{"id":6254,"date":"2025-07-18T08:54:33","date_gmt":"2025-07-18T08:54:33","guid":{"rendered":"https:\/\/www.goodcore.co.uk\/blog\/?p=6254"},"modified":"2025-08-01T08:25:53","modified_gmt":"2025-08-01T08:25:53","slug":"how-to-choose-an-ai-model","status":"publish","type":"post","link":"https:\/\/www.goodcore.co.uk\/blog\/how-to-choose-an-ai-model\/","title":{"rendered":"How to Choose the Right AI Model for Your Project"},"content":{"rendered":"

You\u2019ve identified a clear use case for AI in your product; maybe it\u2019s smarter search, better user personalisation, or automating tasks. But once you get past the excitement, a tricky question comes up: <\/span>what is the best AI model right now<\/span>, and which AI model should we use?\u00a0<\/span><\/p>\n

With so many options, from simple decision trees to powerful language models like GPT, the choice can feel overwhelming. And choosing wrong can lead to spiralling costs, disappointing performance, and wasted development time.<\/span><\/p>\n

In this post, we\u2019ll share a straightforward guide on <\/span>how to choose the right AI model<\/span> for your software project, so you can move forward confidently and avoid costly missteps.<\/span><\/p>\n

What is an AI model?<\/span><\/h2>\n

An <\/span>artificial intelligence<\/b><\/a> model is a program that has been trained to recognise patterns, make decisions or generate outputs based on data.\u00a0<\/span><\/p>\n

At a technical level, it\u2019s an algorithm that is exposed to large datasets during a training process, learning how to map inputs (like text, images, or numbers) to desired outputs (like categories, predictions, or actions). Once trained, it can apply that \u201clearned\u201d behaviour to new, unseen data in real time.<\/span><\/p>\n

For a deeper dive into this topic, check out our article: <\/i><\/b>What does artificial intelligence mean?<\/i><\/b><\/a><\/p>\n

Different types of AI models<\/span><\/h2>\n

There are many types of AI models, depending on what you want them to do. We\u2019ve outlined the key categories below:<\/span><\/p>\n

Supervised learning models<\/span><\/h3>\n

Supervised learning is one of the most common types of AI modelling. It\u2019s powerful, relatively straightforward, and highly effective when you have the right kind of data.<\/span><\/p>\n

Supervised learning models learn from labelled data. That means you provide the model with input examples and the correct answers.\u00a0<\/span><\/p>\n

For instance, if you’re building a model to detect spam emails, you\u2019d train it on a dataset where each email is already marked as \u201cspam\u201d or \u201cnot spam.\u201d The model studies the patterns in that data, learns the relationships between inputs and outputs, and eventually becomes capable of making predictions on new, unlabeled inputs.<\/span><\/p>\n

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Supervised learning is used for two main tasks:<\/span><\/p>\n