AI-Assisted Decision-Making and Productivity Training for Managers
A practical training program that helps managers use AI more effectively and safely for decision preparation, meeting management, reporting, prioritization, and managerial productivity.
About This Course
Detailed Content (EN)
This training is designed to help managers position generative AI not merely as a technology trend, but as a practical support system that improves management quality and decision-preparation speed. The program creates strong value especially for manager profiles who work under high information load, run many meetings, make sense of input from multiple teams, and need to make fast but controlled decisions.
Throughout the program, participants learn how AI and large language models work from a management perspective, experience how effective prompting improves output quality, and work on highly practical use cases such as summarizing reports, turning meetings into actions, structuring decision alternatives, clarifying risk messages, and drafting executive communication.
A key differentiator of the training is that it does not stop at individual productivity. It also addresses higher-level managerial needs such as team management, delegation, information standardization, cross-functional communication, internal reporting quality, executive summaries, and decision-support frameworks. As a result, participants learn not only how to manage their own workload more intelligently, but also how to guide AI usage more effectively within their teams.
The program also covers critical topics such as security, privacy, hallucinations, over-reliance, verification, and managerial accountability. This ensures that participants gain not only speed, but also a clear understanding of where human judgment must remain central and how to apply quality control before using AI outputs in real decision processes.
Who Is This For?
- Mid-level and senior managers
- Team leaders and department managers
- Directors, senior functional leaders, and executive sponsors
- Strategy, planning, and decision-support professionals
- Managers who want to improve team productivity
- Decision-makers who want to frame AI adoption at enterprise level
Highlights (Methodology)
- Management-oriented, process-focused delivery rather than tool-centric teaching
- Concrete use cases such as meetings, reports, presentations, emails, and decision preparation
- Live demos, hands-on prompt workshops, and executive scenarios
- A structure that combines daily productivity and managerial quality
- Verification, risk awareness, and quality-control thinking for AI outputs
- Frameworks suitable for developing internal manager AI usage guidelines
Learning Gains
- Use AI more consciously in decision preparation and management processes
- Generate faster and higher-quality outputs from meetings, reports, and information flows
- Make alternatives, risks, and actions more visible
- Create clearer, faster, and more effective managerial communication
- Apply security, privacy, and verification discipline in AI-assisted work
- Build a more systematic and sustainable AI usage culture within teams
Frequently Asked Questions
- Does this require technical knowledge? No. The training is designed for managers and focuses on business value, decision support, and productivity rather than technical depth.
- Is this only for senior executives? No. It is also highly suitable for mid-level managers, team leads, and process owners.
- Does the training include practice? Yes. It includes real managerial scenarios, prompt examples, and decision-support exercises.
- Can it be customized for an organization? Yes. The content can be tailored based on industry, management level, and priority workflows.
Training Methodology
Use cases directly aligned with the daily workload of managers
A practical structure focused on decision preparation, meetings, reporting, and communication
Management impact and business value orientation rather than technical depth
Verification, risk visibility, and quality-control thinking for AI outputs
Manager-level prompt design and structured thinking techniques
Content adaptable into internal managerial AI usage guidelines
Who Is This For?
Why This Course?
It makes the most time-consuming information-heavy managerial tasks faster and more systematic.
It connects AI usage in meetings, reports, emails, and action management directly to business value.
It makes alternatives, risks, and priorities more visible in the decision process.
It teaches reliable and verifiable AI usage rather than uncontrolled speed.
It helps management teams achieve productivity gains at both individual and team level.
It offers directly applicable managerial use cases grounded in real organizational practice.
Learning Outcomes
Requirements
Course Curriculum
39 LessonsInstructor

Şükrü Yusuf KAYA
AI Architect | Enterprise AI & LLM Training | Stanford University | Software & Technology Consultant
Şükrü Yusuf KAYA is an internationally experienced AI Consultant and Technology Strategist leading the integration of artificial intelligence technologies into the global business landscape. With operations spanning 6 different countries, he bridges the gap between the theoretical boundaries of technology and practical business needs, overseeing end-to-end AI projects in data-critical sectors such as banking, e-commerce, retail, and logistics. Deepening his technical expertise particularly in Generative AI and Large Language Models (LLMs), KAYA ensures that organizations build architectures that shape the future rather than relying on short-term solutions. His visionary approach to transforming complex algorithms and advanced systems into tangible business value aligned with corporate growth targets has positioned him as a sought-after solution partner in the industry. Distinguished by his role as an instructor alongside his consulting and project management career, Şükrü Yusuf KAYA is driven by the motto of "Making AI accessible and applicable for everyone." Through comprehensive training programs designed for a wide spectrum of professionals—from technical teams to C-level executives—he prioritizes increasing organizational AI literacy and establishing a sustainable culture of technological transformation.
Frequently Asked Questions
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