📘 Overview

This 16-hour executive training program is designed for executives seeking to strengthen their strategic capabilities in leveraging Artificial Intelligence (AI) and intelligent automation for sustainable business transformation.

It represents an advanced continuation of a previously HRDA vital program, namely “AI Leadership for Enterprise Transformation: Strategy, Governance, and Innovation”. The new program extends participants’ understanding of the practical deployment of intelligent automation frameworks, including AI-enabled automation and decision-support tools that enhance performance, compliance, and innovation. Thus, participants will develop the knowledge, skills, and mindset required to design, implement, and oversee AI-driven automation strategies that align with organizational goals and regulatory frameworks. The course combines conceptual learning, applied case studies, and strategic design workshops, providing leaders with comprehensive tools for AI governance in accordance with the EU AI Act and ethical leadership standards.

🧭 Why this seminar

The rapid advancement of intelligent systems and automation technologies has created an urgent need for leaders who can strategically integrate Artificial Intelligence (AI) into core business operations. Modern organizations require professionals who understand both the opportunities and risks associated with AI adoption and who can develop and implement ethical, transparent governance frameworks. These leaders must be able to leverage AI-powered automation tools to enhance operational efficiency, decision-making, and innovation. Equally important is their ability to foster cross-functional collaboration between technology and business units while ensuring full compliance with European and national AI regulatory standards. This program responds directly to these needs by preparing AI-literate and governance-ready leaders who can drive innovation responsibly, align AI initiatives with organizational values, and promote sustainable, human-centered technological transformation.

🎓 Learning Outcomes

1. Define the concept of intelligent automation and differentiate it from traditional automation and RPA systems.
2. Describe how different types of intelligent tools (reactive, goal-based, and learning) are applied in enterprise scenarios.
3. Explain the core components of AI tools deployment, including data readiness, trigger mechanisms, and human oversight.
4. Identify where in the value chain AI automation can generate strategic business value.
5. Define performance indicators for assessing AI success at an executive level (e.g., ROI, efficiency gains, risk mitigation).
6. Define governance, ethics, and acceptable decision boundaries for Supervised or human-in-the-loop automation.
7. Explain the difference between task-level automation and strategic orchestration of AI systems.
8. Recognize the role of executives in selecting, scaling, and supervising AI-powered platforms and tools.
9. Describe cultural and organizational conditions that enable successful AI tools adoption.
10. Explain leadership responsibilities in managing AI-driven transformation and innovation.

Skills Objectives

1. Implement innovation by distinguishing AI-enabled automation from traditional automation and RPA systems to drive more adaptive and intelligent business solutions.
2. Apply appropriate types of AI-automation (reactive, goal-based, learning) to relevant enterprise use cases.
3. Operationalize core conditions for AI deployment, including data readiness, triggers, and human oversight.
4. Create strategic opportunities within business functions where AI tools can create measurable value.
5. Evaluate AI effectiveness using executive-level performance indicators such as ROI, efficiency, and decision support quality.
6. Develop internal governance guidelines for the responsible use of automation based on ethical and operational constraints.
7. Plan automation strategies by distinguishing between task-level automation and orchestrated, enterprise-wide AI systems.
8. Monitor cross-functional teams in the evaluation and adoption of AI platforms aligned with business needs.
9. Facilitate organizational change by assessing culture and readiness factors critical to successful AI transformation.
10. Operationalize the leadership role in championing AI-enabled innovation and overseeing enterprise adoption of Supervised or human-in-the-loop automation.

Attitude Objectives

1. Adopt a strategic, opportunity-driven mindset toward intelligent automation.
2. Promote ethical, transparent, and human-centered AI deployment practices.
3. Embrace collaboration between leadership, data teams, and business units for AI integration.
4. Encourage experimentation and continuous improvement in AI applications.
5. Demonstrate confidence in guiding innovation through AI-enabled business models.

🏢 In-Company Part

Hour 1: Understanding the Organization’s Automation Landscape

• Icebreaker and objective setting
• Presentation by the company on current workflows, key challenges, and digital transformation priorities
• Interactive mapping exercise: Participants align internal business functions with AI-automation opportunities using a simplified orchestration canvas
• Q&A session to clarify context, goals, and internal barriers

Hour 2: Identifying Use Cases with Strategic Value

• Workshop: Participants identify 2–3 potential areas for intelligent automation within their departments
• Group activity: Score and prioritize opportunities using business impact, risk, and cultural feasibility lenses
• Facilitator input: Provide recommendations on scaling and sequencing based on training insights

Hour 3: Governance, Metrics, and Change Readiness

• Discussion: What guardrails, leadership roles, and governance structures are needed for safe AI-automation deployment?
• Collaborative task: Draft a preliminary AI performance dashboard using leadership KPIs (e.g., time saved, errors reduced, employee engagement)
• Mini-debate: Who should make final decisions when AI-driven automation is involved?

Hour 4: Strategy Alignment and Executive Leadership

• Workshop: Design a high-level rollout strategy (goal, sponsor, team, tools, timeline)
• Role-play simulation: Present the strategy to an internal stakeholder (e.g., CFO, COO)
• Closing: Reflect on leadership’s role in building an automation-ready culture
• Commitment circle: Each leader sets one next step to move forward