The VP of Strategy role is fundamentally an information processing and synthesis challenge. You're consuming massive volumes of market data, analyst reports, competitive signals, customer insights, and internal performance data — then distilling it into decisions and narratives that move the company.
AI is reshaping how the best strategy leaders work. Not by replacing strategic judgment, but by dramatically compressing the time it takes to go from raw data to insight.
This breakdown covers the specific use cases where AI delivers the most leverage for strategy leaders, with recommended tools for each.
Use Case 1: Competitive Intelligence
The problem: Tracking 8–15 competitors across their product changes, pricing updates, customer reviews, hiring signals, content strategy, and analyst commentary takes a full-time research analyst — or a compromised strategy leader who's spending too much time in the weeds.
AI-powered approach: Continuous monitoring with automated synthesis.
Best tools:
Perplexity AI is the most underrated competitive intelligence tool for strategy teams. Real-time web search with synthesis, cited sources, and the ability to ask nuanced questions like "What has [Competitor] changed about their enterprise pricing in the last 6 months?"
Trackr — Purpose-built for tool and vendor research. Submit any competitor's tool URL and get a structured scorecard: features, pricing, pros/cons, review sentiment, competitor positioning. Useful for product-adjacent competitive research.
Crayon or Klue — Dedicated CI platforms for teams that need systematic tracking at scale. Better for larger orgs with a dedicated CI function.
Workflow: Weekly competitive digest → Perplexity pull on top 5 competitors → synthesize into 1-page brief for executive team. Trackr for deeper product-level analysis before strategic pivots.
Use Case 2: Market Research and Sizing
The problem: Market sizing exercises are expensive (Gartner reports are $5K+) and often outdated before the ink dries. Bottom-up analysis takes weeks of analyst time.
AI-powered approach: Triangulated synthesis from multiple free sources + your internal data.
Best tools:
Claude (Anthropic) — Best for structured analytical tasks: building TAM/SAM/SOM models, structuring assumptions, drafting market sizing frameworks. Works best with clear instructions and document context.
ChatGPT (GPT-4o) with Code Interpreter — Useful for processing raw datasets, running calculations, and building quick models from imported data.
Perplexity — Real-time research to pull current market data, analyst quotes, and industry reports that feed into sizing exercises.
Workflow: Define segmentation → Perplexity research on each segment → Claude structures the model and identifies assumption gaps → iterate with team.
Use Case 3: Scenario Planning
The problem: Traditional scenario planning produces 3 static documents that are outdated 60 days after writing. Strategy leaders need living frameworks that update as the market shifts.
AI-powered approach: AI-assisted scenario building with structured assumption management.
Best tools:
Claude — Exceptional for structured scenario analysis. Use it to build out the implications of each assumption, identify second-order effects, and write scenario narratives that are internally consistent.
Notion AI — For teams using Notion as their strategy knowledge base, Notion AI can summarize previous scenario work, identify contradictions in your existing planning docs, and draft updates.
ChatGPT — Good for "what if" modeling and stress-testing assumptions by asking it to argue against your scenarios.
Workflow: Build master scenario template → Claude generates 3 scenarios from assumption set → weekly update prompts surface new signals that shift probabilities.
Use Case 4: Board Communication and Reporting
The problem: Board prep consumes enormous strategy leader bandwidth — often 15–20 hours per quarter just on materials creation. The content exists; the synthesis and presentation work is the bottleneck.
AI-powered approach: AI-assisted narrative synthesis and deck drafting.
Best tools:
Claude — Best for long-form narrative synthesis. Feed it your data and it can draft board memo sections, executive summaries, and strategic option framing documents.
Gamma — AI-powered presentation builder that converts outlines/notes into structured slide decks. Significantly faster than building in PowerPoint for first drafts.
Notion AI — If your strategy work lives in Notion, AI can surface cross-document insights and summarize quarterly work for board review.
Workflow: Compile data and key decisions → Claude drafts the narrative → Gamma converts to slide format → human refinement of visuals and messaging.
Use Case 5: Due Diligence and M&A Research
The problem: Preliminary M&A research — market position, competitive differentiation, customer sentiment, management team quality signals — is time-intensive and often delegated to analysts who lack the strategic context.
AI-powered approach: Rapid surface-level research to qualify or disqualify targets before engaging bankers.
Best tools:
Trackr — If the target is a software company, Trackr's research pipeline surfaces product quality signals, review sentiment, customer complaints, and competitive positioning in minutes.
Perplexity — Real-time news, analyst commentary, funding history, and market position research.
Claude — For synthesizing research into a 1-page strategic rationale document that can be shared with the executive team.
Workflow: Perplexity initial research → Trackr for product/market analysis → Claude synthesizes into strategic memo → decision on whether to engage further.
Use Case 6: Internal Knowledge Management
The problem: Strategy decisions made 18 months ago are invisible to new team members. Context is locked in Slack threads and email chains. The strategy team repeatedly re-litigates decisions that were already made.
AI-powered approach: Searchable, AI-queryable knowledge base for all strategy work.
Best tools:
Notion AI — If strategy work lives in Notion, AI search surfaces relevant previous analysis, decisions, and context on-demand.
Glean — Enterprise knowledge search with AI. Searches across Notion, Google Drive, Slack, email, Confluence. Better for larger orgs.
ChatGPT with file upload — For teams without a centralized knowledge base, uploading strategy docs and querying them with GPT is a pragmatic short-term solution.
The VP of Strategy AI Stack (Recommended)
| Use Case | Primary Tool | Secondary | |---|---|---| | Competitive intelligence | Perplexity | Trackr | | Market research | Claude | ChatGPT | | Scenario planning | Claude | Notion AI | | Board communication | Claude | Gamma | | Due diligence | Trackr + Perplexity | Claude | | Knowledge management | Notion AI | Glean |
Monthly cost estimate: $60–120 for an individual VP (Claude Pro + Perplexity Pro + Trackr Team). Dramatically less than a single Gartner report.
What Most Strategy Leaders Get Wrong
Over-relying on AI-generated content without verification. AI is excellent at synthesis and structure. It is unreliable for precise market data and recent events. Always verify quantitative claims from AI against cited primary sources.
Not building a research protocol. Ad-hoc AI use creates inconsistent outputs. Build a standard research playbook your team can follow for competitive analysis, scenario planning, and board prep.
Ignoring the evaluation overhead. Adding AI tools to your stack without a systematic evaluation process creates tool sprawl. Run new AI tools through a structured evaluation (features, security, integrations, pricing) before onboarding the strategy team.