AI Opportunity Matrix
Structured assessment of every department's AI potential, ranked by business impact and technical feasibility, with clear priority recommendations.
A practical framework for strategy firms to build and deploy enterprise AI capabilities — from opportunity assessment to production delivery.
Strategy consulting and AI execution have evolved along parallel tracks — but they need to converge.
Strategy firms excel at diagnosing problems, crafting roadmaps, and advising leadership. But without an execution mechanism, those roadmaps stay on slides. AI, uniquely, requires both strategic vision and technical delivery to create value.
A 2025 McKinsey survey found that 72% of organizations have adopted AI in at least one function, but only 12% report significant revenue impact. The gap is not in AI technology — it's in bridging strategy to production. Most companies get stuck after the strategy phase because they lack the execution infrastructure, the engineering talent, or the experience to deploy AI that actually works in production.
This proposal outlines a unified framework where strategy consulting and AI engineering operate as a single delivery engine — not as separate phases handed off between teams.
Through work with executive teams across financial services, insurance, and technology sectors, we've identified a consistent pattern: companies invest heavily in AI strategy, then stall at the execution boundary.
Traditional consulting engagements produce PowerPoint decks with AI recommendations, technical architectures, and vendor assessments. What they don't deliver: working code, production deployments, integrated systems, or measurable outcomes. The client receives a blueprint but lacks the engineering capacity to execute. By the time they find implementation partners, momentum is lost, timelines slip, and budgets double.
Our approach collapses the traditional consulting-then-build waterfall into a continuous cycle. We start with a Strategic Discovery Sprint to align on opportunity and feasibility, then move immediately into iterative delivery — each cycle producing production-ready capability.
Unlike traditional consulting engagements where strategy teams pass deliverables to implementation teams (creating translation loss), we operate as a unified delivery unit. The same team that identifies the opportunity and designs the solution also builds and deploys it. This eliminates the handoff overhead, preserves strategic intent through to production, and compresses timelines by 40–60%.
Our methodology maps to four distinct phases, progressing from business context to technical production. Each phase produces concrete, verifiable outputs.
Understand the business, identify highest-impact AI opportunities, and define success criteria.
Build and deploy the first AI experience — typically an Executive AI Assistant that demonstrates immediate, measurable value.
Go-live with real users, active monitoring, and structured feedback collection.
Expand capabilities, add new workflows, and deepen integration across the organization.
Tangible, production-ready outputs at every stage. Not PowerPoint — deployed, measurable capability.
Structured assessment of every department's AI potential, ranked by business impact and technical feasibility, with clear priority recommendations.
Deployed AI Executive Assistant connected to your company's knowledge base, email, and communication channels — not a demo, a working tool.
Connected knowledge base that the AI agent retrieves from: company documents, policies, historical data, and live systems — with permission controls.
Real-time analytics showing time saved, tasks completed, cost reduction, and user adoption metrics — updated daily, not after-the-fact.
Documentation, training sessions, admin playbooks, and ongoing support to ensure your team can maintain and extend the system independently.
Three engagement tracks, each designed for a different stage of AI maturity. All begin with a no-obligation Strategic Assessment call.
Based on deployments with executive teams across multiple sectors, typical results within the first 8–10 weeks.
"The single biggest unlock from this engagement wasn't the technology — it was finally having a partner who could both understand our strategic context and deliver working production software. We went from 'let's think about AI' to a deployed Executive Assistant handling our daily briefings, follow-ups, and knowledge retrieval in 8 weeks."
This is not a pure consulting engagement or a pure engineering project — it's a hybrid designed to overcome the specific failure modes of both approaches.
No handoff gap. The same team discovers, designs, builds, and deploys. Strategic intent is preserved through to production.
Compressed delivery timeline through battle-tested architecture, reusable patterns, and focused scope. We don't build everything — we build what matters first.
Every phase has quantifiable success metrics. You see time savings, cost reduction, and adoption data — not just qualitative "strategic alignment."
We don't create dependency. Documentation, training, handover, and admin tools ensure your team can manage, extend, and evolve the system post-engagement.
Pavel Anisimov — Fractional Head of AI with a track record of deploying production AI systems for executive teams. Previously led AI at a Sber unit, now focused on helping leadership teams move from AI experimentation to practical, measurable deployment. Builder of AI Executive Assistants that save organisations 10+ hours/week per executive. Combines deep technical capability with strategic consulting discipline.
Every engagement starts with a no-obligation Strategic Assessment call — 30 minutes to understand your context, identify opportunities, and determine fit.