Artificial Intelligence for Leaders: Strategy, Value, Future

To teach business owners, executives, and experts how to turn AI into a real source of growth and profit.

Business owners, managers, analysts, consultants.

In-person, Vilnius, 2 months, 8 sessions + thesis defense.

January 9, 2026

Why Do Leaders and Experts Need to Understand AI?

To make informed, data-driven decisions

Modern decision-making – from financial planning to product strategy – is impossible without data analysis and predictive models. A leader who understands the principles of AI:

effectively assesses the risks and benefits of technological initiatives;
identifies areas for automation and process optimization;
correctly interprets model outputs and avoids mistakes caused by misinterpreting data.

To collaborate effectively with technical teams

Understanding technology enables leaders to formulate tasks more precisely, set realistic KPIs, and properly evaluate the results of development and analytics teams.

To adhere to legal and ethical standards

AI requires a new level of responsibility: algorithmic bias, protection of personal data, and compliance with regulatory requirements. A leader who understands these aspects reduces their company’s risks.

Executive program for leaders who are responsible for company growth and want to understand how to use AI without risks and unnecessary costs

Meet Our Mentors

Gintautas Mežetis

A data-driven leader with a strong background in digital transformation, risk management, and expertise across various sectors including satellite, data center, fintech, energy, and AI. With a strategic-analytical mindset and extensive experience in technology and business communication, he excels in simplifying complex information and concepts while creating impactful solutions, as evidenced by his leadership roles at VIALET, Paysera, and previous executive positions focused on digital innovation, infrastructure development, and strategic business growth.

Roman Rimša

The Managing Director at Sigli. He focuses on digital transformation and applied AI, guiding teams from strategy to delivery. He also advises startups and shares practical lessons from implementation.

David Mataciunas

Deividas Mataciunas is the CTO and Co-Founder of AQ22, passionately developing AI agents that help financial institutions make their private credit processes more efficient, automate underwriting, and enable faster, data-driven lending decisions. With a background in both finance and machine learning, he has previously worked at IBM and Sunrise UPC, creating AI solutions for global banks and private equity firms. Deividas is also a member of the AI Association of Lithuania and serves as the European Region Lead at Cohere for AI. His pioneering research on AI data access and multilingual models has been published at NeurIPS and highlighted in The New York Times.

Maxim Golikov

Chief Business Development Officer, Sigli
15+ years in digital transformation and AI (operations, sales, service).
Startup mentor at Plug and Play Lithuania.
Host of the Innovantage podcast about business and technology.

Dr. Neringa Gaubienė

Artificial Intelligence Regulation Expert, Researcher & Partner at AI Clinic.

Dr. Neringa Gaubienė is a leading expert in artificial intelligence regulation and digital technology law, combining academic research, legal practice, and business consulting.

She teaches Law and Digital Technologies at the Faculty of Law, Vilnius University, and serves as the lead researcher of the Digital Technologies, Cybersecurity, and Law research group.

Vitali Krupenka

With over 20 years in IT, specializing in project management, consulting, and Al solutions development, I have helped large corporations, SMBs and startups build and optimize engineering teams and implement Al solutions to enhance business process efficiency.

Program

Module 1: Artificial Intelligence in the Era of Digital Transformation

Date:

10:00-18:00

Session 1: Strategy & Disruption: From Hype to Value in a VUCA World

Goal

Understand how AI and other disruptive technologies shift competitive dynamics and industry structure – and how to embed them in overall business strategy.

How to think about strategy in a VUCA world. Speed, uncertainty, and information asymmetry.

AI in practice. Moving from hype to an economics-of-value view.

Tech shift & competition. How AI/cloud/IoT reshape Porter’s Five Forces and the Value Chain.

Expected Outcomes

A clear view of competitive pressure through an “AI lens.”
Focused priorities: where to defend margin and where to pursue growth.

Session 2: Business & Digital Transformation

Goal

Build a structured business/IT alignment model to avoid the “IT black hole” and consistently turn digital initiatives (incl. AI) into business outcomes.

The role and value of IT in business strategy.

Frameworks. Porter’s Five Forces, Value Chain (where tech strengthens competitive position), and Nolan–McFarlan (IT’s role: innovation vs. reliability).

Business ↔ IT strategy / Alignment.

SAM (Henderson–Venkatraman), expression/specification/execution barriers, measurement approaches (scoring/maturity, Luftman), and using the Balanced Scorecard for “digital mastery.”

Governance. EGIT in practice.
Structures, processes, and relational mechanisms (Run/Grow/Transform portfolio, committees, decision rights).

Expected Outcomes

Clear articulation of IT/AI’s role in strategy.
A governance “skeleton” to scale successful use cases.

Module 2: From Strategy to Management

Date:

10:00-18:00

Session 3: Embedding AI into Corporate Strategy, Implementation Roadmaps

Goal

Strategic Planning Framework.

Define the strategic plan as weighting alternatives (market, cost, customer) to achieve advantage.
Show where AI can support or transform these choices.

Process Maturity & AI Integration.

Outline process maturity stages: standardised → documented → measured → controlled.

Highlight AI roles.

Automating steps or full process.

Real‑time sampling & measurement.

Case Exercise – “From As‑Is to To‑Be”.

Analyze a scenario, identify AI opportunities, draft a transition roadmap.

Expected Outcomes

Clear strategic planning framework.
Understanding of process maturity and AI enhancement.
Practical application through case exercise.

Session 4: AI Governance and Risks – Frameworks (COBIT, EU AI Act, ISO), Balancing Risks and Opportunities

Goal

AI Governance within the Company.

How AI projects are linked to business goals, who is responsible for them, and how “go / no-go” decisions are made. We use the logic of EGIT / COBIT / the Strategic Alignment Model.

Prioritization of AI Initiatives.

AI Value Matrix: how to assess each idea in terms of business value, data availability, implementation complexity, presence of a sponsor, and clear KPIs.

Practical Work.

Participants fill out the matrix using their real cases, receive an evaluation of “business value vs feasibility,” and select a project to include in their final course work.

Expected Outcomes

A clear model of AI accountability within their company (who owns, who sponsors, who is responsible for results).
A prioritized list of AI initiatives – not just “ideas in the air,” but a concrete shortlist.
A solid, board-ready argument: which initiative to start with, why this one, and what effect is expected in the next 3–6 months.

Module 3: AI Use Cases and Industry Applications

Date:

10:00-18:00

Session 5. AI in Operations & Efficiency: From Cost Center to Value Driver

Goal

Provide leaders with a P&L-focused framework to identify, prioritize, and execute high-ROI AI initiatives in core operations (supply chain, logistics, and maintenance).

Finding the “hidden money”. How to spot and quantify the highest-impact AI opportunities in your existing processes.

Beyond the buzzwords. Real-world wins in Supply Chain (forecasting), Logistics (routing), and Predictive Maintenance (uptime ROI).

The Leader’s Real Challenge. Overcoming critical barriers in data, process adoption, and team resistance.

Interactive Workshop. A framework to prioritize “quick wins” and build a compelling business case for C-level/investors.

Expected Outcomes

Ability to spot and quantify high-potential AI use cases in your own operations.
A clear model for “selling” operational AI initiatives internally, focusing on ROI and risk mitigation.
Actionable insights to move from “reactive” to “predictive” operations.

Session 6: AI for Growth and Customer Experience – Personalization, Marketing, New Products

Goal

Understand how to leverage AI to drive business growth through improved customer experiences, optimized marketing and sales, and the creation of innovative products.

Personalization, marketing, sales optimization.

How AI enables hyper-personalization of the customer journey.

Applying AI for targeted marketing campaigns, lead scoring, and sales forecasting.

Optimizing customer relationship management (CRM) and conversion rates using predictive models.

Creating new products with AI.

Using AI to identify unmet customer needs and market gaps for product innovation.

Embedding AI directly into products and services to enhance functionality and value.

Accelerating R&D and time-to-market through AI-powered design and simulation.

Case discussion: data-driven customer journey.

Analyzing a real-world example of how a company mapped and optimized its customer journey using AI and data analytics.

Discussing the challenges and successes of implementing a data-driven approach to customer experience.

Expected Outcomes

A framework for identifying high-impact areas in the customer journey and marketing funnel for AI implementation.
Actionable strategies for leveraging personalization to increase customer lifetime value (CLV).
Insights into developing AI-powered new products that capture market share.

Module 4: Leadership and Legal Aspects in the Age of AI

Date:

10:00-18:00

Session 7: Legal & Compliance in AI – EU Regulation, Ethics & Responsibility

Goal

Key legal frameworks. EU AI Act, GDPR, civil liability & IP aspects

Risk-based approach. System classification, high-risk requirements & obligations for providers and deployers

AI literacy & organizational readiness. Compliance duties for teams and leadership

Ethical & responsible AI use. Transparency, human oversight, fairness, data quality, and explainability

Lithuania’s regulatory landscape & institutional roles. Supervisory bodies, guidance, implementation updates

Practical exercise. Evaluating an AI system’s compliance & risks (e.g., recruitment, public sector services, legal practice)

Expected Outcomes

Understand key EU and local regulatory requirements for AI (GDPR, EU AI Act, liability).
Be able to assess AI system risks and develop measures to reduce them in terms of compliance, ethics, and transparency.
Understand the role of supervisory authorities and sector-specific requirements, including the public sector and legal practice.

Session 8: The Future of AI – Leadership + Creativity

Goal

We cover the practical side of AI adoption, you do what you do best.

How to think creatively and globally about new technologies.

The human factor in a world of algorithms.

How leaders can drive change and innovation in fast-shifting markets.

We believe your voice on creativity and business innovation would be the perfect way to close the course — giving participants energy, perspective, and courage to embrace change.

Expected Outcomes

Learn to think creatively about technology and account for the human factor in a world of algorithms.
Master leadership approaches to drive innovation and confidently guide teams through change.

thesis defense

Date:

10:00-18:00

thesis defense

Group work on a business case of AI implementation.

Each team develops and presents a strategy for applying AI in a specific company or industry.

What makes

the program unique

Participants learn to see where AI truly creates impact: increasing margin, reducing costs, growing CLV, accelerating processes, and improving forecasting.

Porter models, SAM, Balanced Scorecard, EGIT – adapted for working with AI so that digital initiatives stop being a “black hole” and become a tool for competitive advantage.

AI Value Matrix helps form a shortlist of AI initiatives that can be presented to the CEO, the board, or investors.

Logistics, supply chains, maintenance, forecasting – participants learn to find “hidden money” and calculate ROI for their own processes.

Personalization, prediction models, AI-driven product design, market niche discovery – all based on examples from real companies.

The program concludes with demonstrations of how AI unlocks new opportunities and also has creates the potential for serious legal risks.

Not sure if the course is right for you? Book a consultation.

January 9, 2026

Deadline for applications: December 31, 2025

What the company gains

Ready-to-implement AI projects with impact within 3–6 months.
Reduced risks of digital transformation.
Strengthening of innovation culture.
Leaders who confidently work with data and technology.
Increased competitiveness in the digital economy.

What each participant gains

Clear understanding of technologies and their business value.
Skills in strategic and creative thinking about future markets.
The ability to defend an AI project ready for implementation.
The capability to work effectively with analyst and developer teams.
Confidence in decision-making in a VUCA environment.

Join our webinars and meet our mentors

Practical AI tools for business: a framework to evaluate AI projects

Stop Wasting Your Budget: Selecting High-ROI AI Initiatives

Course price

2500 €

Enter promo code for 500 € discount

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Frequently Asked Questions

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