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Last updated on Mar 7, 2025
  1. All
  2. Engineering
  3. Artificial Intelligence (AI)

You're tackling complex AI concepts with non-technical colleagues. How do you make it understandable?

Got any tips for simplifying AI for everyone? Share your strategies for making complex ideas click.

Artificial Intelligence Artificial Intelligence

Artificial Intelligence

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Last updated on Mar 7, 2025
  1. All
  2. Engineering
  3. Artificial Intelligence (AI)

You're tackling complex AI concepts with non-technical colleagues. How do you make it understandable?

Got any tips for simplifying AI for everyone? Share your strategies for making complex ideas click.

Add your perspective
Help others by sharing more (125 characters min.)
160 answers
  • Contributor profile photo
    Contributor profile photo
    Nebojsha Antic 🌟

    Senior Data Analyst & TL @Valtech | Instructor @SMX Academy 🌐Certified Google Professional Cloud Architect & Data Engineer | Microsoft AI Engineer, Fabric Data & Analytics Engineer, Azure Administrator, Data Scientist

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    🧠Use real-world analogies to explain AI concepts in familiar terms. 🎨Visualize ideas with diagrams, flowcharts, or infographics. 💬Avoid technical jargon—use simple language and relatable examples. 📊Demonstrate AI applications through interactive demos or case studies. 🤖Show AI in action with practical examples like recommendation systems. 📝Break complex concepts into step-by-step explanations. 👥Encourage discussions and Q&A to ensure clarity. 🔄Reinforce learning with simple summaries and key takeaways.

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    22
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    Contributor profile photo
    Vikram Verma

    Your Go-To Marketing Ally | Building Communities Where Real Growth Happens | Let’s Learn & Win Together

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    Demystifying Complex AI Concepts Communicating AI ideas to non-technical colleagues doesn't have to be daunting! Relate and Visualize 1. Use analogies: Explain AI with everyday examples. 2. Avoid jargon: Use simple language. 3. Diagrams and demos: Illustrate AI processes. Focus on Practical Applications 1. Highlight business benefits: Explain how AI solves real-world problems. 2. Share success stories: Showcase AI's impact. By using relatable language and practical examples, you'll make complex AI concepts more accessible and engaging.

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    16
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    Pinaki Ranjan Aich, CISA

    GRC & Cybersecurity Strategist | ISO 42001 | AI Risk | Audit-to-Leadership Transition | Author | Ex-Accenture, Aptean

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    🔹 Use Analogies & Real-World Examples – Relate AI concepts to everyday experiences. 🔹 Avoid Jargon – Use simple language and define key terms. 🔹 Visual Aids & Storytelling – Leverage diagrams, infographics, and relatable stories. 🔹 Focus on Business Impact – Explain how AI solves problems and improves outcomes. 🔹 Interactive Demos – Show AI in action through hands-on examples or simulations. 🔹 Encourage Questions – Foster an open discussion for better understanding

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    15
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    Stefan Auerbach

    I educate people on AI via Satirical AI Videos” | Creator of the YouTube Channel, The AI Comedy Lab | 30+ Years Cybersecurity

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    Explaining AI concepts is not easy. There are basic paths you can choose. 1. Use simple analogies: 2. number 1, but tie them together via storytelling. 3 Show them a demo of the most common uses of AI. Typically, simplifying something complicated like AI is hard. However, of the three ideas listed above, the first one seems to work the most. I have used analogies many times, and nine out of ten times, they are understood at a high level. Even then, it's a 30k-foot view of AI. The only way to really understand AI is to jump right into the deep end and watch for sharks. I am curious, though, how others have responded to this question.

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    Dr. Adem Kayar

    Kurucu Ortak ve CEO - MCS Group | Sanayide Dijital Dönüşüm Lideri | Akademik Yazar ve Eğitmen | DDX Dijital Dönüşüm Danışmanı | Konuşmacı

    (edited)
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    AI applications in Industrial Automation Systems and Digital Transformation applications in industry, especially in smart manufacturing processes, are not easy. It is necessary to develop separate solutions for each sector and application in the industry. Recently, it has been seen that AI applications related to energy efficiency and carbon emission reduction have been successfully applied in the industrial sector. The topics to be considered in the industry are as follows: 1- Obtaining the correct data 2- Making the received data meaningful 3- Implementing the correct AI model.

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