Post Date: December 3, 2025

How AI Helps Us Save Hours Every Week and How You Can Too

Have you ever wondered how AI and LLM can streamline your daily tasks and boost productivity?

Does your head spin when you hear LLM and AI?

These acronyms may seem intimidating at first, but we can break them down into simple concepts.

You probably already know AI stands for artificial intelligence, which is the ability of machines to perform tasks like learning, problem-solving and decision-making.

AI has been around for years — think video games, social media algorithms and digital assistants — but it’s seeing a resurgence because of a certain type known as LLM, or large language model.

LLM is an AI model that can understand human writing, allowing it to respond in a human-like manner.

Copilot, ChatGPT and Gemini are chatbots that all use LLM models to understand your prompts and generate responses.

And while these chatbots are fun to use in our personal lives to get restaurant recommendations or create a song about your pet dog, organizations use them to increase productivity and solve problems for their clients more efficiently.

At Hungerford Technology, we use an LLM and AI to categorize and improve the intake process for support tickets and chats we receive from our clients. So, what’s the process, how does it help us solve tickets faster and why should you care? Let’s dive in!

AI Automatically Categorizes Tickets

When a client submits a ticket, we use an LLM to analyze the content of the message. Based on the written message, it will decide how the ticket should be categorized, whether it’s an email issue, a network issue or something else.

Then, an AI model automatically applies the appropriate issue types to the ticket.

The same goes for clients who start a chat. Our chatbot will ask them a few preliminary questions to get more context about their issue, such as, “How many people are affected?” and “Is there an error message?” It will then categorize the ticket appropriately based on their responses.

No one likes busy work, so free up your employees to handle more meaningful and creative tasks.

Of course, we still have a human technician scan the ticket to ensure the right categories were applied, but it saves us from manually adding ticket types and asking contextual questions for every ticket. It might only seem like a couple of minutes saved, but that’s a couple of minutes multiplied by 50 to 70 tickets per day, which adds up to hours over a month.

With the ticket types automatically applied, we can assign the ticket to the right technician to solve the issue faster and more efficiently.

How Other Organizations Can Use This Technology

While ticket categorization is how we utilize this technology, there are several ways other organizations can improve their productivity by using LLMs and AI.

Retail: Retail organizations can automate stock levels by automatically placing orders when stocks are low, to avoid stockouts, and updating inventory records in real time.
All organizations: Businesses can use a chatbot on their websites that asks visitors what they are looking for and directs them to the corresponding page based on the response, improving the user experience.
Financial: Banks can automate the processing of loan applications by approving or rejecting them based on predefined criteria, speeding up the process and reducing human errors.
Health care: Health care organizations can manage patient records by automatically updating patient information or scheduling appointments, allowing doctors and nurses to focus on patient care instead of administrative tasks.

It should be noted there’s an added cost to implement this kind of technology. For us, it adds up to about $8 per month. It’s minuscule and shouldn’t dissuade you, as the amount of time it saves vastly outweighs the cost.