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AI ML

🎯 AI Strategy

AI strategy grounded in what actually works in production

⏱️ 3+ Years
📦 10+ Projects
✓ Limited availability
Experience at: Anaqua• Flowrite• Sparrow Intelligence

🎯 What I Offer

AI Opportunity Assessment

Identify where AI can create real value in your business.

Deliverables
  • Process analysis and AI fit
  • Use case prioritization
  • ROI estimation
  • Risk assessment
  • Quick wins identification

AI Roadmap Development

Create actionable plan for AI implementation.

Deliverables
  • Technology stack recommendations
  • Build vs buy analysis
  • Phased implementation plan
  • Resource requirements
  • Success metrics definition

AI Implementation Support

Guide and support your team through AI implementation.

Deliverables
  • Architecture design
  • Vendor evaluation
  • Team training
  • Progress reviews
  • Course correction

🔧 Technical Deep Dive

AI Strategy That Works

Most AI strategies fail because they:

  • Start with technology instead of business problems
  • Underestimate data requirements
  • Expect magic from off-the-shelf solutions
  • Ignore change management

My approach is different:

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1. UNDERSTAND: What problems are worth solving?
   - Process analysis
   - Pain point identification
   - Value quantification

2. ASSESS: Where can AI actually help?
   - Data availability check
   - Technical feasibility
   - ROI calculation

3. PRIORITIZE: What should we do first?
   - Quick wins vs strategic bets
   - Dependencies
   - Resource constraints

4. PLAN: How do we get there?
   - Technology selection
   - Team requirements
   - Phased implementation

5. EXECUTE: Make it happen
   - Implementation support
   - Progress tracking
   - Course correction

AI Use Case Framework

Not all AI projects are equal. My prioritization framework:

High Value, Low Risk (Do First):

  • Internal productivity tools
  • Document processing
  • Search enhancement
  • Data extraction

High Value, Higher Risk (Plan Carefully):

  • Customer-facing AI
  • Decision automation
  • Content generation
  • Complex agents

Validation Questions:

  • Do we have the data?
  • Is the problem well-defined?
  • What’s the cost of errors?
  • Can we measure success?

📋 Details & Resources

AI Strategy Framework

Phase 1: Discovery (1-2 weeks)

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Stakeholder Interviews → Process Analysis → Pain Point Mapping
                                    ↓
                         AI Opportunity Identification

Phase 2: Assessment (1-2 weeks)

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Data Audit → Technical Feasibility → ROI Estimation
                        ↓
              Use Case Prioritization

Phase 3: Planning (2-3 weeks)

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Technology Selection → Architecture Design → Resource Planning
                              ↓
                    Implementation Roadmap

Phase 4: Execution Support (Ongoing)

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Implementation Review → Progress Tracking → Course Correction
                              ↓
                      Success Measurement

AI Use Case Evaluation

Use CaseData NeedsRisk LevelTypical ROI
Document SearchMediumLowHigh
Data ExtractionLowLowHigh
Content DraftingLowMediumMedium
Chatbot/SupportMediumMediumHigh
Decision SupportHighMediumVery High
Autonomous AgentsHighHighVaries

Questions I Help Answer

Strategic

  • Where should we invest in AI?
  • Build vs buy vs partner?
  • What’s realistic given our data and resources?
  • How do we measure success?

Technical

  • What technology stack should we use?
  • How do we handle data privacy?
  • On-premise vs cloud?
  • How do we ensure reliability?

Organizational

  • What skills do we need?
  • How do we upskill existing team?
  • How do we manage change?
  • How do we govern AI use?

AI Technologies I Advise On

LLMs & Providers: OpenAI, Anthropic, Google, Open Source RAG & Search: Vector databases, embeddings, hybrid search Agents: LangChain, LangGraph, custom orchestration MLOps: Training, fine-tuning, deployment, monitoring Infrastructure: Cloud, on-premise, hybrid options

Frequently Asked Questions

What is AI strategy consulting?

AI strategy consulting helps organizations identify AI opportunities, assess feasibility, plan implementation, and avoid common pitfalls. It bridges the gap between AI hype and practical business value, focusing on achievable goals with measurable ROI.

How much does AI strategy consulting cost?

AI strategy consulting typically costs $150-250 per hour. An AI readiness assessment starts around $10,000-20,000, while thorough strategy development with roadmap and proof-of-concept ranges from $30,000-75,000+.

When should I hire an AI strategy consultant?

Hire when: you’re unsure where AI can help your business, you’ve had failed AI projects, you want to avoid expensive mistakes, or you need to evaluate AI vendors. Good strategy prevents wasted budget on wrong approaches.

What does an AI strategy engagement include?

Typically: business process assessment, AI opportunity identification, feasibility analysis, technology recommendations, build vs buy analysis, vendor evaluation, implementation roadmap, and team capability assessment.

How do you evaluate if an AI project is feasible?

I assess: data availability and quality, problem definition clarity, accuracy requirements, latency needs, cost constraints, and organizational readiness. Many AI projects fail not from technology but from unclear requirements or insufficient data.

Experience:

Case Studies:

Related Services: Fractional CTO, AI Agents, RAG Systems, LangChain

💼 Real-World Results

Enterprise AI Transformation

Anaqua (RightHub)
Challenge

Transform IP management platform with AI capabilities, from zero AI to acquisition-worthy features.

Solution

Led complete AI strategy: identified high-value use cases (semantic search, document analysis, AI agents), designed architecture, built team capabilities, delivered production systems.

Result

AI capabilities became key factor in acquisition. Built 0→1 AI platform processing 10K+ daily queries.

AI Cost Optimization Strategy

Flowrite
Challenge

Scale AI email writing from 10K to 100K users while controlling costs.

Solution

Developed multi-model strategy with intelligent routing. Matched model capability to task complexity. Built cost monitoring and optimization.

Result

40% cost reduction while 10x user growth. Enabled sustainable unit economics.

AI Product Strategy

Sparrow Intelligence
Challenge

Define AI offerings for consulting practice.

Solution

Identified enterprise AI pain points, designed service offerings, built reusable components for reliable AI agents.

Result

Clear positioning in enterprise AI space with differentiated offerings.

⚡ Why Work With Me

  • ✓ Led AI transformation resulting in acquisition (Anaqua)
  • ✓ Built production AI, not just strategy decks
  • ✓ Understand both technology AND business value
  • ✓ Practical approach, focus on what works
  • ✓ Can help implement, not just plan

Discuss Your AI Strategy

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