Natural Language Processing (NLP) is the branch of artificial intelligence focused on enabling computers to understand, interpret and generate human language. It covers a wide range of tasks, from simple keyword matching through to advanced text generation, and underpins many everyday business tools including spam filters, search engines and AI assistants such as Microsoft Copilot.
How Natural Language Processing works
NLP systems convert human language into a structured form a computer can process, then apply techniques ranging from simple pattern matching through to large language models for more sophisticated understanding and generation. Tasks within NLP include sentiment analysis (is this text positive or negative), entity extraction (identifying names, dates and amounts within text) and text generation. Modern large language models have significantly improved performance across nearly all of these tasks compared to older, more rule-based NLP approaches.
How UK businesses use NLP
- A customer service team uses NLP-based sentiment analysis through AI Builder to automatically flag negative customer feedback for priority review.
- A business uses NLP-powered search across its document library, allowing staff to find relevant content using natural language queries rather than exact keyword matches.
- A finance team uses NLP-based entity extraction to automatically pull supplier names, invoice numbers and amounts from scanned invoices.
- A sales team relies on Microsoft Copilot's NLP capabilities to summarise lengthy email threads into a short briefing before a client call.
How Advantage applies NLP for businesses
Advantage identifies practical opportunities to apply NLP capabilities, often through AI Builder and Microsoft Copilot, to automate document processing, customer communication analysis and other language-based tasks within existing Microsoft Platform deployments.
Frequently Asked Questions
What is the difference between NLP and a large language model?
NLP is the broader field of AI concerned with understanding and processing human language, including tasks like sentiment analysis, translation and entity extraction. Large language models are a specific, more recent type of NLP technology that has dramatically improved performance across most of these tasks, particularly text generation.
Where might a business already be using NLP without realising it?
Spam filters, predictive text, voice assistants, search engines and many customer service chatbots all rely on NLP. Within Microsoft 365, features such as Outlook's smart replies and sentiment analysis in AI Builder are also examples of NLP in everyday use.
Does NLP only work in English?
No. Modern NLP models, particularly large language models, support many languages, though performance and the volume of available training data can vary by language. Most major business AI tools, including Microsoft Copilot, support multiple languages including UK English.
