What is AI?

Artificial Intelligence (AI) refers to the concept and creation of computer system that can carry out tasks traditionally requiring human intelligence. These tasks include things like understanding spoken language, making informed decisions, and recognizing patterns in data.

AI is a broad field that includes several specialized technologies, including:

  • Machine Learning enables systems to learn from data and improve over time without being explicitly programmed.
  • Deep Learning, a subset of machine learning that uses neural networks to model complex patterns and behaviors.
  • Natural Language Processing (NLP), which allows machines to understand, interpret, and respond to human language in a meaningful way.

These technologies and their combination form the foundation of AI and enable computers to perform increasingly sophisticated tasks across various industries.

What is Generative AI?

Generative AI, often referred to as GenAI or GAI, is a branch of artificial intelligence focused on creating original content in response to user prompts. Unlike traditional AI, which analyses data to produce predefined results, generative AI can produce entirely new outputs such as:

Text

  • Articles.
  • Stories.
  • Poems.
  • Software Code.

Images

  • Digital Artwork.
  • Illustrations.
  • Photorealistic visuals.

Music

  • AI-generated compositions.
  • Soundtracks.

Video

  • Deepfakes simulations.
  • Animations and other visuals.

What sets GenAI apart is its ability to go beyond analysis and prediction. It can synthesize new ideas, simulate creativity, and produce content that didn’t previously exist—all based on how the user frames their request.

What is the difference between Traditional and Generative AI

AspectTraditional AIGenerative AI
PurposeAnalyzes data to make predictions or decisionsProduces new and original content based on prompts
OutputDelivers predefined results or classifications Creates text, images, music, and more from scratch
ApproachFollows programmed rules or learns from data patterns Uses advanced models to simulate creativity and innovation
RoleSupports and automates routine tasksEnables new forms of expression and creation
ExampleSiriCopilot, ChatGPT

Can you identify the key difference?

Traditional AI predicts while Generative AI creates.

How AI has evolved over the years and affected the workforce

1. Early AI: Rules and Robots

In the beginning, AI was mostly about machines following rules. It could do simple tasks like sorting data or playing chess—but only if you told it exactly what to do.

2. Smarter AI: Learning from Data

Later, AI started learning from examples. Instead of being told every step, it could figure things out by looking at patterns—like recognizing faces in photos or spotting spam emails.

3. Modern AI: Talking and Writing

Today’s AI (like Copilot and/or ChatGPT) can understand and create human-like language. It can help write emails, summarize documents, answer questions, and even translate text—all by learning from huge amounts of information.

4. Modern AI and the workforce

AI is now helping people work faster and smarter. In universities, it’s used for: Automating routine tasks, supporting communication, organizing information and helping with research and writing.

5. What’s Next?

AI is still growing. It’s becoming more accurate, more helpful, and easier to use. But it still needs human guidance—specially in education, where context and care matter.

Artificial Intelligence is not replacing jobs—it’s changing how we do them. Staff who learn to use AI tools can save time and focus on more meaningful work.