ARTICLE
5 concrete use cases for AI and automation that create real business value
5.9.2024 | 3 minute read
Authors
JARNO TOIVONEN
PAIJU KOIVULA
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AI has long been a topic of discussion when it comes to improving individual employee efficiency, but how can AI be leveraged to create real value for business? AI, combined with automation, offers opportunities to enhance efficiency at the entire organizational level. AI acts as the brain of automation, while robotics serves as its hands – together, they complement each other and enable broader business development initiatives.
According to a survey commissioned by the OP group, already half of large Finnish companies are planning to replace work tasks with AI. In this article, we go through 5 concrete applications, how large companies can use AI and automation to make their business more efficient.
Use case 1: Interpretation and processing of documents
AI has long been used in processes where a machine is naturally more efficient than a human and where structured documents such as forms, certificates or passports, or semi-structured documents such as invoices, receipts or order deliveries are processed. With the help of AI, information from the material can be automatically identified and saved for further processing, and missing fields can be validated. Recent developments in artificial intelligence products enable more reliable and faster model training with a smaller amount of training material, combining human annotation for different document types and AI recognition (so-called active learning). In addition, generative AI enables human queries to the material, which produces new information and further improves the reliability of document processing.
Typical applications in companies are AI invoicing, order confirmation processing and timesheet management. Depending on the environment and needs, Sisua has chosen Microsoft Azure ML solution for document processing, which is naturally suited to the MS Office environment and the Microsoft ecosystem, or in more demanding automation cases, Uipath Intelligent Document Processing (IDP) solution. You can read more about the concrete results in Sisua’s implementations in customer stories about Posti’s purchase invoice processing and Kekäle’s financial management automation.
Use case 2: Analysis and automation of unstructured data (such as e-mails)
AI can also be used in processing and analyzing unstructured data, such as interpreting or processing e-mail messages, feedback or tickets. Customer service is an excellent use case in terms of business benefits, as it receives numerous customer messages in different formats, such as free-form texts (sometimes in different languages), emails with attachments, and scanned documents —that previously relied on manual handling. AI combined with automation aim to improve the customer experience, find an answer or solution faster, and at the same time lighten the workload of customer service personnel. Tools for this are provided by e.g. Microsoft Power Platform and UiPath’s Communications Mining. Sisua has already implemented several such automations for its customers, for example for Stark.
Additionally, UiPath’s Communications Mining interprets the tone of feedback, enabling the generation of customer satisfaction metrics and the creation of automated responses, which employees review before sending.
Use case 3: Image recognition and classification
AI is also used in processes that require the recognition and classification of images. AI can be trained to classify vehicles in the insurance industry, for example in crash cases, where AI automatically recognizes and classifies vehicles into the correct category, such as motorcycles, cars or other vehicle types. Classification of images is also widely used in the health care sector as pre-processing to reduce the workload required of an expert.
Sisua has implemented automations based on image recognition to support customer service and HR, for instance for Administer. In addition, Sisua has built an automation that utilizes image recognition, which makes warehouse management more efficient. Image recognition is utilized in calculating an electricity company’s inventory balances. The company’s employees take pictures of the warehouse, after which the artificial intelligence model analyzes the pictures and counts the products in the warehouse. Once the calculation is completed, the automation connects to the company’s ERP system, SAP, and updates the balances.
Use case 4: On-promise solutions with ChatGPT
Gen AI consumer applications such as ChatGPT, or MS Copilot for enterprise use, are already transforming working methods across several industries, including content creation, assisting with programming, and performing personal assistant tasks. For enterprise use, especially when handling sensitive information, solutions are needed where data privacy is guaranteed and the sources (context) are restricted to the company’s own data. This ensures that the results provided by the language model are accurate within the specific context. Sisua has ongoing projects in which on-premise solutions are implemented with the help of generative AI to process confidential materials such as contracts, job applications or health information.
Use case 5: Internal company chatbots
Artificial intelligence can also be utilized by building internal chatbots for companies that enhance and monitor repetitive routines. For example, Sisua has developed an internal chatbot for its customer, which operates the IT department’s ticket processing. When an employee requests a password change or another similar action, the chatbot saves the necessary information for the change and generates a structured result for the RPA automation or API process in the system, in which case the automation takes the change, such as password change, into production. Chatbot validates and handles change requests, improving efficiency and accuracy in ticket processing.
Which industries or functions are particularly profitable for the use of AI?
1) Insurance sector: Insurance sector particularly benefits from AI’s ability to efficiently process and interpret documents and images.
2) Service industry and customer service function: Service industries often handle large amounts of customer feedback or messages, where AI can create significant efficiency.
3) Banks and the financial sector: The financial sector has just as much use for AI, both in terms of customer service and in the processing of various documents or forms. AI can e.g. handle the pre-processing of mortgage applications by deciding whether the application should be directly rejected or forwarded for the employee’s review.
4) Financial administration: AI creates a lot of efficiency in processing invoices in financial administration. It is especially useful in an international context where there are many differences in the variability or appearance of invoices. In these cases, AI is particularly good, while intelligent automation handles the simpler variations.
5) Help desks and other support functions: Help desks and other support functions often receive customer messages in diverse formats, and AI optimizes processing these messages. AI can, for example, categorize messages and forward them to the right people.
6) HR: AI can be utilized in recruitment processes by analyzing CV files. The AI is taught the desired metrics with which it analyzes the applications, after which it creates a table in which the applicants are presented in order according to the desired metrics.
What are the benefits of using AI and automation?
The biggest measurable benefit of AI mostly comes from improved efficiency and productivity. Otherwise, the benefits of artificial intelligence largely adapt to the benefits of process automation, such as fewer errors and better accuracy in processes, increased scalability, data-based decision-making and predictive analytics. In addition, artificial intelligence expands automation opportunities and use cases – together they complement each other and create opportunities for more versatile business development projects.
Benefits of AI
- Increase in productivity
- Time savings
- Faster customer service
- Faster customer service
- More harmonious and structured processes
- Increasing scalability
- Increasing scalability
- Predictive analytics
- End-to-end automations
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