AI stands for “artificial intelligence”. In business computing it normally means using algorithms that have been generated by a computer, rather than programmed by a human.

Generating and applying these algorithms can be very resource-intensive – which is why many desktop applications rely on cloud services for their AI functions. However, AI-accelerator chips are now being built into computers, phones and graphics cards, making local AI increasingly viable.

What are the applications of AI?

AI works out rules by examining and cross-referencing data. It can process enormous quantities of information, and it has no preconceptions about what it expects to find. This means it can identify connections and trends that a developer might never think to look for – or ones that would be too subtle and obscure for an analyst to spot.

While AI is a powerful tool for analysing historical data, it can also work in real-time. For example, an AI system might track ongoing sales figures to spot emerging trends. IT administrators can use AI to monitor system logs and activity, and get a warning when unusual behaviour is detected.

What is generative AI?

AI systems aren’t limited to purely analysing data – they can also use it as a model to create new output. One popular use of generative AI is for first-level customer support. An AI chatbot can be “trained” on information from previous support calls, and use this to generate appropriate answers to new queries.

A similar principle can be applied in the visual realm. Image- and video-editing software can use AI to enhance a scene far beyond its native resolution, adding natural-looking detail based on real-life images. Entire new scenes can even be created, for marketing or visualisation purposes.

Finally, there’s the most famous example of generative AI: ChatGPT. This almost certainly needs no introduction, but we cover it in more depth in our separate ChatGPT explainer.

What’s next for AI?

As AI services become more widely available, the technology has potential to transform almost every area of business.

For example, it’s anticipated that AI will soon be able to perform knowledge discovery, digesting a folder full of documents and presenting a summary of significant facts. In product development, AI can be used to find the most efficient designs and manufacturing methods. In healthcare, AI can be used to find new drugs and treatments far more quickly than has historically been possible.

Perhaps the biggest revolution will be in automation. Interactive AI systems will take over everyday tasks in fields ranging from bookkeeping to communications, research and customer services. Combining AI with robotics will transform industries including agriculture, transportation, manufacturing and security.

What are the limitations of AI?

In the long run, the widespread replacement of humans with AI systems may create challenges for society. Right now the risks are more operational: since an AI system effectively makes decisions for itself, the owner can’t be certain it will behave appropriately or reliably in all circumstances.

And if something does go wrong, difficult questions arise as to who is accountable, and how to remedy the situation. These are issues that every firm needs to consider before placing its trust in AI solutions.


  • AI uses machine-generated algorithms, rather than ones defined by a programmer. 
  • AI-powered data analysis can find insights that traditional methods would miss. 
  • AI-powered data analysis can find insights that traditional methods would miss. 
  • Since AI doesn’t follow a known set of instructions, operators need to be alert to possible issues of reliability and accountability. 

If you enjoyed this explainer, we recommend you have a read through our “What is ChatGPT?” explainer, where we cover some of the basics of how ChatGPT works. In addition, here’s an article if you need help understanding how your business can take advantage of GPT-3.

Avatar photo
Darien Graham-Smith

Darien is one of the UK's most knowledgeable technical journalists. You will find him in PC Pro magazine, writing reviews for a variety of sites and on guitar with his band The Red Queens. His explainer articles help TechFinitive's audience understand how technology works.