Questions to Think About:

• Where do we see AI in everyday life — even when we don’t realise it?

• Why are AI systems becoming so widely used?
  ✅ automates repetitive tasks
  ✅ processes massive amounts of data

• How does AI affect industries like healthcare, transport, and education?

• What ethical issues can AI raise?
  ✅ bias in decision-making
  ✅ job displacement

• What might AI look like in the future — and who decides how it’s used?

AI is most commonly used today to replace humans in repetitive or menial jobs, allowing people to focus on higher-level tasks that require empathy, creativity, or judgment.

Real-world examples of AI in use:

• Customer service chatbots answer questions instantly, reducing wait times and the need for human staff.

• Complaint-handling AI analyses customer feedback to identify patterns and suggest improvements more quickly than a person could.

• Healthcare AI can scan patient records and medical images to assist doctors with faster diagnosis and treatment.

• Legal AI helps lawyers by scanning large volumes of legal documents and pulling out key information.

• Self-driving cars use AI to process sensor data and make real-time decisions about braking, turning, and detecting obstacles.

AI can also reduce risk in dangerous environments (e.g. mining, deep-sea exploration), and while the setup cost may be high, businesses often benefit from long-term savings — AI doesn't need wages or breaks.

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Creating and deploying AI systems takes a skilled team and strong infrastructure. It's not as simple as downloading software — it involves data, training, and ongoing monitoring.

“AI implementation requires considerable investment in the team. The team typically consists of data engineers, data scientists & domain experts to build good mathematical algorithms. These algorithms are translated into software solutions by product development teams.” – talentica.com

Key Facts (spiceworks.com):

• 91% of top companies are actively investing in AI (NewVantage, 2022).

• High-performing companies say AI contributes to most of their profits (McKinsey).

• A shift is happening toward holistic AI platforms that solve multiple business problems, rather than using one tool at a time (Forbes, 2022).
  
  

To implement AI successfully, organisations need access to quality data, clear goals, and strong collaboration between human experts and tech teams.

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