Beyond ChatGPT: What is AI? And What Are the Use Cases for Your Organisation?

It’s not just a chatbot, and it’s not quite Skynet… yet. Artificial intelligence (AI) is an evolving field, and to get the most from it you’ll need to understand both its capabilities and how they can be applied most effectively to benefit your organisation, its users, its clients, and you yourself. In this blog post we’ll explain what AI is and take you through six potential use cases that you may want to explore for your organisation.

Artificial intelligence, or AI, has never been far from the public conscience for well over half a century now. From the HAL computer in Stanley Kubrick’s 2001: A Space Odyssey in 1968, through Skynet in the Terminator franchise, to today’s swathes of action and adventure franchises, AI has been a touchpoint in popular culture for some time. What united all these depictions of AI, though, was a sense that AI was a tool for some far-off future – not a reality today.

That all changed in 2022 with the launch of ChatGPT, a large language model-based chatbot that captured the public’s imagination like little else that had come before. Suddenly AI became very real for a great many people, and the opportunities it presents – along with the potential risks to peoples’ careers – became abundantly clear.

As we step into 2024, organisations should be exploring how they can deploy AI to greatest effect. Because the truth is AI is far more than just ChatGPT – it’s a whole universe of potential, and it’s constantly evolving.

In this blog post we’ll go beyond ChatGPT to explain what AI is – and take you through six of its potential use cases for organisations just like yours.

What is AI?

For many people AI has become shorthand for anything computer-generated. The truth is a bit more nuanced than that. To understand what AI actually is, we need to go back to mathematician and scientist Alan Turing’s 1950 paper Computing Machinery and Intelligence. Turing explored the question ‘can machines think?’ and created the famous Turing Test in which a human would attempt to distinguish between written responses from a human and from a computer.

From these beginnings scientists and researchers evolved our understanding of AI, reaching a consensus around AI being a field that combines computer science with data to enable us to resolve problems.

Going back to ChatGPT, the tool ultimately exists to solve problems – answering the questions we as users pose it. And as we’ll explore now, AI’s ability to process large datasets to resolve problems means it can be applied to a large number of use cases by organisations today.

Conversational AI

Conversational AI uses machine learning and natural language processing to provide services like chatbots and voice assistants that users can interact with. Chatbots are great for applications including online customer support, autocomplete functionality in applications like Microsoft Word, and accessibility through things like language translation and dictation from speech to text and vice versa. It can bring obvious cost efficiency and customer service improvements, as it enables organisations to prioritise their peoples’ time on resolving more complex issues when leveraging conversational AI to manage straightforward queries.

Process Automation

Process automation is one of the most popular uses of AI today, enabling organisations to automate tasks like back-office administration and financial activities. As with conversational AI, process automation can make a tangible impact on organisations’ cost and process efficiencies by enabling skilled users to take focus away from straightforward business as usual activities and towards more complex problem solving that better leverages their skills and experience.

Predictive Analysis to Support Decision Making

Conversely, AI’s ability to process huge amounts of data to arrive at evidenced outcomes can bring significant benefits to organisations undertaking strategic planning. By gaining insights that humans couldn’t possibly replicate, predictive analysis can help organisations make better decisions based on tangible evidence that can support in implementing strategies to enhance performance and minimise risk.

Recruitment

Recruitment is a very time and resource-intensive process, and one that is crucial to any organisation’s success. AI-driven technology has uses throughout the recruitment process, from candidate sourcing, through candidate screening, talent assessment, interviews, all the way to onboarding. By using AI in recruitment organisations can realise efficiency benefits, overcome issues around bias, enhance the experiences of candidates, and improve the quality of hiring.

User Productivity

There are already myriad AI tools on the market that increase user productivity by completing straightforward, mundane tasks – allowing people to focus time and energy on more creative tasks. Microsoft 365 Copilot spans the Microsoft 365 suite to unleash creativity, unlock productivity and uplevel skills through apps people use every day including Word, PowerPoint, Excel, and Teams. We provided a primer on Microsoft Copilot at our most recent Cyber University seminar. Enrol for the next session here.

IT Operations

AI for IT operations, sometimes referred to as AIOps, collects data from across an organisation’s IT infrastructure and identifies performance and availability issues. It can then diagnose root causes, alerting IT to remediate or even resolving the issues automatically. AIOps can bring a number of benefits to organisations, including faster resolution times, lower operating costs, and enhanced visibility.

Use Cases for AI in Organisations Today

As we’ve demonstrated in this blog post, there’s a lot more to AI than ChatGPT. In fact, there are multiple uses cases for AI in organisations today. However, to get the most from AI your organisation must ensure it has the stable foundations of usable, optimised data – AI is only ever as good as the data it has to work with. Speak to one of our experts about how your organisation can take steps towards building AI into its go-forward strategy.