Intelligent automation is a new type of automation that combines RPA technology with AI capabilities, giving businesses an advantage over traditional rule-based RPA automation. In recent times, 40% of companies have invested in Intelligent Automation.

Software robots with semantic capabilities are an important component of AI-powered automation, and we will likely see increased investments in this area in the next few years. Semantic automation can assist employees in repetitive and semi-technical tasks. This article will help you understand semantic automation, its importance, and how it can be used.

What is semantic automation?

Semantic analysis refers to the process of deducing meaning and intent from text. Semantic automation integrates AI-powered semantic analysis into automation solutions like RPA or intelligent automation. Software bots, also known as software automation, are possible thanks to this. 

What is the importance of semantic automation?

Businesses embrace traditional automation solutions like RPA in conjunction with cognitive and intelligent automation technologies. Many organizations that implement and scale RPA are also using cognitive automation.

Software robots can use semantic automation to understand human language and process information. This allows bots to understand:

• The differences between unstructured documents.
• What information is needed to enable users to work with various applications with inconsistent user interfaces.
• Domain-specific terms and language

Using Semantic Automation for:

Document processing

Extracting data from documents is difficult due to many types of documents, such as reports or invoices. Even the same kind of document can come in many formats. The process can be further complicated by blurred images, blurred text, or different handwriting.

Bots with a semantic understanding can analyze unstructured data from documents of different layouts or formats and improve data extraction accuracy.

Chatbots

Computers cannot have human-like conversations. Natural language can be irregular and require intuitive knowledge that is based on the human experience. Informal languages have many irregularities, such as missing punctuation, abbreviations, and typos, making chatbots sometimes fail to understand the user's needs.

Bots with semantic understanding and domain-specific language knowledge can understand the context and use common sense and reasoning when answering queries.

Semantic automation is emerging as a new technology allowing a better understanding of human language, paving the road to more possibilities for business applications in the future.

Contact us if you need help in starting your automation journey.