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Think Like AI
The training titled 'Think Like AI,' held on 8-9 July 2024, aimed to equip participants with the skills to think like artificial intelligence. In addition to learning how AI algorithms work, participants followed the processes these algorithms use to explore how they could apply similar thinking and problem-solving methods in their own working lives. The training focused on understanding how AI generates fast, effective solutions and integrating these approaches into their own professional processes. The main topics of the training led by Prof. Dr. C. Ruhi Kaykayoğlu were: 1. Modular Thinking: AI generates solutions by breaking large, complex problems into small, manageable parts. By adopting this modular approach, participants learned to manage complex projects more efficiently. 2. Rapid Decision-Making: AI can quickly analyze large datasets to find solutions in a short time. Participants explored how to integrate these rapid decision-making mechanisms into their business processes. 3. Continuous Improvement and Learning: Inspired by AI's ability to continually update and improve itself, the participant
At a glance
- Project Focus
- Transformation with AI · Problem-Solving
- Solution Area
- Transformation with AIProblem Solving with TRIZ
- Approaches Used
- Facilitation
- What Emerged
- A hands-on program in which teams tested technology against their own problems · Use cases drawn from real business contexts
- Year
- 2024
Inside the project
Focus
How can AI become an organizational capability without diminishing human creativity?
This project focused on connecting training needs with technology. The organization wanted not just to purchase new tools, but to embed them in the way its teams work.
The account of this project was structured around the organization's own definition of its needs.
The 'Think Like Artificial Intelligence' training held on 8-9 July 2024 aimed to equip participants with the ability to think like artificial intelligence.
Technology becomes useful not when its use cases are listed, but when teams test it against their own problems.
Scope
We explored with participants how AI algorithms work and how their reasoning and problem-solving processes can be applied at work. We worked on breaking complex problems into smaller parts, making quick data-informed decisions, and adopting continuous learning approaches.
Implementation
WHAT ROLE DID GENAI PLAY IN THIS PROJECT?
GenAI was positioned not as a tool that produces ready-made answers, but as a working partner that helps teams address their own problems through stronger questions. Every example was drawn from a real business context.
What brings technology into an organization is not the tool itself, but teams’ ability to engage with it through their own problems.
The journey we designed
- 01EXPLOREA situation map was developed by considering the organization's real needs, current ways of working and external signals together.
- 02REFRAMEParticipants practiced creative problem solving and application through their own real work problems.
- 03BRING IT INTO THE ORGANIZATIONA follow-through plan was developed with teams to connect the methods learned to daily workflows.
Kaykayoğlu project insight
The value of new tools begins not when they are purchased, but when people use them to ask stronger questions.
Explore further
Selected resources that examine the transformation highlighted by this project from a broader perspective.