AI STRATEGY ADVISORY PROGRAM
AI Doesn't Transform Companies. AI Strategy Does.
Get a complete AI strategy in 8 weeks — readiness assessment, prioritized portfolio, product concepts, implementation roadmap — shaped by 25 years of building what works.
Every leadership team is asking the same questions: Where should we invest in AI? What can we build versus buy? How do we move fast without breaking what works?
The answers don't come from technology — they come from strategy. Most AI initiatives fail not because the models don't work, but because organizations chase the wrong use cases, underestimate implementation complexity, or lack the roadmap to move from pilot to production.
Our AI Strategy Advisory Program delivers what your team needs to make confident decisions: an objective assessment of your AI readiness, a prioritized portfolio of high-impact use cases, detailed product concepts for your top opportunities, and a phased implementation roadmap — all in 8 weeks.
This program is led by George Krasadakis — holder of 20+ AI/ML patents, architect of Ainna.ai (the world's first AI Innovation Agent), and author of Innovation Mode 2.0: Designing Innovative Companies in the Era of Artificial Intelligence. This isn't AI advice from someone who read about it. It's strategy from someone who builds it.
The hardest part of AI isn't the technology. It's knowing where to apply it.
Executive teams are drowning in AI noise:
Vendors promising transformation with no clarity on implementation
Pilots that never scale beyond the demo
Pressure from boards asking "what's our AI strategy?" with no good answer
Technical teams excited about capabilities but disconnected from business value
Fear of falling behind while competitors announce AI initiatives
What's missing isn't AI expertise — it's strategic clarity. A framework for deciding where AI creates genuine competitive advantage versus where it's just expensive automation.
This program provides that clarity.
WHAT'S INCLUDED
Deliverables you can act on — not frameworks that gather dust.
The AI Strategy Advisory Program delivers five concrete outputs:
1. AI Readiness Assessment. A comprehensive diagnostic of your organization's AI capabilities across five dimensions: data infrastructure, technical talent, process maturity, leadership alignment, and cultural readiness. No generic benchmarks — a diagnosis specific to your operating reality, identifying exactly where you're strong and where the gaps will slow you down.
2. AI Use Case Portfolio. A prioritized portfolio of AI opportunities mapped across your business — from quick wins that build momentum to strategic bets that create competitive moats. Each use case scored on business impact, technical feasibility, data readiness, and implementation complexity. Not a wishlist; a decision-ready framework.
3. AI Product Concepts. For your top 3-5 priority use cases, we develop detailed product concepts: user journeys, technical architecture sketches, build-vs-buy recommendations, integration points, and success metrics. These are the specifications your product and engineering teams need to move from "interesting idea" to "let's build this."
4. AI Implementation Roadmap. A phased transformation plan covering the next 12-24 months: what to pilot first, what to scale, what to defer. Includes technology stack recommendations, vendor evaluation criteria, talent requirements, governance framework, and risk mitigation strategies. Each phase has clear milestones and decision gates.
5. Executive AI Briefing. A board-ready presentation synthesizing findings, recommendations, and roadmap — designed for communicating AI strategy to leadership, investors, and stakeholders. Includes talking points for common questions and concerns.
Every program includes 10 copies of the Innovation Mode 2.0: Designing Innovative Companies in the Era of Artificial Intelligence — the complete framework for building AI-powered capabilities, and ongoing reference for your leadership team.
THIS PROGRAM IS DESIGNED FOR
Executives ready to move from AI conversations to AI decisions and leadership teams who:
• Know AI is strategically important but lack clarity on where to invest
• Have run pilots that didn't scale — and want to understand why
• Need to present an AI strategy to their board within the next quarter
• Want to separate genuine AI opportunities from vendor hype
• Are ready to move from talking about AI to building with it
The program works for organizations from growth-stage to enterprise scale, across industries. What matters is leadership commitment to act on the findings — not just collect another report.
Strategy with a deadline. Clarity in 8 weeks.
This is a rapid, focused advisory engagement: 50 hours of AI strategy consulting delivered across 32 sessions over 8 weeks. Available fully remote or hybrid.
Each week targets a specific dimension of your AI strategy — building toward actionable recommendations your team can execute.
WEEK #1 - AI READINESS
"Where do we actually stand?"
We conduct a comprehensive assessment of your AI capabilities: data infrastructure and quality, technical talent and skills gaps, existing AI/ML initiatives, vendor relationships, and organizational readiness for AI-driven change. We benchmark against what's actually achievable and identify the specific constraints that will shape your strategy.
Output: AI Readiness Assessment with capability gaps and priority areas.
WEEK #2: OPPORTUNITY MAPPING
"Where can AI create real value — not just efficiency?"
We map AI opportunities across your entire value chain — customer experience, operations, product development, decision-making, and back-office functions. We interview stakeholders across business units to surface pain points and unmet needs. The goal: identify where AI creates competitive advantage, not just automation.
Output: Comprehensive AI opportunity map across business functions.
WEEK #3: STRATEGIC PRIORITIZATION
“Which bets do we make first?”
We score and prioritize identified opportunities using a rigorous framework: business impact, technical feasibility, data readiness, time to value, and strategic alignment. We separate quick wins from long-term bets, and identify the sequencing that builds capability while delivering results. You'll know exactly which use cases to pursue — and which to defer.
Output: Prioritized AI Use Case Portfolio with scoring rationale.
WEEK #4: AI CONCEPTS DEFINITION
“What would we actually build?”
For your top 3-5 priority use cases, we develop detailed product concepts. This includes user journeys, technical architecture sketches, data requirements, integration points, build-vs-buy analysis, and success metrics. These aren't vague ideas — they're specifications your teams can act on.
Output: Detailed AI Product Concepts for priority use cases.
WEEK #5: TECHNOLOGY & VENDOR STRATEGY
“Build, buy, or partner - and why?”
We develop recommendations on technology stack, vendor selection, and build-vs-buy decisions. This includes evaluation criteria for AI platforms, guidance on foundation models vs. custom training, and a framework for vendor assessment. We also cover infrastructure: cloud strategy, compute requirements, and data architecture.
Output: Technology strategy and vendor evaluation framework.
WEEK #6: GOVERNANCE, RISKS, ETHICS
“How do we adopt and scale AI responsibly?”
We design an AI governance framework appropriate to your organization: policies for data usage, model validation, bias monitoring, and human oversight. We address regulatory considerations, IP protection, and risk management. This isn't about slowing you down — it's about building AI capabilities that scale without creating liabilities.
Output: AI Governance Framework and risk mitigation plan.
WEEKS #7-8: IMPLEMENTATION ROADMAP
“What's our path from here to AI-powered?”
We synthesize all findings into a comprehensive AI Implementation Roadmap covering 12-24 months:
1. Foundation (Months 1-3): Quick wins, data infrastructure, team formation
2. Build (Months 4-9): Priority use case development, pilot deployment, learning cycles
3. Scale (Months 10-18): Production rollout, capability expansion, organizational embedding
4. Evolve (Months 18+): Advanced use cases, autonomous systems, continuous optimization
Each phase includes specific milestones, resource requirements, decision gates, and success metrics.
Final Deliverables: (a) AI Readiness Assessment, (b) Prioritized Use Case Portfolio, (c) AI Product Concepts, (d) AI Implementation Roadmap, (e) Executive AI Briefing deck, (f) Innovation Mode 2.0 copies for leadership team.
THE ARCHITECT OF THE PROGRAM
AI strategy from someone who builds AI - not just advises on it.
This program is led by George Krasadakis — a technologist who has been architecting intelligent systems for 25 years. George has 25 years of experience across multinationals and startups. He holds 20+ patents as sole inventor in AI and machine learning — negotiation agents, voice-driven ideation systems, natural language processing architectures. His patent portfolio reads like a 2025 AI startup pitch deck, except he filed these a decade ago. The work has since been cited 500+ times by inventors and global technology giants building on his foundations.
His foundation is scientific: an MSc in Computational Statistics, with deep expertise in data modeling and software architecture. This technical grounding matters — today's large language models are sophisticated statistical machines. George spotted the opportunity early and has been building AI-powered systems across startups and multinationals ever since: Microsoft, Accenture, GSK, and four technology ventures of his own.
Currently, George is the architect of Ainna.ai — the world's first AI Innovation Agent. Ainna embodies the principles he advises on: an autonomous system that discovers opportunities, validates concepts, and generates execution-ready documentation. It's proof that AI-powered transformation isn't theoretical.
The Innovation Mode is a specialized advisory firm based in Dublin, Ireland, serving clients across Europe and the United States. We offer AI strategy consulting and corporate innovation programs for enterprise leaders seeking to build sustainable competitive advantage through artificial intelligence.
AI Advisory: Frequently Asked Questions
How is this different from AI consulting from the big firms?
Two things. First, you work directly with someone who builds AI systems — not partners who delegate to junior analysts learning on your dime. The advice comes from hands-on experience, not frameworks. Second, the deliverables are designed for action: product concepts your teams can build, not slide decks that sit on a shelf.
We're not a tech company. Is this relevant for us?
AI strategy is no longer a tech company concern. Pharma, manufacturing, financial services, logistics — every industry has AI opportunities. The frameworks adapt to your context. What matters is whether you're ready to act on the findings.
Who should participate from our organization?
The program works best with a core team of 4-6 stakeholders: C-suite sponsor (CEO, COO, or CDO), heads of product or technology, business unit leaders who would own AI initiatives, and someone from data/analytics. We'll advise on optimal participation during scoping.
What's the time commitment for our team?
Expect 4-6 hours per week from your core team across interviews, workshops, and review sessions. The 50 hours of advisory is our commitment; your team's involvement is intensive but manageable.
Do you help with implementation?
The program delivers strategy and roadmap; implementation is typically led by your internal teams or partners. For organizations wanting ongoing advisory support during execution, we offer quarterly check-ins and extended engagements.
What if we've already started AI initiatives?
Even better. We'll assess what's working, what isn't, and how to course-correct. Many organizations have pilots that haven't scaled — understanding why is often more valuable than starting fresh.
How does this relate to the Innovation Mode Advisory Program?
The Innovation Mode Advisory Program focuses on building organizational innovation capability — systems, culture, and processes for systematic opportunity discovery. The AI Strategy Advisory Program focuses specifically on AI adoption: where to invest, what to build, how to implement. They're complementary; some clients do both.
What is AI strategy consulting?
AI strategy consulting helps organizations identify where artificial intelligence can create business value, prioritize use cases, develop product concepts, and create implementation roadmaps. Unlike general technology consulting, AI strategy focuses specifically on how to leverage machine learning, large language models, and intelligent automation to achieve competitive advantage — not just efficiency.
How long does it take to develop an AI strategy?
A comprehensive AI strategy can be developed in 8-12 weeks with focused effort. This program delivers a complete strategy in 8 weeks: AI readiness assessment, prioritized use case portfolio, product concepts for top opportunities, and a 12-24 month implementation roadmap. Longer timelines often indicate scope creep rather than thoroughness.
What is an AI readiness assessment?
An AI readiness assessment evaluates your organization's capability to successfully implement AI initiatives. It examines five dimensions: data infrastructure and quality, technical talent and skills, process maturity, leadership alignment, and cultural readiness for AI-driven change. The assessment identifies gaps that could slow implementation and informs realistic prioritization.
How do I prioritize AI use cases?
Prioritization requires evaluating opportunities across multiple dimensions: business impact (revenue, cost, competitive advantage), technical feasibility (complexity, maturity of AI approaches), data readiness (availability, quality, accessibility), time to value (quick wins vs. long-term bets), and strategic alignment. A rigorous scoring framework prevents chasing exciting technology that doesn't drive business value.
Why do AI pilots fail to scale?
Most AI pilots fail for predictable reasons: wrong use case selection (technically interesting but low impact), data problems discovered late (quality, access, governance), lack of integration planning (AI works but doesn't connect to processes), missing change management (users don't adopt), and no clear path from pilot to production. A proper AI strategy prevents these failures upfront.
START YOUR AI STRATEGY
Fill in the form below to receive a tailored proposal. We'll respond within 48 hours with program options matched to your organization's size, industry, and AI maturity.