Durată: 2 zile
Certificare: Diploma de participare

The following minimal prerequisites are required:
● Basic familiarity with business operations and strategy concepts
● Interest in understanding the potential applications and impact of AI on business
● No prior deep technical expertise or programming skills are required
The Core Curriculum provides essential AI strategic understanding through a 2-days course (approx. 7 hours daily), balancing foundational concepts (~30-40%) with strategic application discussions and frameworks (~60-70%).
The complementary optional Advanced Modules (1-2 days) are available for companies seeking to develop more comprehensive AI strategies and governance structures.
The Core Curriculum (Essential Strategic Skills):
● Day 1: AI Fundamentals and Business Opportunities - Builds foundational knowledge of AI capabilities, communication techniques, tools evaluation and responsible AI principles
● Day 2: AI Integration Strategies and Implementation Considerations - Delivers actionable knowledge on leveraging internal data, integration approaches, strategic automation and building business cases Advanced Modules (Strategic Planning & Governance):
● Advanced Module 1: Developing Your Organization's AI Strategy (1+ days): Focuses on creating a cohesive AI strategy, aligned with business goals, competitive analysis and capability planning
● Advanced Module 2: Governing AI Initiatives & Measuring Their ROI (1+ days): Covers establishing governance frameworks, managing the AI projects lifecycle, defining business KPIs and measuring their ROI
The sessions include presentations, case study discussions, framework applications and strategic planning exercises, designed for maximum knowledge retention relevant to leadership roles.
Day 1: AI Fundamentals & Business Opportunities
● Training overview and expectations setting (~10 min)
● 1.1: AI overview and sub-domains: core concepts & strategic value - AI/DL/ML/NLP/CV/GenAI overview, business value mapping overview
● 1.2: AI opportunity mapping workshop: identify the potential AI use-cases for the main business challenges
● 1.3: Developing actionable AI use-cases: converting the high-level opportunities into well-defined integration use cases, with clear business contexts
● 1.4: Evaluating AI tools: landscape, selection & integration - categories, evaluation criteria, integration challenges
● 1.5: Responsible AI: managing business risks & building trust - fairness, reliability, privacy, transparency and accountability, from a business perspective
● Day 1 review and Q&A
Day 2: AI Integration Strategies & Implementation Considerations
● 2.1: Strategic prioritization of AI initiatives: prioritize the identified AI initiatives, for a gradual integration
● 2.2: Data foundations for AI success: assess and plan the organizational data used in the prioritized AI integrations
● 2.3: Practical integration pathways: high-level overview of the integration methods with the existing business systems
● 2.4: Crafting compelling AI integration business cases: ensure the organizational buy-In, using quantifiable value propositions
● 2.5: Roadmap development for sustainable AI growth: create a phased implementation plan, with defined success metrics
● Overview of the optional advanced modules
● Course wrap-up, evaluation of the next steps
● Final Q&A and feedbac