Michael Macfarlane Associates provides Reputation Intelligence: live reports that show how a person, family or company is regarded by AI platforms, search engines, the media and social channels, in every language and market that matters.

The data that should sit behind every decision, and the most powerful form of due diligence available today.

Reputation Intelligence

Affinity and sentiment, including that of institutions, are now driven by large language models, artificial intelligence queries and data points spread across democratised media and social media worldwide. Reputation manifests differently across languages, platforms and geographies.

Each report is built live at the moment it is ordered and read by large language models, the artificial intelligence systems behind ChatGPT, Claude, Gemini, Perplexity and Grok. It establishes how a person, family or company is regarded, by whom and where, and how they are likely to be regarded in relation to a specific matter, planned or impending.

It is used by private clients and family offices, law firms, banks and financial institutions, companies and public institutions, and by the strategists and PR and communications professionals who advise them.

Live sources read by large language models into a report and monitoring that support eight kinds of decisionObserved live5 AI platformsanswers and citationsSearch, by marketpage one, questions, demandWeb, news & editorial12 months, month by monthSocial, incl. Chinesepublic conversationOwned channelsactivity and responseRead by LLMsEntity precisionnamesakes excludedSemantic associationwhat the name meansFraming & sentimentper surface, per languageScenario modellingwhat happens nextDeliveredThe report40 to 70 pagesLive monitoringhourly triageDecisions supportedInvestment & acquisitionCounterparty KYCAppointmentsMarket entryListing & capitalPhilanthropyDisputesCommunicationsIllustrative example
From live observation to decision.Every source is observed at the time of order and read by large language models, so the data behind each decision is current on the day it is taken.
5Artificial intelligence platforms observed
12Months of history
40-70Pages of intelligence
24/7Monitoring, checked hourly
01

Who It Serves

Private Clients And Family Offices.

Principals, families and their offices use it to see how they are regarded before a move, an introduction or a generational transition, and to track whether that view is changing.

Law Firms.

Before and during disputes and in reputation-sensitive matters: how a client, counterparty or witness is regarded, what journalists and opposing parties will find, and how a ruling or settlement is likely to be received.

Banks And Financial Institutions.

In onboarding, KYC and enhanced due diligence, and before lending, investing or appointing: a live view of how a client, counterparty or target is regarded, beyond the records held in databases.

Companies And Institutions.

Boards, foundations, universities and public bodies use it before appointments, partnerships, listings, market entry and announcements, and to monitor how the institution is regarded over time.

Strategists And Advisers.

Strategy, transaction, investor relations and political advisers use it to map outcomes against reputation and to test how a plan is likely to land before it is deployed.

PR And Communications Professionals.

Campaigns are set on measured data, with the sources artificial intelligence repeats identified and progress shown market by market and language by language.

02

Decision Outcomes

Reputation data should sit behind every decision.

KYC And Due Diligence.

Applied to counterparties, investments, appointments and partners, and to clients themselves. It establishes how a person or institution is regarded, not only what is on file.

Strategy Development.

Outcomes are mapped against reputation. Strategy is set on data, with reputational risks identified and their likely course across each surface established in advance.

Communications, PR And Media.

Communications, PR and media strategies are deployed against measured data and specific outcomes in any part of the world, then tracked to show what is working, where and with whom.

Standing Intelligence.

Any family, ultra high net worth individual or company engaged in transformative or building activity, or exposed to reputational risk, should have current reputation data behind every decision, refreshed by regular Reputation Intelligence.

Matrix showing which report insights inform eight kinds of decisionAI perceptionSearch by marketSentiment by languagePerception mapScenario modelRisk watchMonitoringInvestment & acquisitionCounterparty KYCAppointments & hiringMarket entryListing & capital raisePhilanthropyDisputes & litigationCommunications strategyPrimary inputSupporting inputIllustrative example
Which insight informs which decision.Eight kinds of decision and the reputation data that should sit behind each one.
03

Live, Not Archived

Beyond Traditional Databases.

Traditional databases hold stored data points, scraped from the internet at a set point in time and refreshed on someone else’s schedule. They record what is on file, not how a subject is regarded.

Observed Live, Read By LLMs.

Reputation Intelligence is observed at the moment of order and read by large language models, the same systems that now shape how the world forms its view.

A stored database record last refreshed years before a decision compared with Reputation Intelligence observed live up to decision day20222023202420252026Database recordstored data pointslast refreshed2½ years unseenReputationIntelligenceobserved live12 months, month by monthDecision dayIllustrative example
What each sees on decision day.A database record last refreshed years earlier against twelve months of live observation up to the day a decision is taken.
QuestionTraditional due-diligence databasesReputation Intelligence
How current is itAs at the last scrapeAs at the day of order
How artificial intelligence platforms describe the subjectNot coveredChatGPT, Claude, Gemini, Perplexity and Grok, every answer and citation
How the subject reads by language and marketLimitedMarket by market, in English and Chinese
How sentiment will move under a strategyNot coveredModelled scenarios, by segment
How a planned matter will be receivedNot coveredMapped surface by surface in advance
How the material is readKeyword matchesSemantic association, framing and sentiment read by LLMs
04

The Report

An Intelligence Briefing.

Each report is prepared for the principal and nominated advisers and delivered as an editable presentation. It opens with how artificial intelligence defines the subject and closes with the moves that change the answer.

Ordered On Demand.

Twelve months across every surface, market and language, with six- and twelve-month comparisons, in English and Chinese. Repeated monthly or quarterly as a standing input to decisions.

40 to 70pages
5Artificial intelligence platforms, 200 answers
12months, month by month
2languages
6 & 12month comparisons

Sample pages for a fictional principal. All figures on this page are illustrative.

05

Artificial Intelligence Perception Outcomes

Reputation According To Artificial Intelligence.

How ChatGPT, Claude, Gemini, Perplexity and Grok define the subject, measured as a primary reputation and weighted secondary attributes, compared with six and twelve months earlier.

The Sources Behind The Answers.

The publications, profiles and pages behind each association, including owned domains, so corrective work targets the sources that move the answer.

Illustrative reputation summary: primary reputation 46 percent and four weighted secondary attributes with direction of changePrimary reputation according to AI46%Hong Kong property andinvestment principalShare of weighted associations,200 observed answers, five platformsSecondary attributesPatron of contemporary art▲ since 6 months21%Education philanthropynew14%Family business successionstable11%Historic litigation▼ from 23%8%Illustrative example
Reputation according to artificial intelligence.The description artificial intelligence platforms most often give of the principal (the person the report is about), and the other attributes they attach, by share of 200 answers.
Illustrative comparison of five AI platforms: how often the principal is named, leading frame, accuracy and sentimentPlatformNamed in answersLeading frameAccurateSentimentChatGPTInvestor-firstYesClaudeInvestor-firstError foundGeminiHeir-firstError foundPerplexityLitigation-ledYesGrokInvestor-firstYesPos.Neu.Neg.Illustrative example
Five platforms, five answers.How often each platform names the principal, how it frames them, whether it is accurate, and how positive it is.
Illustrative flow of citations from five source types into five AI platformsBusiness pressOwned websitesReference & profilesHistoric litigation reportsSocial & videoChatGPTClaudeGeminiPerplexityGrokCitations by source type · historic litigation drives a quarter of Perplexity’s citationsIllustrative example
The sources behind the answers.The types of source each artificial intelligence platform cites when it describes the principal.
06

Market And Language Outcomes

One Reputation, Many Readings.

A principal can read one way in London and another in Hong Kong, one way in English and another in Chinese. Each market is measured separately.

Page One, Market By Market.

Every page-one result is graded positive, neutral, negative or owned, in each market that matters, and tracked over time.

Hexagon tile map of net sentiment in 25 markets from New York to MelbourneLondon+34Paris+20Zurich+16Beijing+6Seoul+12Tokyo+15New York+24Lisbon+22Geneva+18Monaco+26Shanghai+10Taipei+6Riyadh+9Dubai+12Delhi+5Shenzhen+8Hong Kong+29Macau+14Mumbai+8Bangkok+2K. Lumpur+4Singapore-14Jakarta+1Sydney+3Melbourne+5Net sentiment by market-100+10+20+30Illustrative example
Net sentiment, market by market.Twenty-five markets. Darker gold is more positive; rose is negative.
Illustrative matrix: sentiment and volume for one principal across six market and language pairs and four surfacesAI answersSearchEditorialSocialLondon · EnglishHong Kong · ChineseHong Kong · EnglishSingapore · EnglishShanghai · ChineseMumbai · EnglishPositiveNeutralNegativeDot size = volumeIllustrative example
Six market and language pairs.Sentiment on each channel in six market and language combinations. Larger dots mean more coverage.
Illustrative grid of the first ten search results for the principal’s name in four markets12345678910Positive or ownedLondon5 / 10Hong Kong6 / 10Singapore3 / 10Shanghai3 / 10PositiveNeutralNegativeOwnedIllustrative example
Page one, market by market.The first ten Google results for the principal’s name in four markets, graded positive, neutral, negative or owned (the principal’s own websites and profiles).
07

Narrative And Perception Outcomes

What A Name Is Known For.

The associations, people and companies linked to a name, how each is felt, when each emerged or declined, and which shifts are lasting.

Sentiment By Surface.

Artificial intelligence, search, social and editorial sentiment are measured separately, never blended into a single score, and reported with their drivers.

Perception map plotting each association by share of coverage and net sentiment, with bubble size for volume-1000+1000%20%40%Share of associations →Net sentimentAmplifyProtectDisplaceReframeProperty recordFamily groupArt patronageEducation givingHistoric litigationLifestyle & wealthSuccessionIllustrative example
Perception map.Each theme linked to the name, placed by how much it is discussed (left to right) and how positively (bottom to top).
Streamgraph of five narrative themes across twelve months, with two dated inflection pointsOctNovDecJanFebMarAprMayJunJulAugSepProperty & investmentArt patronageEducation foundationFamily & successionHistoric litigationExhibition partnershipFoundation launchIllustrative example
Narrative themes over twelve months.Share of coverage by theme, with dated inflection points.
Waterfall chart of what moved net sentiment from +8 to +21 over twelve months0+10+20+8Oct2025+7Exhibitionpartnerships+6Foundationlaunch+4Tier-oneinterviews-3Resalecommentary-2Litigationresurfaced+1Ownedchannels+21Sep2026Illustrative example
What moved net sentiment.How each development raised or lowered net sentiment between October 2025 and September 2026.
Network of people, companies and institutions linked to the principal, sized by co-mentionsFamily groupProperty fundContemporary art museumFoundationAuction houseHotel brandFormer partnerUniversityBiennaleSovereign fundTier-one dailyPhilanthropy forumPrincipalBusinessArts & givingNeutral linkRisk linkLine weight = co-mentionsIllustrative example
Who the name travels with.The people, companies and institutions most often mentioned alongside the principal. Thicker lines mean more joint mentions.
Illustrative slope chart of five reputation associations twelve months ago and now12 months agoNowProperty & investment 52%46% Property & investmentHistoric litigation 23%8% Historic litigationPatron of contemporary art 12%21% Patron of contemporary artFamily business succession 13%11% Family business successionEducation philanthropy none14% Education philanthropyIllustrative example
Associations, then and now.Share of weighted artificial intelligence associations twelve months ago and today.
08

Strategy And Scenario Outcomes

Net Sentiment If A Strategy Is Deployed.

Strategies are modelled before they are deployed, by segment and market, so the expected movement in sentiment is known in advance.

Planned And Impending Matters.

For a listing, transaction, appointment, market entry, dispute or announcement, the likely response is mapped surface by surface, with the exposure identified.

Fan chart of net sentiment observed for twelve months and modelled for twelve more under three strategies0+20+40Today+18 No action+31 Conservative+42 RecommendedOct 2025Sep 2026Sep 2027Net sentiment, observed and modelledIllustrative example
Net sentiment under three strategies.Twelve months observed, twelve months modelled.
Four-quarter roadmap from the current perception to the intended positionTodayInvestor first46% of AI associationsQuarter 1Correct the recordAI citations replacedQuarter 2Lead with patronageTier-one interviewsQuarter 3Carry it eastChinese-language presenceQuarter 4Patron and investorPatronage leads on all fiveNet sentiment today +21+42 modelled at quarter 4Illustrative example
From today to the intended position.Four quarters, each with a defined outcome.
Radar chart comparing six perceived attributes today with the intended positionInvestorArt patronPhilanthropistInnovatorGlobal citizenFamily stewardPerceived todayIntended positionIllustrative example
The gap to close.How the principal is seen today against how they intend to be seen.
Venn diagram of the associations AI answers, search and editorial share and those unique to eachAI answersSearchEditorialHeir to the group2014 court reportResale pricesAddress & holdingsFoundation launchExhibition reviewsHotel portfolioLitigationGallery openingsPropertyrecordIllustrative example
The common ground.What artificial intelligence answers, search results and press coverage say in common.
Illustrative matter map: reputational exposure by surface and market for a planned listing, today and after the recommended strategyPlanned matter: London listingLowModerateHighAI answers · UKSearch · UKEditorial · UK national pressSearch · SingaporeSocial · Hong Kong (Chinese)AI answers · Chinese-languageExposure if the matter proceeded todayExposure after the recommended strategyIllustrative example
Mapping a planned matter.For a planned London listing: reputational exposure on each channel and market if it proceeded today (rose) and after the recommended strategy (gold).
09

Reputation Monitoring

Reputation Inside artificial intelligence.

A growing share of first impressions now come from artificial intelligence platforms. Reputation Monitoring follows what ChatGPT, Gemini, Claude, Perplexity, Grok and the leading regional platforms say about the principal, in each language and market, and records every source each answer cites.

Content Change To Answer Change.

When a new article, post, filing, forum thread, video or encyclopaedia edit begins to be cited, it is flagged before the answer settles. Each shift in what artificial intelligence says is traced to the content that caused it, so the response targets the source rather than the symptom.

Every Platform And Language.

News, every social platform, forums, video, podcasts, filings and registries are covered together, in every language that matters to the principal, including Chinese platforms such as RedNote, Weibo, WeChat and Douyin that Western tools cover thinly or not at all.

Trends, Sentiment And Risk.

Monitoring follows long-term change in sentiment, narrative and audience, not only the volume of mentions, measured against a twelve month baseline so that drift is seen early and spikes are read in context.

Escalation Within The Hour.

New items are checked hourly and graded by urgency as RED, AMBER or GREEN. RED and AMBER items reach nominated advisers immediately; routine items go into a weekly digest, with a monthly report.

Advisers Who Act.

Alerts reach experienced counsel and the in-house Content Studio, not a dashboard. Corrections, new authoritative content, removal requests and legal coordination follow, and their effect on artificial intelligence answers and citations is measured.

Five-step flow from a change in online content to a shift in AI citations, a change in AI answers, a graded alert and action by advisers01Content changesNew article, post,filing, edit or video,in any language›02Citation set shiftsAI platforms begin tocite it in answers›03Answer changesWhat AI says about theprincipal moves›04Risk gradedRED, AMBER or GREENwithin the hour›05Advisers actCorrection, content,removal or legalIllustrative example
From a content change to action.How a new source moves into artificial intelligence answers, and where Reputation Monitoring intervenes.
Line chart over sixteen weeks: the share of AI answers citing a hostile article rises after publication, an alert is raised when it is first cited, and the share falls after response content is published while citations of the principal’s own sources rise0%20%40%60%Week 1Week 4Week 8Week 12Week 16Article publishedFirst cited · AMBER alertResponse content live46%61%10%Answers citing the hostile articleAnswers citing the principal’s own sourcesIllustrative example
Citations in artificial intelligence answers.The share of artificial intelligence answers about the principal citing a hostile article, against the share citing the principal’s own sources, across five artificial intelligence platforms over sixteen weeks.

Keyword alerts report that something was published. Social listening dashboards measure volume and sentiment for brands. Reputation Monitoring is built for principals and families: it shows what is changing, why, what artificial intelligence now says as a result, and what to do about it.

QuestionKeyword alertsSocial listening dashboardsReputation Monitoring
What is coveredWeb pages and news indexed by one search engineNews and selected social platforms, set up by keywordNews, every social platform, forums, video, podcasts, filings, registries and artificial intelligence answers
Languages and marketsMainly the language of the searchMany languages, depending on the planEvery language and market that matters to the principal, including Chinese platforms such as RedNote, Weibo, WeChat and Douyin
SpeedDaily or weekly digestNear real timeChecked hourly
Sentiment and narrativeNot coveredAutomated sentiment scoresSentiment, framing and narrative drift read by LLMs, against a twelve month baseline
Artificial intelligence answersNot coveredBrand visibility and share of voice, in some productsWhat ChatGPT, Gemini, Claude, Perplexity, Grok and regional artificial intelligence platforms say about the principal, prompt by prompt and market by market
Artificial intelligence citationsNot coveredRarely traced to the content that caused a changeEvery source cited, the date it entered the citation set, and the content change behind each shift in an answer
Risk gradingNot coveredVolume spikesRED, AMBER or GREEN, graded by experienced advisers
Who it is built forAnyoneBrands and marketing teamsPrincipals, families and family offices
What happens nextAn emailA dashboard to interpretAdvisers act: correction, Content Studio production, removal, legal coordination
Calendar heatmap of daily coverage volume over 52 weeks, marking a spike and a RED alert dayMTWTFSSOctNovDecJanFebMarAprMayJunJulAugSep▲ Exhibition coverage▲ RED alert, verified within the hourLessMoreIllustrative example
Every day of the year.Daily volume of coverage over 52 weeks. Darker squares mean more coverage; the rose square marks a day an urgent alert was raised.
Illustrative long-term monitoring: net sentiment over 24 months and the changing share of conversation by audienceNet sentiment, 24 months-100+10+20+21Oct 2024Sep 2026Who is talking, share of conversation20252026Investors & financerising22%31%Arts & culturerising9%24%General publicfalling41%30%Media & commentatorsfalling28%15%Illustrative example
Long-term sentiment and audience.Net sentiment over 24 months and the changing share of conversation by audience.
Illustrative content attack tracker: 36 hostile items logged, 31 removed over ten weeks, none on page one36Hostile items logged31Removed5Still online0On Google page oneWeek 1Week 2Week 3Week 4Week 5Week 6Week 7Week 8Week 9Week 10Still onlineRemovedIllustrative example
Coordinated content attacks.A coordinated campaign of hostile articles, with every item logged and tracked week by week until removed.
10

Engagement

Reputation Intelligence Report.

Twelve months across every surface, market and language, built live at the moment of order. Repeated monthly or quarterly as a standing input to decisions.

Reputation Monitoring.

Artificial intelligence answers and their citations, every platform and language, long-term sentiment and narrative, hourly triage, immediate RED and AMBER alerts, a weekly digest and a monthly report.

Matter And Proposition Report.

Focused on a specific transaction, listing, appointment, market entry, dispute or announcement, planned or impending, with outcomes mapped and scenarios modelled.

Reputation Intelligence is data to decide on. Every figure in a report comes from an observed source and carries its period. Nothing is estimated or invented. Artificial intelligence findings describe observed answers to a consistent set of questions and never claim visibility of private artificial intelligence conversations.

Facts, derived measures and interpretation are labelled separately, and unverified allegations are attributed, never asserted. Reports are strictly private and confidential, prepared for the principal and nominated advisers, and coordinated with Pre-Legal Counsel where a matter has legal dimensions.