Let’s take a moment to understand what Artificial Intelligence is at its most basic level.
AI is a field in Computer Science focused on creating systems that can perform tasks that would typically require human intelligence. These tasks include:
- Understanding language — Natural Language Processing (NLP)
- Recognizing patterns — such as in images, sounds, or data
- Learning from experience — Machine Learning
- Making decisions — planning and problem-solving
- Interacting with the environment — robotics
In other words, AI is about building systems that can think and act intelligently. Over the past five years, we’ve seen AI become increasingly mainstream, a shift driven largely by Generative AI, which surged in popularity when OpenAI introduced ChatGPT back in Nov 2022.
Generative AI (GenAI), a subset of artificial intelligence, refers to AI systems that can create content based on a prompt or input, think of how ChatGPT generates responses to your question. It can also interpret data and produce entirely new content, such as text, images, music, speech, etc.
AI is being adopted across many industries, and we’re already seeing productivity gains in a wide range of fields. Here are some common examples:
Everyday Applications
- Virtual assistants (e.g., Siri, Alexa, Google Assistant)
- Search engines and recommendation systems (e.g., Google Search, YouTube, Netflix)
- Spam filters and autocorrect in email and messaging
- Smart home devices (e.g., thermostats, lighting systems)
Business and Productivity
- Customer support: AI chatbots, automated ticketing (e.g., Zendesk bots)
- Sales & marketing: Lead scoring, personalized ads, email generation
- Document processing: Auto-summarization, data extraction from PDFs
- Meeting assistants: AI notetakers like Otter.ai or Fireflies
Healthcare
- Medical imaging analysis (e.g., detecting cancer in X-rays or MRIs)
- Drug discovery and research
- Virtual health assistants and symptom checkers
- Predictive analytics for patient outcomes
Finance
- Fraud detection
- Algorithmic trading
- Credit scoring and risk assessment
- Customer service automation in banking apps
Manufacturing and Industry
- Predictive maintenance (sensors detect failure risk)
- Quality control using computer vision
- Robotics and automation in factories
Education
- Personalized learning platforms
- Automated grading
- Tutoring bots
- Language learning apps (e.g., Duolingo’s AI)
Creative Work
- Code generation (e.g., GitHub Copilot)
- Writing and content creation (e.g., blogs, scripts, books)
- Image and video generation (e.g., Midjourney, DALL·E)
- Music composition and audio editing
AI’s influence is everywhere and you don’t need to be an IT professional to use it. Many people already interact with AI every day without even realizing it.