Compare practical AI use cases for consultants across research, analysis, interviews, presentations, reports, proposals, and client meetings.
Updated July 26, 2026
Consultants lose hours searching for evidence, rebuilding the same analyses, and turning approved thinking into client-ready work. These are the eight AI workflows that give you the most useful time back.
All 8 run on whichever AI agent you already use - Claude, ChatGPT, Gemini, or Microsoft Copilot - connected to the tools listed with each use case.
Best first workflow - turn a defined client question into a sourced decision brief
3.5 hr/wkest. time saved
How it’s done today
You search market databases, company sites, filings, reports, prior work, and interview notes in parallel, then reconcile competing claims and rebuild the useful evidence into a briefing.
How AI helps
Given a precise decision question, your agent builds a research plan, searches the allowed sources, compares conflicting evidence, and delivers a cited brief with implications and unanswered questions.
Question approveddecision and scope are clear
Your AI agent
Searches current and approved internal sources, separates fact from inference, and reconciles evidence against the client question.
Decision brief
Evidence table
Open questions
How to set it up
Required
Research
Reads current public sources, company pages, filings, reports, and search results.
Returns source links and passages that support each material finding.
Recommended
Files
Reads the engagement brief, client material, prior research, and approved internal examples.
Writes the source pack and supporting evidence table to the project folder.
Optional
Docs
Writes the decision brief in your firm’s normal research template.
A paid research database is not required. Start with your agent’s web research and attach the client files you are allowed to use; add specialist databases only when the engagement already relies on them.
Have one real client question, the engagement scope, your trusted and excluded source types, and two research briefs your team considered strong. Then paste this into your agent.
Setup prompt
Help me build a repeatable consulting research workflow.For each approved client question, create a source-linked decision brief.1. Ask what decision this research should inform, who will read it, the geography, time window, definitions, and what is out of scope.2. Ask which internal files and external sources are approved, preferred, or prohibited for this engagement.3. Propose a research plan and the hypotheses or questions the evidence needs to test before you begin collecting sources.4. Record the source, date, claim supported, relevant passage, and limitation for every material finding.5. Keep observed facts, client-provided evidence, calculations, and your own inference visibly separate. Show conflicting estimates side by side.6. Deliver an executive answer, findings by question, implications, evidence table, contradictions, and unanswered questions in our template.7. Ask me to verify the decisive sources and revise the brief from my notes.8. Test the workflow on a market, a company, and a competitor question before we reuse it.
What good looks like
A reviewer can trace every important conclusion to a current source, see when two sources disagree, and understand what the evidence does and does not establish without reopening twenty browser tabs.
Choose your trigger
Start manually from a research request that names the decision, owner, scope, and deadline. For recurring market or competitor briefs, schedule only the source refresh - a vague question should produce a clarification request, not a generic report.
What runs without you
The agent can collect and organize evidence once three briefs in a row have passed source review without missing or invented citations. You still approve the research plan and conclusions. Recheck the source list monthly during an active engagement and whenever the question or geography changes.
Best for turning approved findings into an answer-first, editable deck
3 hr/wkest. time saved
How it’s done today
You consolidate findings, decide the answer and storyline, write action titles, build exhibits, move everything into the firm’s template, and check every number, alignment, font, and page break.
How AI helps
Your agent reads the approved evidence and a reference deck, proposes the storyline, drafts editable slides and exhibits, then renders the result and reports unsupported claims, overflow, and template drift.
Findings approvedreference deck is attached
Your AI agent
Builds the answer-first storyline, creates editable slides, links exhibits to evidence, and visually checks the rendered deck.
Storyline
Editable deck
QA report
How to set it up
Required
Slides
Reads the firm template, reference decks, aspect ratio, layouts, and brand rules.
Writes an editable deck with native text and charts where practical.
Recommended
Files
Reads the approved findings, source exhibits, logos, images, and prior deliverables.
Writes the draft deck, rendered slide images, and QA report to the engagement folder.
Optional
Spreadsheets
Reads the final figures and chart data rather than retyping numbers from screenshots.
Start from a real approved template. A blank “make this look like McKinsey” prompt is much less useful than showing the agent the deck size, layouts, fonts, colors, and two slides your team would happily reuse.
Have one reference deck, the approved evidence pack, two strong example slides, and three representative deliverables ready: a weekly update, an analysis deck, and an executive presentation.
Setup prompt
Help me build a client-presentation drafting workflow.For each approved evidence pack, create an editable first-draft deck.1. Ask who the audience is, what decision the deck should drive, the required length, delivery format, and which reference deck to follow.2. Inspect the source deck before editing it and summarize its aspect ratio, layouts, fonts, colors, spacing, chart style, and action-title pattern.3. Ask me to confirm the governing answer, supporting logic, required exhibits, and any sections or language that must remain unchanged.4. Propose an answer-first storyline and slide list before building the deck.5. Keep text, simple charts, and shapes editable. Link every number and factual claim to the supplied analysis or source note.6. Build the slides in the reference template, then render every slide and fix overflow, overlaps, font substitution, and obvious hierarchy problems.7. Deliver the editable deck plus a QA list of unsupported claims, unresolved decisions, changed slides, and source locations.8. Test it on the weekly update, analysis deck, and executive presentation and compare each with our approved examples.
What good looks like
The storyline answers the client question, every action title states a conclusion, all figures trace to the approved analysis, and the rendered deck matches the reference template without clipped text or broken layouts.
Choose your trigger
Start when the findings are marked approved and the reference deck is attached. Do not build from half-finished analysis; if the answer or source pack is missing, return a gap list instead of filling the deck with generic content.
What runs without you
After three decks in a row pass number, source, and visual QA with only normal edits, let the workflow create a first draft when an evidence pack is approved. You still approve the storyline and every client-facing slide; the workflow never presents or sends the deck.
Best for turning client files into traceable findings and exhibits
2.5 hr/wkest. time saved
How it’s done today
You inspect spreadsheets and exports, decipher field definitions, clean inconsistent rows, rebuild formulas, reconcile totals, test hypotheses, create charts, and write the findings by hand.
How AI helps
Your agent profiles the files before analysis, asks for missing definitions, preserves the source, writes inspectable calculations, reconciles control totals, and produces findings plus editable exhibits.
Question and files readydefinitions and controls attached
Your AI agent
Profiles the data, runs traceable calculations, reconciles the result, and explains which evidence supports each finding.
Analysis workbook
Client exhibits
QA log
How to set it up
Required
Spreadsheets
Reads approved source workbooks, CSV exports, data dictionaries, and control totals.
Writes a separate analysis workbook with formulas, checks, findings, and exhibits.
Writes only a draft view or specification unless your data owner approves direct changes.
Optional
Files
Reads business definitions, prior analyses, and project documentation around the data.
A direct database connection is not necessary for the first version. Use a controlled export and preserve it unchanged; the important setup is a clear question, definitions, and control totals.
Have three representative datasets, the business question for each, definitions for the important fields, and the totals or known cases a reviewer uses to decide whether the analysis is trustworthy.
Setup prompt
Help me build a repeatable client-data analysis workflow.For each approved question and dataset, create a traceable analysis pack.1. Ask what decision the analysis supports, the unit of analysis, time period, filters, metric definitions, and expected control totals.2. Inspect every file before calculating. Report columns, types, row counts, missing values, duplicates, units, date coverage, and join keys.3. Preserve the source files unchanged and create stable row IDs plus a log of every cleaning, exclusion, mapping, and assumption.4. Propose the analysis plan and hypotheses, then ask me to approve it before running the full calculation.5. Use visible formulas or reproducible code, reconcile totals to the source, and investigate every material difference instead of hiding it.6. Produce the answer, supporting tables and charts, sensitivity checks, limitations, and a short explanation of what the data cannot establish.7. Save an editable workbook and a QA sheet with controls, exceptions, and the exact source behind each exhibit.8. Test it on the three datasets and compare the results with known totals and an analysis you already reviewed.
What good looks like
Control totals tie, units and filters are explicit, formulas remain inspectable, every chart can be reproduced, and a reviewer can account for every excluded or transformed row.
Choose your trigger
Start manually when a consultant approves the question and selects the files. For a recurring report, run when a complete dated export arrives - not when one source file changes halfway through the refresh.
What runs without you
After three consecutive runs reproduce the known totals and pass the exception checks, let the workflow refresh the workbook and exhibits on the agreed cadence. You still review definitions, outliers, findings, and recommendations before they reach a client.
Pairs well with draft client presentations - the validated exhibits should flow into the deck without retyping any numbers.
Best for finding evidence and disagreement across stakeholder conversations
2 hr/wkest. time saved
How it’s done today
You reread transcripts, standardize participant labels, code observations, group themes, pull evidence, count how broadly a view appears, and separate real disagreement from different wording.
How AI helps
Your agent converts approved transcripts into a traceable theme matrix, links observations to exact interviews and quotes, preserves outliers, and drafts implications and follow-up questions.
Interview batch completetranscripts are approved
Your AI agent
Codes observations, groups themes, preserves disagreement, and links every finding to the interview evidence behind it.
Theme matrix
Evidence appendix
Implications
How to set it up
Required
Meetings
Reads approved transcripts with speaker labels, timestamps, and meeting metadata.
Returns exact passages for every coded observation and theme.
Recommended
Docs
Reads the interview guide, research questions, taxonomy, and prior synthesis examples.
Writes the theme matrix, evidence appendix, summary, and follow-up questions.
Optional
Files
Reads consented notes, survey exports, org charts, and other engagement evidence.
You can test with transcript files in a folder before connecting a meeting assistant. Use the tool and retention settings approved for the engagement, and remove participant details from the synthesis when names do not matter.
Have three interview batches a consultant has already synthesized, the research questions, the interview guide, and the level of anonymity expected in the final deliverable.
Setup prompt
Help me build a stakeholder-interview synthesis workflow.For each completed interview batch, create a traceable synthesis for review.1. Ask for the research questions, participant groups, interview guide, naming convention, anonymity rules, and the approved output template.2. Inspect the transcripts for missing speakers, poor transcription, duplicate meetings, and incomplete interviews before coding anything.3. Extract observations as discrete statements and attach the interview ID, speaker group, timestamp, and exact supporting passage to each.4. Group observations into themes, but preserve counterexamples, outliers, and differences between participant groups.5. Show how many interviews support each theme without treating frequency as proof of importance or manufacturing consensus.6. Draft implications and follow-up questions separately from the observed evidence, and label every inference clearly.7. Deliver a theme matrix, evidence appendix, executive summary, disagreements, and gaps that require another interview or source.8. Test it on the three reviewed batches and compare its themes and evidence links with your original synthesis.
What good looks like
Every theme links to exact interview evidence, meaningful dissent remains visible, participant groups are not blurred together, and the implications are clearly separated from what people actually said.
Choose your trigger
Run when a named interview batch is complete and its transcripts have passed the basic quality check. Do not re-synthesize the whole project every time one note changes; version each batch and then combine approved batch summaries.
What runs without you
After two batches match your reviewed themes and quotes, let the workflow create a draft synthesis whenever at least three approved interviews enter a batch. You still review the coding, combine themes, and own every implication used with the client.
Pairs well with draft client reports - the evidence appendix gives the report a traceable base instead of unattributed anecdotes.
Best for turning approved analysis into an answer-first memo or report
2 hr/wkest. time saved
How it’s done today
You move approved analysis into a memo or report template, write the answer and rationale, place exhibits, check every claim, and rewrite sections until the document reads as one argument.
How AI helps
Your agent maps approved findings into the client or firm structure, drafts an answer-first narrative, inserts source-linked exhibits, and marks unresolved claims instead of smoothing over them.
Analysis approvedreport template selected
Your AI agent
Turns approved evidence into a coherent recommendation, keeps claims traceable, and exposes the questions a reviewer still needs to resolve.
Executive summary
Full report
Review checklist
How to set it up
Required
Docs
Reads the report template, style guidance, required sections, and approved examples.
Writes the executive summary, full report draft, footnotes, and reviewer notes.
Recommended
Files
Reads the approved evidence pack, analysis, interview synthesis, exhibits, and prior reports.
Writes the draft and evidence checklist into the engagement folder.
Optional
Spreadsheets
Reads final figures and exhibit sources directly rather than relying on copied prose.
The workflow should begin only after the underlying findings are approved. AI can make incomplete thinking sound finished; requiring an evidence pack and an explicit recommendation prevents a polished report from getting ahead of the work.
Have the report template, two approved examples, one complete evidence pack, and three representative report types ready before you configure the workflow.
Setup prompt
Help me build a client-report drafting workflow.For each approved evidence pack, create a reviewable report or memo draft.1. Ask what type of report this is, who will read it, the decision it should support, required sections, length, tone, and delivery format.2. Ask for two approved examples and identify their answer-first structure, evidence style, exhibit conventions, and level of detail.3. Confirm the governing recommendation, supporting findings, approved source pack, required exhibits, and unresolved decisions before drafting.4. Build an outline that states the answer first, then organizes the evidence by the logic needed to support it rather than by the work chronology.5. Draft only from approved material. Link claims and figures to their source and mark [SOURCE NEEDED], [DECISION NEEDED], or [ANALYSIS NEEDED].6. Produce the executive summary, full draft, exhibit references, evidence checklist, limitations, and questions for the reviewer.7. Check that the summary, recommendation, body, figures, and next steps agree with one another before delivery.8. Test it on three different report types and compare the drafts with our approved examples and reviewer comments.
What good looks like
The answer appears immediately, the body actually supports it, every figure matches the underlying analysis, exhibits are placed where the argument needs them, and every unresolved claim is obvious to the reviewer.
Choose your trigger
Start when the workstream owner marks the evidence and recommendation approved and selects the report template. If the evidence checklist is incomplete, create an outline and gap list rather than a full draft.
What runs without you
After three reports need only normal editorial changes and no source or number corrections, let the workflow create a first draft when an evidence pack is approved. You remain the author: the workflow never sends, publishes, or represents the report as final.
Best for tailoring a proven approach to a real client opportunity
2 hr/wkest. time saved
How it’s done today
You interpret discovery notes or an RFP, search old proposals for relevant language and credentials, tailor the scope and workplan, collect case studies and team bios, and check every requirement.
How AI helps
Your agent builds a requirement matrix, retrieves approved examples, drafts each section against the opportunity, and flags missing proof, scope choices, commercial inputs, and approvals.
Proposal requestedbrief or RFP is approved
Your AI agent
Maps every requirement, retrieves approved proof, tailors the approach, and exposes the commercial and delivery decisions still missing.
Proposal draft
Requirement matrix
Approval gaps
How to set it up
Required
Docs
Reads the opportunity brief or RFP, proposal template, instructions, and required response format.
Writes the tailored proposal, requirement matrix, and reviewer questions.
Recommended
Files
Reads approved past proposals, case studies, credentials, team CVs, methodologies, and rate cards.
Returns the exact source behind every reused claim and credential.
Optional
CRM
Reads discovery notes, stakeholders, opportunity stage, known constraints, and prior activity.
Writes a draft proposal link or status update only after review.
The useful connection is the approved proposal library, not every file the firm has ever produced. Curate current credentials, examples, team bios, methods, and commercial guidance so the agent cannot revive stale claims.
Have an opportunity brief, one RFP, two approved or won proposals, the current credential library, and one proposal that failed review so the workflow can learn both the standard and the common mistakes.
Setup prompt
Help me build a consulting proposal and RFP workflow.For each approved opportunity, create a tailored proposal draft for review.1. Ask whether the starting point is a discovery brief or formal RFP, who the buyer is, the decision process, deadline, format, and approval owners.2. Extract every stated requirement, question, attachment, word limit, and due date into a requirement matrix before drafting.3. Ask me to confirm the client situation, desired outcome, scope boundaries, approach, deliverables, timeline, team, assumptions, and pricing owner.4. Search only the approved proposal library for relevant case studies, credentials, methods, bios, and language; cite the source of each reuse.5. Draft the situation, point of view, approach, workplan, deliverables, team, proof, timing, and assumptions against the client's language.6. Never invent experience, people, availability, fees, or commitments. Mark [OWNER INPUT], [COMMERCIAL DECISION], or [APPROVAL NEEDED] instead.7. Deliver the proposal, requirement matrix, source list, compliance check, duplicated language check, and open decisions.8. Test it on a won proposal, an RFP response, and a bespoke discovery-led proposal before connecting it to live opportunities.
What good looks like
Every requirement is answered or visibly open, the proposal sounds written for this client, only approved proof is used, and the scope, workplan, timeline, team, assumptions, and commercials agree throughout.
Choose your trigger
Start when the opportunity owner marks the request approved and supplies either the RFP or a complete discovery brief. Ignore early leads without a defined problem, buyer, and next step; create a discovery-question list instead of a proposal.
What runs without you
After three drafts pass requirement and credential review without material errors, let the workflow create a first draft when an opportunity moves to Proposal requested. A partner or owner still approves scope, team, timing, fees, and submission; the workflow never sends a proposal.
Pairs well with research client questions - a short, sourced client and market brief makes the proposal specific before the delivery approach is written.
Best for turning every client call into a clear record of what happens next
1.5 hr/wkest. time saved
How it’s done today
After each call, you turn notes into a client recap, decision log, action list, internal update, and sometimes a project-plan change - often long after the context was fresh.
How AI helps
When the meeting note is saved, your agent separates decisions from discussion, drafts the client recap, captures stated owners and dates, and prepares internal actions without inventing commitments.
Meeting note savedexternal client call complete
Your AI agent
Extracts what was decided and promised, separates client-safe from internal context, and prepares every downstream draft together.
Client recap
Decision log
Action drafts
How to set it up
Required
Meetings
Reads the approved transcript, speakers, timestamps, title, attendees, and meeting notes.
Returns exact evidence for decisions, commitments, owners, dates, and open questions.
Recommended
Email
Reads the existing thread and approved client communication style.
Writes a reply draft only - never a send.
Optional
Tasks
Reads existing project tasks so the workflow updates rather than duplicates them.
Writes task drafts with stated owners, dates, source meeting, and approval status.
One meeting connection is enough to start. Add Email when the recap quality is stable, then Tasks only if the project team already has clear ownership and due-date conventions.
Have three representative meetings ready - one straightforward update, one decision-heavy workshop, and one call with unclear owners - plus examples of a good client recap and internal action log.
Setup prompt
Help me build a consulting meeting-follow-up workflow.After each eligible client meeting, prepare all follow-up drafts for review.1. Ask which meeting assistant, email, task, and document tools we use and which external meetings should qualify.2. Ask for examples of our client recap, decision log, action format, tone, and the rules for separating client-safe from internal notes.3. Read the transcript and extract only stated decisions, commitments, owners, dates, open questions, risks, and requested materials with timestamps.4. Draft a concise client email with context, decisions, next steps, owners, dates, and open questions. Do not include internal commentary.5. Create a separate internal recap with the decision log, risks, unresolved interpretation, and task drafts linked to the source meeting.6. Never infer an owner, deadline, agreement, or commitment. Mark it as open and quote the relevant passage when the transcript is ambiguous.7. Save every output as a draft and show a short verification checklist for decisions, owners, dates, names, and attachments.8. Test it on the update, workshop, and ambiguous meeting and compare the drafts with follow-ups you already approved.
What good looks like
The recap is short enough to send, decisions and commitments match the transcript, owners and dates are never guessed, internal context stays internal, and the task list does not duplicate work already in the project plan.
Choose your trigger
Run when an eligible external meeting note is saved and the transcript is complete. Exclude internal calls, informal conversations, interviews routed to the synthesis workflow, and meetings shorter than your chosen minimum.
What runs without you
After five follow-ups in a row need no decision, owner, or date correction, let the workflow create the email and task drafts automatically after each eligible meeting. You review and send the email and approve any project-plan changes.
Pairs well with prepare client meetings - the prior follow-up supplies the decisions and actions the next brief should revisit.
Best for walking into each meeting with the latest context and a clear objective
1 hr/wkest. time saved
How it’s done today
You reopen recent emails, meeting notes, project files, action logs, prior decks, and attendee information to remember what changed, what remains open, and what the meeting must accomplish.
How AI helps
Before an eligible meeting, your agent retrieves the latest approved context, summarizes progress and open decisions, proposes an agenda and questions, and prepares likely objections for you to rehearse.
Client meeting upcomingstarts in 90 minutes
Your AI agent
Retrieves the latest project state, identifies the meeting’s decision and open loops, and turns them into a focused brief with the questions to ask.
Meeting brief
Agenda and questions
How to set it up
Required
Calendar
Reads the meeting title, time, organizer, attendees, description, links, and recurrence.
Starts the workflow only for meetings that match your eligibility rules.
Recommended
Files
Reads the latest project plan, prior deck, decision log, follow-up, analysis, and client material.
Writes a dated meeting brief in the engagement folder.
Optional
CRM
Reads account background, stakeholders, open opportunities, and prior commercial activity when relevant.
Calendar plus a well-organized engagement folder is enough. Add Email, meeting history, or CRM only when those systems hold context the project folder does not; more connections do not improve a brief if the scope is unclear.
Have three upcoming meeting types, examples of useful and useless briefs, the eligible-calendar rules, and a clearly named engagement folder for each test case.
Setup prompt
Help me build a client-meeting preparation workflow.Before each eligible meeting, create a focused brief for the consultant.1. Ask which calendar, file, email, meeting, and CRM tools we use and how an eligible client meeting can be identified reliably.2. Ask how far back to look, where each engagement's current files live, which sources are authoritative, and how long the brief should be.3. From the event and approved sources, identify the meeting objective, latest project state, prior decisions, open actions, risks, and required materials.4. Build a brief with attendees and roles, what changed, unresolved decisions, a proposed agenda, questions to ask, and documents to open.5. Suggest likely objections or curveball questions separately and label them as rehearsal prompts, not facts about what an attendee believes.6. Link every project fact to its source and surface conflicts or stale files rather than choosing one silently.7. Keep unrelated sensitive information out of the brief and never contact an attendee or modify the calendar.8. Test it on a weekly status call, a decision meeting, and an executive steering meeting and compare the result with consultant-prepared briefs.
What good looks like
The brief takes less than five minutes to review, reflects the latest project state, states the decision the meeting needs, links material facts, and keeps suggested questions or objections clearly separate from known context.
Choose your trigger
Run 60 to 90 minutes before an eligible external meeting, after the source systems have had time to update. Skip cancelled events, focus blocks, internal calls, and meetings without a mapped engagement folder.
What runs without you
After five briefs in a row use the correct project, latest sources, and meeting objective, let the schedule create them automatically. The agent can prepare and deliver the brief privately; it never edits the calendar, emails attendees, or represents its rehearsal prompts as facts.
Pairs well with draft meeting follow-ups - each recap closes the loop and supplies fresh context for the next meeting.
Start with research client questions if you repeatedly rebuild the same source pack, or meeting follow-ups if every call creates an email and action-list backlog.
During discovery, combine client research, interview synthesis, and client-data analysis. They create the evidence base; hypotheses belong inside those workflows rather than in a separate AI brainstorm.
During delivery, choose presentations for deck-led work and client reports for memo- or report-led work. Both should reuse the same approved evidence instead of drafting from a blank prompt.
For business development, start with proposals when you already have a current library of credentials, examples, methods, and team bios.
If your week is meeting-heavy, use meeting prep before the call and meeting follow-ups after it. One improves the conversation; the other makes sure the commitments survive it.
Two things consultants are being sold are deliberately missing here:One-click client deliverables - tools promising a finished deck or report from a single prompt - are absent by design. AI gives you a strong, editable first draft; the argument, the numbers, the commercial commitments, and everything the client sees stay yours. A deliverable you cannot defend in the room is worse than a slow one.Due diligence and financial modeling carry real AI value but are specialist, high-stakes workflows with their own data-room and validation discipline - not something to run from a general setup guide. If a use case earns its way onto this list, we will add it with the same setup steps.
A general AI agent such as Claude, ChatGPT, Gemini, or Microsoft Copilot can run all eight workflows. Choose based on which one your firm approves and which connections it supports. Specialist tools matter around the agent: research services for evidence, meeting assistants for transcripts, and Office or Google Workspace for the actual deliverables.
Can consultants use client information in ChatGPT, Claude, or Gemini?
Use the workspace and data settings approved by your firm and the client engagement. Check the engagement terms before connecting recordings or confidential files, and keep the source set as narrow as the workflow needs. If a client does not allow a connection, use an approved redacted export rather than a personal account.
Can AI create consulting-quality presentations?
It can create the storyline, action titles, editable first-draft slides, and much of the mechanical formatting. It does not remove the consultant’s review: check the governing answer, every number and source, slide hierarchy, template fidelity, and the rendered deck before it reaches a client.
Do these use cases work for independent consultants and large firms?
Yes. An independent consultant can start with a few approved files and simple connections. A larger firm can connect its proposal library, internal knowledge, meeting system, and templates. The job and output stay the same; the difference is where the context comes from and which approvals are required.
Will AI replace management consultants?
AI is compressing research, synthesis, drafting, and production work. Clients still pay consultants to frame the right problem, judge imperfect evidence, align people, make trade-offs, and stand behind a recommendation. The useful near-term model is AI producing a faster first pass while the consultant owns the decision and the client relationship.