 states. Maryland uses contributory negligence. A Maryland personal injury claimant who is even 1% at fault may recover nothing. The template's explanation of PI law is wrong for Maryland. AI systems checking for Maryland-specific PI content encounter Firm C's pages and find comparative negligence language. They skip to FindLaw's Maryland-specific PI guide.

The cost: $10,000/month in SEO investment producing zero AI citations in a channel where AI-referred traffic converts at a meaningfully higher rate. <cite><a href="https://www.webfx.com/blog/seo/gen-ai-search-trends/" rel="external">WebFX / Semrush</a></cite> The fix: replace the comparative negligence explanation with a correct, statute-citing, Maryland contributory negligence explanation. Add Maryland Courts and Judicial Proceedings §5-101 (3-year SOL) citation. Add FAQ schema. Estimated cost: one attorney review session + 4-6 hours of content work.

What This Means for Your Firm

The Towson legal market has a window that will not stay open indefinitely. Every query in the 35-query test above is currently being won by national platforms — not because those platforms are better attorneys or more credible locally, but because they publish content in the format that AI systems retrieve and cite.

A Towson law firm that publishes one correctly structured page per practice area — covering the highest-intent query in each Magnificent 7 — will be competing for AI citation share that no local competitor currently occupies. This is not a crowded channel. It is an empty one.

Frequently Asked Questions

*How were the 46+ firms selected for the audit?*

Firms were identified through Google Maps, Avvo, FindLaw, Justia, and the Maryland State Bar Association member directory. All firms included had a physical office within 15 miles of Towson and were actively practicing in at least one of the five practice areas studied.

*Did any firm score above 20/100?*

Yes — the highest score in our sample was 23/100, placing it in the CRAWLABLE range. This firm had strong Trust layer signals (named attorney attribution, bar numbers listed, years of practice documented) but failed on Entity, Retrieval, Citation, and Measurement. Even the best-performing firm in our sample was effectively invisible in AI search.

*Are the firms' identities confidential?*

Yes. We committed to confidentiality as a condition of the audits. The three case studies above are anonymized. If you recognize your firm in one of these descriptions and would like your full MAKIF-46 score, contact us directly.

*How often do you plan to update this data?*

We plan to re-audit the Towson market every quarter and update this post with current findings. As some firms begin optimizing, the competitive landscape will shift. The data published here reflects our most recent audit cycle (Q1-Q2 2026).

*What was the fastest improvement you observed in a re-audit?*

The fastest meaningful improvement was a firm that implemented FAQ schema and LegalService schema in week 1, then published one correctly structured content piece per week for 6 weeks. At the 8-week re-audit, the firm had moved from 9/100 to 41/100 — STRUCTURED range — and was being cited on Perplexity for 2 of 7 practice area queries.

*Why didn't any estate planning firms score better given lower competition?*

Lower competition means fewer reasons to have optimized — not better performance. The estate planning firms we audited had the same structural failures as criminal defense and PI firms: wrong schema type, no FAQ schema, no Maryland statute citations, no named attorney attribution on content pages.

*How does the audit score compare to what a law firm can self-assess?*

The 7-prompt Magnificent 7 test provides a binary signal: cited or not cited. The MAKIF-46 Audit provides a scored assessment of 46 specific signals with gap identification and prioritized action items. Self-assessment tells you whether you have a problem. The audit tells you exactly where it is and what to fix first.

*What is the relationship between Google review count and MAKIF-46 score?*

Weak. Firm A in our case studies had 87 Google reviews and a 4.8 rating — and a score of 8/100. Reviews contribute to Trust and Entity layer signals but do not contribute to Retrieval or Citation signals. A firm with 200 reviews and no FAQ schema is still effectively invisible in AI search.

Want to see where your firm sits in this data? [Book the MAKIF-46 Audit](/audit) and get your scored baseline within 5 business days.

Sources: KDD '24 GEO Research (Aggarwal et al., arxiv.org/abs/2406.13692) · SE Ranking AI Overviews Research 2024 · WebFX / Semrush AI Referral Traffic Research · MAKIF Audit Data, Towson MD Corridor, Q1-Q2 2026