AI lecturer holding a class on text classification

Jul 14, 2025

8 Industries using AI Text Classification

Discover 8 industries that are quickly embracing text classification within their operations to improve operations and growth.

Industries using NLP Text Classification

1) Retail - using customer sentiment to improve customer satisfaction

Across the retail industry, brands are flooded with customer reviews, chat logs and support emails.

This textual data is invaluable to businesses seeking to better understand their customers and to improve their product or service offerings.

AI text classification of reviews is being used not only to flag whether a review is positive or negative, but is also helping to delve deeper into the analytical and contextual meaning of the review. This is often referred to as sentiment analysis.

For example, the reviews can be tagged into comments about product quality, price, delivery and customer service. By doing so, retailers are able to easily identify recurring issues and take corrective action, helping to improve customer satisfaction.

2) Healthcare - Escalating urgent issues using AI triage

Healthcare departments around the world are often overwhelmed with patient enquiries, some more urgent than others.

NLP text classification is being used to review emails, online consultations and patient portals such as the UK’s 111 online to classify phrases into medically relevant categories.

For example, if a patient mentions in an online form that they are experiencing shortness of breath or a tight chest, the AI Text Classification model will be able to automatically detect these as potentially life-threatening issues and to escalate them accordingly. This early identification has a direct impact on patient outcomes, especially for busy healthcare systems where delays could be critical or even fatal.

Beyond triage, text classification is being used within healthcare to review patient feedback, giving healthcare providers a full spectrum of the patient experience. Management teams get actionable insights into service areas that need improvement.

Discover other ways NLP is being utilized to help improve the services of healthcare providers.

3) Legal - Improving legal accessibility

Legal documents are, by nature, not the most accessible to the average layman. The terminology is complex, and the sheer volume of text within contracts, case notes and compliance reports can be overwhelming.

Custom-trained AI text classification models can be deployed to summarize and categorize text into more manageable, bite-sized chunks that the average person can understand.

For the legal team themselves, text classification can help to pinpoint specific areas within documents that require further attention, categorized by important factors such as risk level, deal type and jurisdiction.

Similarity-based systems can compare new contracts against the industry standard and previously approved contracts, which helps to identify any uncommon or missed clauses, reducing the risk of human oversight when writing or signing contracts.

These text classification models can be integrated within a chatbot function which is undoubtedly of great help to legal firms.

4) Finance - Detecting fraud and improving compliance

Financial institutions are inundated with sheer quantities of textual data every day. From transaction notes to customer service chat logs, every word must be analysed as part of a bank-wide fraud detection programme.

AI text classification tools can flag certain language patterns that are commonly associated with fraud, such as overly vague descriptions or inconsistencies within application data.

Many financial institutions require commercial customers to fill out extensive KYC (Know Your Customer) documents, as well as checking for any PEP (Politically Exposed Person) indicators, someone who is entrusted to a prominent public function and thus represents a higher risk for potential involvement in fraud, bribery or corruption.

By automating these compliance checks, financial institutions can stay ahead of fraud at scale and in real time, without overburdening their internal compliance teams.

5) Publishers - Improving article discovery

We’ve all been there - you have just finished reading an interesting article and want to continue reading something related.

Relevant content suggestions are crucial to promoting higher user engagement and search engine visibility. Text classification systems powered by NLP can analyze an article’s tone, topic and potential audience interests, before tagging them accordingly.

With custom functionalities that plug straight into a publisher’s content management system (CMS), these AI tools work on autopilot to improve the internal structure of large article archives.

As a result, content becomes more discoverable, recommendations become more relevant and readers become more content with the content they are consuming.

6) Customer Service- Improving customer complaint triage

Support tickets, chatbots, chat logs and social media are all avenues for customers to connect with a business. Customers are not homogeneous, with each customer having their own preferred method of communication that they expect a response from.

Some will prefer ringing a customer service hotline, others will use chatbots or social media messages. Companies must be able to handle communications through all of these channels, with customers often expecting instant support.

Text classification solutions can be trained to assign messages into specific categories such as billing issues, delivery enquiries or contract cancellations.

Using sentiment analysis, these AI text classification tools can also identify high-priority issues that need to be immediately escalated to human support agents, whereas other customers can be directed towards FAQs or online resources to help with their inquiry.

This approach helps to reduce waiting times, boost customer satisfaction and reduce human support agent workload.

7) Human Resources - Removing inherent bias when reviewing resumes

Recruitment as an industry and a process has always been vulnerable to the inherent biases of the recruiter, whether it be the candidate’s name, education, gender or particular phrases used in the resume.

HR text classification models, such as NetGeist HR, offer a fairer and consistent approach to reviewing resumes and cover letters, helping companies to evaluate applications based purely on skills, experience, talent and relevancy to the role, helping to remove much of the subjectivity that traditionally affects shortlisting.

AI models for recruitment can be trained to classify candidates according to their core competencies, achievements and experience.

The company commissioning the custom AI solution can instruct how important specific factors such as the university a candidate attended or the turn of phrase used are to the shortlisting priorities.

As these AI models can present anonymised shortlists, hiring managers can receive a more diverse, qualified and relevant list of candidates to progress through to the next round of the recruitment process.

8) Tourism and Hospitality - Managing reviews from international travellers

Travel, tourism and hospitality businesses often rely upon online reviews, forming a major part of their marketing efforts but also in guiding the business strategy based on genuine customer feedback.

The problem is, these reviews are collected across various platforms and are often left in the native tongue of the tourist, not necessarily that of the business. Whilst it may be in a different language, this is still valuable feedback that the hospitality businesses will be keen to understand.

AI classification models can identify the language of the review and be trained to provide contextually accurate translations that remain true to the original sentiment of the review.

These translated reviews can then be fed into quantitative analytical tools that provide actionable insights to the management, allowing them to identify key areas for improvement.

Custom Text Classification Models

These 8 industries have benefited from incorporating text classification models into their workflows, helping to improve business efficiency and customer satisfaction.

The key to a successful utilization of text classification for your business is to ensure your solution is tailored to your specific requirements.

Off-the-shelf models are an excellent example of what this technology can offer, but they fall short in offering niche-relevant expertise.

That’s where custom text classification models developed by NetGeist come into play. We create tools that tackle textual challenges by automating, processing, and summarizing information. Let us simplify your textual tasks with a unique solution, tailored specifically just for you.

Reach out today and we’ll promptly get back to you.