On two business consultant fee questions, and no others in the study, all four tested API configurations were eligible. Hourly median midpoints ran from $75 (Anthropic) to $200 (Google) on “What is the average fee for a business consultant?”, a 2.67× ratio, and from $100 to $225 on “How much does a business consultant usually cost?”, a 2.25× ratio.
Answers from four API configurations of AI assistants, collected on October 8, 2026 (11:49 to 12:06 UTC), with Google AI Overviews pulled the same day. This article reports the business consultant questions from a larger study of 11 executive and consulting cost questions, published as 4 AI Assistants, 11 Executive and Consulting Cost Questions.
The author sells fractional COO, fractional CMO, post-merger advisory, and strategy services. This article links to the author’s strategy service page, which may benefit from search traffic it earns. The author’s own domain appears among the references presented by Google’s AI Overviews for these questions (counts in the references section). This analysis does not test what those services cost or are worth. The question set, the calls, and the analysis rules were fixed before the main data pull. Five post-collection changes are listed under Method: a parser fix, a calibration check coded by the study’s AI producer instead of a person, one preregistered check that was not met as written, a rounding implementation difference that changed no figure, and the title confirmation.
These are AI-generated statements, not market prices. The study does not test whether any answer is accurate.
The two questions
Each question went to four API configurations ten times: OpenAI (openai/gpt-5.6-terra), Google (google/gemini-3.8-flash), Anthropic (anthropic/claude-sonnet-5.5), and Perplexity (perplexity/sonar-pro). A configuration was eligible if at least 8 of its 10 answers led with a closed range in the question’s most common unit, which was hourly for both questions. All four configurations were eligible on both.
Results
AI-generated statements collected through an API on Oct 8, 2026; not market prices.
| ID | Question | OpenAI | Anthropic | Perplexity | Ratio | |
|---|---|---|---|---|---|---|
| Q02 | What is the average fee for a business consultant? | $175 | $200 | $75 | $187.50 | 2.67× |
| Q05 | How much does a business consultant usually cost? | $162.50 | $225 | $100 | $200 | 2.25× |
Figures are hourly medians of the midpoints of each configuration’s eligible lead ranges.
On both questions, Anthropic gave the lowest median and Google the highest. OpenAI and Perplexity sat between them. Perplexity’s Q02 median is computed from its 8 hourly lead ranges. The other 2 of its 10 answers gave a range with no resolved unit.
Asking the same question ten times
Each configuration was asked each question ten times. Some answered with the same range almost every time, and others did not.
AI-generated statements collected through an API on Oct 8, 2026; not market prices.
| Cell | Lowest midpoint | Highest midpoint | Max ÷ min |
|---|---|---|---|
| Anthropic, Q05 | $75 | $187.50 | 2.50 |
| OpenAI, Q02 | $100 | $200 | 2.00 |
| Perplexity, Q02 | $144 | $225 | 1.56 |
| OpenAI, Q05 | $112.50 | $162.50 | 1.44 |
| Anthropic, Q02 | $75 | $100 | 1.33 |
| Perplexity, Q05 | $187.50 | $225 | 1.20 |
| Google, Q02 | $175 | $200 | 1.14 |
| Google, Q05 | $200 | $225 | 1.12 |
Anthropic’s ten answers to Q05 spanned midpoints from $75 to $187.50. Google’s answers stayed within $25 of each other on both questions.
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What Google’s AI Overviews showed
AI Overviews appeared in all six pulls for these two questions. The first range and unit were recorded from each, and no AI Overview text is reproduced.
AI-generated statements collected through an API on Oct 8, 2026; not market prices.
| ID | Unit | AI Overview lead ranges (three pulls) | Eligible medians |
|---|---|---|---|
| Q02 | Hour | $50 to $300+, $100 to $250, and $150 to $350 | $75 to $200 |
| Q05 | Hour | $100 to $350, $100 to $400, and $100 to $350+ | $100 to $225 |
These are descriptive and are not compared statistically.
What a 2.67× gap means in dollars (illustration)
The following arithmetic is an illustration, not a finding. Applied to a hypothetical 40-hour engagement, the lowest and highest Q02 medians imply very different totals:
- At Anthropic’s hourly median of $75, 40 hours comes to $3,000.
- At Google’s hourly median of $200, the same 40 hours comes to $8,000.
A buyer who asked only one configuration would have seen only one of those totals. Neither total is a price that any consultant charges.
How the AI Overview ranges sat against the medians
As a descriptive comparison added after the main results, the closed AI Overview ranges had midpoints of $175 and $250 on Q02, and $225 and $250 on Q05. The other two pulls were open-ended and have no midpoint. Three of those four midpoints were at or above the highest configuration median for the same question. The AI Overview ranges were also wider than the spread of the configuration medians, starting between $50 and $150 and ending between $250 and $400.
References presented
Perplexity and AI Overviews list reference domains. The study counted which domains were listed and did not read or grade the pages.
Perplexity. It listed 15 domains in all 10 runs of Q02 and 17 domains in all 10 runs of Q05, with the set fixed within each question. As a descriptive count added after the main results, ten domains were listed in every run of both questions: agiled.app, alexberman.com, clutch.co, consultingsuccess.com, indeed.com, mailchimp.com, paperbell.com, squareup.com, thumbtack.com, and upwork.com.
AI Overviews. The most frequent reference domains across the six pulls were phoenixmi.org (5 pulls), consultingsuccess.com (4), nrcpas.com (4), thumbtack.com (4), and talkspresso.com (3).
The author’s domain. The domain kamyarshah.com was listed in the first AI Overview pull for each of Q02 and Q05. It was not listed by Perplexity for these two questions. This is the author’s own site, as stated in the disclosure at the top. A reference count shows what was listed, not what the page said or whether the answer relied on it.
What the numbers mean (operating judgment)
An AI answer to a consultant fee question is a starting point for further research, not a market price or a provider quote. In this data, the configuration asked made more than a twofold difference in the median, and some configurations varied widely from one call to the next.
As operating judgment, buyers should define the deliverable, the time frame, and how success will be measured before comparing any fee. For example, a hypothetical $15M manufacturer might compare a fixed-fee diagnostic with an hourly advisory arrangement. Those engagements can produce very different totals even at similar hourly figures.
What this data does not show
- These are not market prices, and they are not what any consultant charges.
- The study does not test accuracy.
- The calls went to API configurations, not consumer chat apps.
- The 440 API answers in the full study came from one window, about 17 minutes on October 8, 2026. The AI Overview pulls were made the same day.
- Only four configurations were tested, all at default settings.
Questions about this analysis can be sent through the contact page.
Method
The answers come from the full study, 4 AI Assistants, 11 Executive and Consulting Cost Questions, where the complete method, audit, and exclusion tables appear.
- Collection. From 11:49 to 12:06 UTC on October 8, 2026, each of 11 People Also Ask cost questions went to four API configurations ten times, producing 440 API answers, with provider-default settings and no researcher-added system message. There were also 33 Google AI Overview pulls, three per question, made the same day.
- Extraction. A rule-based parser took the first price range, its unit, and an open-ended flag from each answer. The parser matched the AI-arbitrated coding on all fields in 100 of 100 randomly sampled answers (95% lower bound 0.963). Two auditor models from families not under test did the coding and a third model arbitrated. This was not an independent human audit.
Descriptive counts. Counts labeled as added after the main results are computed from the public normalized-records CSV. For each Perplexity record, split the reference-domain field into individual domains and remove duplicates within the record. The domains listed in every run of both questions are those present in all 10 Q02 records and all 10 Q05 records. The registered results in this article were first reported in the full study.
Five post-collection changes, each described in full in the study:
- Calibration coder. The 30-answer calibration was coded by the study’s AI producer (Claude, made by Anthropic, whose model is one of the four tested), not a person.
- Parser fix. A parser fix for escaped dollar signs affected 5 of 440 answers and changed no headline figure.
- Kill rule. One preregistered kill rule required auditor agreement (κ) of at least 0.60 on whether an answer contained a price range. The κ statistic could not be computed because both auditors marked every audited answer as containing a range, with raw agreement of 115 of 115. The kill rule therefore was not met as written. After seeing the data, the producer decided that the study would proceed and recorded that decision as a protocol deviation.
- Rounding. A rounding implementation difference changed no figure.
- Title. The study title was shortened to fit the site’s limit.
Data.
Related analyses:
- COO Cost Questions: How 4 AI Assistants Answered
- Which Sites AI Tools List for Executive and Consulting Cost Questions
- The Same AI Price Question, Asked 10 Times
Google did not review or endorse this analysis. OpenAI, Google, Anthropic, and Perplexity did not review or endorse it. Model names are used only to identify the configurations tested.
The author sells fractional COO, fractional CMO, post-merger advisory, and strategy services. This analysis does not test what those services cost or are worth.
