Your $300K Strategy Consultant Just Got Replaced by Three Prompts and a Spreadsheet.

Last quarter, a mid market IT consulting firm paid McKinsey $312,000 for a competitive landscape analysis. The engagement lasted nine weeks. The deliverable was a 47 page PDF with three actionable recommendations.

I rebuilt the entire thing in an afternoon. Three prompts. One spreadsheet. Zero billable hours from a 26 year old MBA who Googled half the data anyway.

This is not a hot take. This is math.

And if you run a consulting firm, you need to understand this math before your clients do. Because once they figure out that 80% of what they pay you for is information synthesis (not information creation), the conversation changes fast.

The Consulting Model Is an Arbitrage on Organized Thinking

Here is what a strategy consultant actually does. Strip away the prestige, the frameworks named after the firm, the expensive slides. What remains is a system with three steps:

1. Gather publicly available data (market reports, earnings calls, industry publications, competitor websites)
2. Organize that data into a structure (SWOT, Porter's Five Forces, TAM/SAM/SOM, competitive matrices)
3. Narrate a recommendation based on patterns in that structure

That is the entire system. Every strategy engagement you have ever seen follows this sequence. The data is almost always public. The frameworks are taught in every business school on the planet. The only thing the consultant adds is labor: the hours it takes a human to read, organize, and write.

AI does all three of these steps. Not theoretically. Not "in the future." Right now, today, with the tools you already have access to.

The question is not whether AI can replace the strategy consultant. The question is whether you will be the firm that uses this to your advantage or the firm that gets disrupted by it.

The Math: What You Are Actually Paying For

Let's break down a typical strategy engagement. I have seen dozens of these proposals. The numbers are consistent.

Traditional McKinsey/BCG/Bain Engagement:

• Partner rate: $700/hr (10 hours of "oversight") = $7,000
• Senior Associate: $450/hr (120 hours) = $54,000
• Associates (2): $300/hr each (200 hours each) = $120,000
• Analyst (1): $200/hr (300 hours of actual research) = $60,000
• Overhead, margin, "platform fee": ~$70,000
• Total: $311,000

Now let's look at what those hours actually contain:

• Research and data gathering: ~400 hours (63% of total labor)
• Synthesis and framework application: ~150 hours (24%)
• Writing and slide production: ~60 hours (10%)
• Original strategic thinking: ~20 hours (3%)

Read that last line again. 3% of the labor is original strategic thinking. The rest is reading, organizing, and formatting. That is the work AI was built for.

The AI Assisted Version:

• AI tool subscriptions (Claude, ChatGPT, Perplexity): ~$200/month
• Your time running the prompts and reviewing output: ~20 hours
• Senior strategist reviewing and adding original insight: ~8 hours
• Total cost: under $5,000 (even if you bill your own time at $300/hr)

That is a 98.4% cost reduction for the same deliverable. Not a similar deliverable. The same one. Same frameworks, same data sources, same structure. The only difference is you didn't pay someone to read analyst reports for 400 hours.

The Three Prompt Framework

I use three distinct prompt personas for strategy work. Each one maps to a role in the traditional consulting team. You run them in sequence. The output of one feeds the input of the next.

This is the system. Not a trick. Not a shortcut. A repeatable system that produces consistent output every time you run it.

Prompt 1: The Research Analyst

This prompt replaces the 400 hours of data gathering. It does the work of the junior analyst who reads every earnings call, pulls every market report, and fills the data room.

You are a senior research analyst at a top tier strategy consulting firm.
Your job is to compile a comprehensive competitive landscape briefing.

COMPANY/INDUSTRY: [Insert your client's industry and top 5 competitors]

Produce the following:

1. MARKET OVERVIEW
   - Total addressable market size and growth rate (cite sources)
   - Key market segments and their relative size
   - Regulatory environment and recent policy changes
   - Technology trends affecting the industry in the next 3 years

2. COMPETITOR PROFILES (for each competitor):
   - Revenue (estimated if private), employee count, funding status
   - Core product/service offerings
   - Target customer segments
   - Pricing model and estimated price points
   - Key differentiators and stated value proposition
   - Recent strategic moves (acquisitions, partnerships, product launches)
   - Publicly stated strategy or vision from CEO/leadership quotes

3. COMPETITIVE POSITIONING MAP
   - Create a 2x2 matrix using the two most relevant dimensions
     for this industry (e.g., price vs. specialization, scale vs. customization)
   - Place each competitor on the map with a brief justification

4. DATA GAPS
   - List any claims you are uncertain about
   - Flag areas where public data is insufficient
   - Recommend specific sources that could fill these gaps

Format: Use headers and bullet points. Cite every data point.
Be precise. Do not speculate without flagging it as speculation.

What this gives you: A 15 to 25 page research brief that would take a human analyst 2 to 3 weeks. You get it in about 4 minutes. The data gap section is critical because it tells you exactly where you need to do manual research, instead of wasting time on things AI already knows.

Pro tip: Run this prompt in Perplexity or a web enabled AI model for the most current data. Then take the output and paste it into Claude for deeper analysis. Use each tool for what it does best.

Prompt 2: The Strategy Consultant

This prompt replaces the Senior Associate. It takes the raw research and applies the frameworks. This is the synthesis layer, the part that turns data into structure.

You are a senior strategy consultant at McKinsey.
You have been given the following competitive landscape research.
Your job is to apply rigorous strategic frameworks and extract insights.

[PASTE THE FULL OUTPUT FROM PROMPT 1 HERE]

Produce the following analyses:

1. PORTER'S FIVE FORCES ANALYSIS
   - Rate each force (1 to 5) with detailed justification
   - Identify the single most important force and explain why

2. SWOT ANALYSIS (for the client company)
   - 5 strengths, 5 weaknesses, 5 opportunities, 5 threats
   - Each item must reference specific data from the research brief
   - Rank items within each category by impact (highest first)

3. VALUE CHAIN ANALYSIS
   - Map the industry value chain (minimum 6 stages)
   - Identify where the most margin is captured
   - Identify where disruption is most likely

4. STRATEGIC GROUP ANALYSIS
   - Identify 3 to 4 distinct strategic groups in this market
   - Define the characteristics of each group
   - Identify mobility barriers between groups

5. KEY INSIGHT SYNTHESIS
   - List the top 5 non obvious insights from this analysis
   - Each insight must be something a generalist would miss
   - Support each insight with at least 2 data points from the research

Format: Use the framework name as an H2 header.
Be direct. No filler. Every sentence should contain information.
If you identify a contradiction in the data, flag it explicitly.

What this gives you: A structured strategic analysis that mirrors what a $450/hr consultant delivers after weeks of work. The "Key Insight Synthesis" section at the end is where the real value lives. That is the section you bring to the client meeting.

Why this works: The frameworks themselves are not proprietary. Porter's Five Forces is from 1979. SWOT has been around since the 1960s. What consultants charge for is the labor of applying these frameworks to specific data. AI does that application faster and more consistently than a human who is juggling six other engagements.

Prompt 3: The Strategic Advisor

This is the Partner prompt. It takes the structured analysis and produces the actual strategic recommendations. This is the 3% that matters most.

You are a senior partner at a strategy consulting firm advising the CEO
of [CLIENT COMPANY]. You have 25 years of experience in [INDUSTRY].

You have the following research and analysis:

[PASTE THE FULL OUTPUT FROM PROMPT 1 AND PROMPT 2 HERE]

The CEO has asked you one question:
"What should we do in the next 18 months to increase market share
by at least 3 points while maintaining current margins?"

Produce a strategic recommendation document:

1. EXECUTIVE SUMMARY (250 words max)
   - State the single most important thing the CEO needs to know
   - State the recommended course of action in one sentence

2. THREE STRATEGIC OPTIONS
   For each option:
   - Name it clearly (e.g., "Vertical Integration Play")
   - Describe it in 100 words
   - Required investment (estimate)
   - Expected timeline to results
   - Probability of success (your honest estimate with reasoning)
   - Key risk and mitigation
   - What must be true for this to work (critical assumptions)

3. RECOMMENDED OPTION
   - State which option you recommend and why
   - Provide a 90 day action plan with specific milestones
   - Identify the 3 decisions the CEO must make this month

4. WHAT I WOULD NOT DO
   - List 2 to 3 strategies that might seem obvious but are traps
   - Explain why each one fails in this specific context

5. METRICS THAT MATTER
   - Define 5 KPIs to track progress on the recommended strategy
   - For each KPI: current baseline, 6 month target, 12 month target

Write in direct, confident language.
No hedging. No "it depends."
If you are uncertain about something, say so plainly and explain why.
The CEO does not have time for caveats dressed as wisdom.

What this gives you: A board ready strategic recommendation with options, a clear pick, a 90 day plan, and the metrics to track it. This is the slide that ends the $300K engagement. You just got it for the cost of an API call.

The critical addition: Section 4, "What I Would Not Do," is where AI actually outperforms most junior consultants. Because AI has processed thousands of strategy documents, it can pattern match on failed strategies faster than someone who has only worked on 10 engagements. The negative space (what not to do) is often more valuable than the recommendation itself.

How to Actually Run This System

Knowing the prompts is not enough. Here is the operating system around them.

Step 1: Prepare Your Data Room (30 Minutes)

Before you touch AI, gather the following:

• Your client's last 2 annual reports or investor decks
• The top 5 competitors' websites (About, Pricing, and Product pages)
• 3 recent industry analyst reports (Gartner, Forrester, IBISWorld)
• Any internal data the client has shared (revenue by segment, customer churn, NPS)

Put all of this into a single folder. You will reference it as you review and refine the AI output. The AI gives you the public layer. Your internal data is what makes the analysis specific and defensible.

Step 2: Run the Prompts in Sequence (45 Minutes)

Run Prompt 1. Review the output. Check the "Data Gaps" section. If there are critical gaps, do 15 minutes of manual research to fill them. Then paste the complete research brief into Prompt 2. Review the frameworks. Look for anything that contradicts your industry experience. Then feed everything into Prompt 3.

Total active time: 45 minutes to 2 hours depending on how much you refine.

Step 3: The Human Layer (2 to 4 Hours)

This is where you earn your fee. The AI gives you 97% of the work. Your job is the 3% that requires:

• Relationship context: You know the CEO personally. You know what she will actually execute on versus what sounds good in a slide deck.
• Political awareness: You know the board dynamics, the internal rivalries, the sacred cows nobody will touch.
• Judgment under ambiguity: When the data is inconclusive, your 20 years of pattern recognition fills the gap.

The human layer is not optional. But it is also not 630 hours of labor. It is 8 to 12 hours of focused senior thinking applied to a pre built foundation.

Step 4: Build the Deliverable (2 Hours)

Take the AI output, layer in your human insights, and format it into whatever your client expects. A slide deck. A memo. A one page brief. The formatting takes a fraction of the time because the thinking is already done.

The Spreadsheet: Your Competitive Intelligence Dashboard

The prompts give you point in time analysis. The spreadsheet gives you ongoing intelligence. Here is the structure:

Tab 1: Competitor Tracker

• Columns: Competitor Name | Last Updated | Revenue Est. | Employee Count | Recent Hires (Key Roles) | Product Launches | Pricing Changes | Strategic Moves | Source Links
• Update monthly by running a simplified version of Prompt 1 focused only on changes since the last update

Tab 2: Market Signals

• Columns: Date | Signal | Source | Implications | Action Required (Y/N) | Owner
• Feed this with a weekly AI scan: "What are the 5 most significant developments in [industry] this week that would affect a company competing in [segment]?"

Tab 3: Strategy Scorecard

• Columns: KPI | Baseline | Current | 6mo Target | 12mo Target | Status | Notes
• Pulled directly from Prompt 3's metrics section
• Updated quarterly

This spreadsheet becomes a living document. Every quarter, you re run the full three prompt sequence and update the dashboard. Your client gets continuous strategic intelligence for the cost of a few hours of your time instead of a new $300K engagement every year.

What This Means for Your Consulting Firm

If you run an IT consulting practice, you are sitting at a crossroads. Here are the two paths:

Path A: Ignore this. Keep billing 630 hours for competitive analyses. Hope your clients do not discover they can do it themselves. Watch your margins compress as younger firms undercut you with AI assisted delivery. Lose your best people to firms that give them better tools. This path has a shelf life of about 18 months.

Path B: Absorb this into your model. Use AI to do the 97% that is data gathering and synthesis. Redeploy your consultants' time toward the 3% that actually requires human judgment. Deliver faster. Charge for outcomes instead of hours. Increase your margins because your cost of delivery just dropped by 90%.

Let me put real numbers on Path B:

• Before AI: $300K engagement, $180K in labor costs, $120K gross profit (40% margin)
• After AI: $150K engagement (you pass some savings to the client), $25K in labor costs, $125K gross profit (83% margin)

You make more money per engagement while charging the client less. You deliver in 2 weeks instead of 9. The client is happier. Your team does more interesting work. Everyone wins except the firms still billing by the hour for work a machine does better.

The Objections (And Why They Are Wrong)

"AI hallucinates. The data won't be accurate."

Two things. First, Prompt 1 explicitly asks AI to flag uncertainty and cite sources. You verify the critical data points. That takes 30 minutes, not 400 hours. Second, consultants hallucinate too. I have seen Big Four deliverables with outdated market sizing, miscited reports, and conclusions that contradicted the data in the appendix. The difference is nobody fact checks the $300K PDF because they assume the price guarantees accuracy. It does not.

"Clients are paying for the brand, not the analysis."

This was true in 2020. It is less true every quarter. CFOs are getting smarter about consulting spend. When a CEO can run the same analysis in house and get a similar output, the "McKinsey said so" justification stops working with the board. You are seeing this already in the declining growth rates of the major firms' strategy practices.

"Our clients' problems are too complex for AI."

Your clients' problems are not too complex for AI. Your clients' problems are too complex for a single prompt. That is why this is a three prompt system with a human layer on top. The complexity is handled by the structure, not by any single component. And the human judgment you add at the end is what makes it specific to your client's situation.

"This will commoditize our industry."

No. This will commoditize the labor intensive parts of your industry. The parts that were always commodities disguised as expertise. The actual expertise, the judgment, the relationships, the ability to tell a CEO something they do not want to hear and have them listen, that gets more valuable as the commodity work gets cheaper. AI does not replace the trusted advisor. It replaces the army of analysts behind the trusted advisor.

The Prompt You Should Run Right Now

Do not bookmark this article and forget about it. Open your AI tool of choice and paste this:

I run a [SIZE] consulting firm specializing in [INDUSTRY/SERVICE].
Our average strategy engagement bills at $[AMOUNT] and takes [WEEKS] weeks.

Based on the three prompt framework described below, help me:
1. Estimate how much of our current delivery is data gathering vs. synthesis
   vs. original thinking
2. Calculate the potential cost savings if we automated the first two categories
3. Design a pilot program to test this on one engagement in the next 30 days

Context about our typical engagement:
[Describe your standard deliverable in 3 to 4 sentences]

That will give you your own custom business case for AI adoption. Specific to your firm. Specific to your margins. Specific to your clients.

The Bottom Line

The data your clients need already exists. The frameworks to analyze it have been public for decades. The only thing that was scarce was the human labor to connect the two. That scarcity is gone.

You can mourn that or you can use it.

The consulting firms that thrive in the next five years will not be the ones with the biggest analyst teams. They will be the ones with the best systems for combining AI output with senior human judgment. They will deliver in days instead of months. They will charge for the quality of their thinking, not the quantity of their hours.

Three prompts. One spreadsheet. And the willingness to look at your own business model honestly.

That is the entire system.