Artificial Intelligence (AI) has been a hot topic of conversation for the last couple of years, with programmes like ChatGPT hitting the headlines to mixed reviews. Whilst there’s no denying that AI can speed up certain processes, there’s no replacing human creativity for certain tasks.
However, when it comes to decision making, AI is a fantastic tool. It can gather and analyse data on a wide scale much faster than a human, and can help spot trends that might have otherwise been overlooked. This makes it a valuable resource for businesses who are looking to grow, or even just make sure that they’re putting their money and effort in the right places.
In this post, we explore the different types of AI which are relevant for decision making.
Machine learning
Machine learning is intended to replicate the human thinking process, approaching tasks like a human would with the help of algorithms. The accuracy of this type of AI improves over time as it learns – one example of it in practice is when you get recommendations for things you may like on social media, or on streaming platforms. The programmes suggested might not be right for you at first, but once you’ve used the platform for a while, they become highly accurate.
In business, it can be used to make predictions about trends, as well as uncovering key insights in large datasets. As this sector grows, so will the accuracy of its application in everyday business, so it’s well worth investigating how it might be able to support your company in the future.
Deep learning
A further evolution of machine learning, this type of AI is able to identify images, text and sounds on its own – there’s no need for human interaction. Deep learning AI is designed to recognize complex patterns on its own, meaning that it can spot opportunities for your business that you might not have even considered or noticed. The programme is based on neural networks which are inspired by the human brain, making it incredibly sophisticated.
The technology can be particularly helpful when it comes to optimising complex systems, such as supply chains, by predicting future demand and providing recommendations to refine operations. In addition, deep learning AI can be applied in fields such as finance, healthcare, and law, where precise decision making is critical.
Causal AI
An emerging player in the AI sector, causal AI is a new model which aims to give wider information about datasets – including cause and effect, rather than just predicting what will come next. This could be crucial for decision makers, as it will allow businesses to understand why certain trends are happening, and decide if the same factors are likely to be relevant going forward.
Experts suggest that users will be able to ask causal AI models questions about why it came to a certain output. Importantly, in an era where AI ethics are beginning to be discussed, causal models often have guidelines in place for accountability, fairness and bias.
Using technology to support growth
With a relatively unregulated AI market at the moment, it’s natural to feel a little cautious or unsure about this new technology. Whilst it can’t replace human creativity, it can certainly support data insights, which can then be combined with human input to support business growth.
