Many companies start their AI journey with local initiatives — a chatbot, text generation, or automating a small task. But without a clear strategy, these attempts rarely scale or deliver long-term value. They often break against reality: unstructured data, internal resistance, lack of metrics, or scattered tools.
If you want to adopt AI consciously — with measurable impact on revenue, costs, and efficiency — the right starting point is an audit and a strategic roadmap.
This service helps you:
- identify processes where AI can deliver the greatest value (and where it won’t);
- understand where to realistically start;
- define the tools, data, roles, and resources required;
- and most importantly — build a clear, step-by-step strategy, not just “do AI for the sake of AI.”
What’s included
This is a hands-on expert engagement at the intersection of process analysis, product thinking, and AI technology.
As part of the project, I:
- Audit business processes: how your operations work, where time and money are lost, and what data is already available for AI;
- Identify potential AI application areas, prioritizing by expected impact and implementation complexity;
- Surface organizational constraints: infrastructure readiness, data maturity, team capabilities, and resources;
- Develop a strategic AI roadmap: phased implementation plan, MVP scope, checkpoints, and scaling path;
- Provide recommendations on tools, team structure, and success metrics;
- Build an economic justification: how AI adoption could impact your costs, revenue, or productivity;
- If needed — include competitor benchmarking and industry best practices.
What you get
- Diagnostics of current processes with a focus on automation and AI opportunities;
- A step-by-step implementation strategy: from pilot to scalable solutions;
- A prioritized plan: what to do now, later, or not at all;
- A risk and constraint assessment;
- A financial rationale for AI adoption;
- Actionable recommendations on technologies, team roles, and implementation approach.
Case example
Fintech. AI Strategy for Investor Relations Department
As the head of investor relations, I led a process audit for a 30+ person team of managers, agents, and analysts. The goal was to improve investor communications, reduce document preparation time, and relieve the team from repetitive tasks.
Based on this analysis, I developed an AI adoption strategy focused on:
— automating intake and processing of investor inquiries,
— generating personalized emails and replies,
— building and maintaining an internal knowledge base,
— preparing presentations, blueprints, applications, and other documents.
The solutions were implemented using off-the-shelf generative AI tools.
Why clients choose me
I combine strategic thinking, startup experience, and deep expertise in generative AI. I speak the same language as founders and product teams — while fully understanding what’s happening under the hood of AI models and tools.
I work fast, to the point, and without fluff. My goal is not just to “add an AI feature”, but to identify where it actually creates business value — by reducing costs, speeding up operations, or improving decision quality.
Each project benefits from a unique combination of:
— 12+ years in IT and product development,
— 3 years of hands-on practice with LLMs and AI-based automation,
— dozens of consultations and implemented solutions across industries.
My approach is based on clear diagnostics, pragmatic recommendations, and an actionable plan aligned with the company’s goals, constraints, and resources.