14 Sep AI for business: what are training data use cases?

In recent years the artificial intelligence market has recorded significant growth in various business sectors. It’s actually estimated that it will even double its value between 2020 and 2024. 

Another market strictly related to AI development is also finding room in this situation — the market of data providers. Comprised for the most part of specialist agencies and start-ups, this sector deals with supplying various businesses with the services necessary for data training in order to develop customised AI systems. But what are training data use cases?

Specifically, data providers manage data collection activities but also dedicate themselves to data validation and annotation, thus offering customers accurate and high-quality data sets that can be used for particular projects.

What is data training in AI?

Machine learning systems are based on data. Through specific training activities, these data are processed and utilised to train machines in performing typical human tasks.

Yet in order for this process to function properly and return a good result, it’s important that the data used for machine training are abundant and of good quality and that they’re processed with a human-in-the-loop approach. Only in this way, by starting out with an appropriate behavioural model, is it possible to develop models for AI that are increasingly accurate and reliable.

What are AI training data use cases?

Data training is a process that often requires time and many resources. This is why agencies are putting their trust in data provider services more and more; these agencies take care of providing specific sets of AI training data.

The data are then used to develop artificial intelligence projects, customised for particular business needs. So, which sectors can make use of training data sets?

IT and Big Tech

The IT and Big Tech sectors have always ranked in the top position regarding the use of training data. Data are mainly used in this area for the development of automated systems and highly customised technological products, which usually require data sets with rather specific requirements.

The data in this field can be utilised to develop:

• AI-powered personal assistants
• cybersecurity systems to fight online threats
• smart security models associated with computer vision
• optimisation systems for machine learning projects and data science

Finance

In this field, there truly are many repetitive tasks that have been automated over time to produce savings in terms of time scales and money. This has made it possible to leave the management of the set of the most complex problems concerning the direct relationship with customers in the hands of human experts.

In the financial sector, the data sets can be used for:

• the development of robo-advisers capable of monitoring personal finances and providing consumer advice
• systems for fraud detection and calculation of insurance risk
• automatic models of credit scoring and analysis of investments
• automatic billing systems for customers
• the development of software for managing customer requests and analysing the best financial solutions

Industry and the primary sector

In industry and the primary sector, data can be utilised to automatically manage various production processes. Through the use of complex algorithms, it’s possible, for example, to develop precise prediction systems as well as inventory and optimisation systems for production processes.

The data can be used for:

• developing automatic and robotic production systems
• optimising production lines for industry by means of automatic systems for quality control, check-out and inventory
• implementing models of facial and voice recognition for an end product
• managing the scheduling of maintenance in industry and analysing production processes

Life sciences

In the healthcare field, data can be utilised to develop automatic systems for checking patients’ health, but also for research and accurate diagnosis of certain diseases. Quite often, the development of these systems requires very specific training activities and the selection of particular data sets.

The data in this field can be utilised for:

• automatic management of remote health check-ups and prevention
• improvement of systems for image recognition
• making the check-up phases of triage faster
• improving systems for diagnosing and analysing patients remotely

E-commerce

This sector is particularly suited to using automatic systems based on artificial intelligence models, considering that there are numerous repetitive activities that can be managed by these systems. Data sets can be used to develop services for customer care, to improve customer experience and to manage products.

Therefore, the data can be used for:

• creating customised chatbots and digital assistants
• developing sentiment analysis models to examine customer feedback
• developing and managing recommendations for personalised purchases
• implementing voice recognition systems and voice or visual authentication systems

Tourism

In the tourism industry, data are used to develop systems capable of improving the customer travel experience and quicken some processes that can be easily automated in the field of transport. Data can be used for developing chatbots and virtual assistants capable of helping tourists. But also to implement facial recognition systems that can speed up the checking documents and tickets in tourist facilities.

Communication and entertainment

In the field of communication, the data are mainly used to develop systems for the fact-checking of news and to manage conversations and information on social media and websites. In particular, the data can be employed in:

• creating and automatic managing of content
• recording of user feedback related to content
• researching and selecting news items in the field of journalism
• developing of optimising systems for online research

Education and recruiting

Data can be also be used in the field of education and recruiting, offering the opportunity to develop platforms and automatic systems capable of automating several specific procedures. In these areas, the use of data makes it possible to:

• provide students with virtual and automatic assistance they can access from any place
• develop virtual tutors capable of supporting smart learning software and personalised learning
• implement automatic systems for the management of recruiting processes
• develop models for the swift and automated scanning of CVs and other documents

The use of training data and the development of various possible artificial intelligence systems still leave ample space for creativity and innovation. It’s exactly for this reason that in time AI will likely find an increasingly broader field of application in various business sectors.

But in the meantime, if you have any innovative ideas in mind and want to develop them with us, please tell us about your project!