Intelligent Automation Tools: Key Features & Top Vendors 
RPA and intelligent automation adoption is already high in the enterprise: More than 90% of C-level executives report that some level of intelligent automation already exists within their organizations. On a broader level, the global intelligent automation market is expected to reach $8 billion by 2023.1
Due to the abundance of choice, it could be challenging to distinguish between the different types of process automation tools and select the right one. In this article, we’ll review eight features that intelligent automation tools provide and explore which tools provide them for end-to-end process automation.
8 key capabilities of intelligent automation tools
Artificial intelligence (AI) capabilities
1. Natural language processing (NLP)
NLP is a branch of artificial intelligence that deals with the understanding and manipulation of human language in text or voice form. By leveraging NLP algorithms, intelligent automation tools can:
- Read and interpret unstructured data coming from various sources such as emails, social media, customer service conversations, or invoices,
- Understand the context of the document and extract relevant information from them,
- Classify, summarize, or validate extracted information.
2. Optical character recognition (OCR) and intelligent document processing (IDP)
Optical Character Recognition (OCR) is a technology that allows computers to read text from images. There are OCR tools in the market since the 70s but traditional OCR is limited in its ability to accurately recognize text, particularly in handwritten or poorly scanned documents.
IDP, or intelligent document processing, is a newer technology that uses OCR and artificial intelligence methods such as NLP and computer vision to process documents. IDP systems are designed to:
- Understand the structure of a non-machine-readable document and the meaning of its content,
- Reduce noise in the documents,
- Accurately recognize handwritten or poorly printed documents.
These features allow intelligent automation tools to convert unstructured documents such as images or PDFs to a machine-readable format and extract information from them.
3. Conversational AI
Conversational AI and chatbots have become increasingly popular tools for businesses as nearly 80% of CEOs have changed or want to change the way they manage client engagement using conversational AI technologies. In addition to their use cases in customer services, intelligent automation tools with conversational AI capabilities can improve the employee experience by making it easier for employees to access information and complete tasks.
For example, an intelligent bot can be used to answer common questions that employees have about the company’s policies. The chatbot can then direct the employee to the appropriate resource, or even complete the task on the employee’s behalf. This can free up employees’ time so that they can focus on more important tasks.
Process intelligence capabilities
Check out our comprehensive market guide for process intelligence tools.
4. Process mining
As businesses continue to strive for process optimization, process mining has emerged as a valuable tool for understanding and improving processes. Process mining uses real-time data and incident records to:
- Understand the as-is state of existing business processes rather than the ideal ones,
- Identify process bottlenecks and inefficiencies,
- Present process improvement opportunities.
By combining process mining with RPA, intelligent automation tools allow businesses not only to identify process improvements but also automate them. Using process mining in conjunction with RPA can increase the business value by 40% while reducing RPA implementation time by 50% and RPA project risk by 60%.
5. Task mining
Task mining is another process intelligence method that allows organizations to understand how they perform their tasks through user interaction data. While process mining focuses on how processes are handled, task mining focuses on specific steps or tasks within a process.
Since they are closely related technologies, most process mining solutions also provide task mining capabilities. For example, if process mining reveals that a particular process is taking longer than necessary, task mining can be used to pinpoint which steps in the process are taking up the most time.
Intelligent automation tools with task mining capabilities can allow businesses to understand how users interact with process applications so that intelligent bots can be configured to automate these tasks. This approach can improve process efficiency and effectiveness by reducing process variation and eliminating the need for manual intervention.
6. Digital twin of an organization (DTO)
A digital twin of an organization (DTO) is a comprehensive, digital model that captures all the data, processes, and interactions within an organization. A DTO provides real-time visibility over business processes and assets as it:
- Analyze individual processes and interactions between them,
- Identify inefficiencies,
- Run simulations about the outcomes of intended changes.
A DTO can be used in conjunction with process mining and task mining to identify opportunities for intelligent automation. For more, check out our article on how DTOs and process mining complements each other.
7. Robotic process automation (RPA)
Robotic process automation (RPA) is the core technology of intelligent automation tools. RPA tools are on the market since the early 2000s and traditional RPA tools are based on screen scraping to create bots that can interact with GUI elements to complete repetitive, well-defined, and rules-based tasks.
Intelligent automation integrates RPA with AI and other capabilities mentioned in this article to:
- Automate complex tasks with unstructured information,
- Handle exceptions,
- Make data-driven decisions.
Most leading RPA vendors provide either built-in cognitive capabilities or enable developers to add these capabilities to create intelligent bots. Feel free to check our article on the difference between intelligent automation and RPA for more information.
An integration platform as a service (iPaaS) provides tools, such as connectors, adaptors, APIs, etc., to enable different software applications to share data and connect with each other. For example, through APIs provided by an iPaaS, an e-commerce website can connect with a CRM system and create new records or retrieve customer information.
Intelligent automation tools with API-based automation capabilities can automate tasks that require data from multiple software applications including modern cloud software as well as legacy applications. Feel free to check our article on RPA and APIs and how you use them together.
What are other criteria when selecting an intelligent automation tool?
Since intelligent automation is built upon RPA and intelligent automation tools are provided by RPA vendors, the process of selecting an intelligent automation tool is similar to selecting an RPA tool. We have a comprehensive guide on how to choose an RPA tool, feel free to read it.
Some other criteria to consider when selecting an intelligent automation tool include:
- Programming options: There are 4 main types of programming intelligent automation bots: code-based, low-code/no-code, recording-based, and self-learning bots. Feel free to check our article on RPA programming options to learn more.
- Attended vs. unattended bots: Attended bots, also called robotic desktop automation (RDA) or human-in-the-loop automation, reside on the user’s machine and are triggered by them to complete tasks. Unattended bots complete tasks autonomously in the background. Most intelligent automation vendors enable users to create both types of bots. Check our article on attended vs unattended automation for more.
- Pricing: Pricing models of intelligent automation vendors can be complex and lack transparency. Read our article on RPA pricing to learn more about the pricing models of different vendors.
For screening, we’ve considered:
- Review and rating data: We’ve aggregated review and rating data from public sources for the RPA and intelligent automation market
- Number of employees: Companies with 300+ employees as per LinkedIn, since the number of employees is highly correlated with revenues
According to these criteria, the top players in the intelligent automation market are:
- IBM Cloud Pak for Business Automation
- UiPath Business Automation Platform
- Automation Anywhere Automation 360
- Microsoft Power Automate
- SS&C Blue Prism Cloud
- Pegasystems Pega Platform
- WorkFusion Enterprise
Note: We might have missed some intelligent automation vendors with relevant capabilities. In that case, please let us know, and we will add them to our research.
Which vendors provide these capabilities?
According to vendors’ claims, three of the intelligent automation features that we discussed above are provided by all seven vendors, so we can refer to them as core intelligent automation capabilities:
- Robotic process automation (RPA)
- Natural language processing (NLP)
- Optical character recognition (OCR) and intelligent document processing (IDP)
These three features allow organizations to automate document processing, connect enterprise applications through UI-based automation and migrate data between them.
The other five features are not provided by all vendors, so these are distinctive intelligent automation capabilities:
- Conversational AI and chatbot
- Process mining
- Task mining
- Digital twin of an organization (DTO)
- API-based automation (iPaaS)
For more on intelligent automation
- Top 25 Use Cases / Examples of Intelligent Automation
- 5 Ways Intelligent Automation Consulting Adds Value to Business
- RPA vs Intelligent Automation: Which is the Right Tool for You?
- Intelligent Automation & Hyperautomation: What’s the difference?
You can also check our data-driven list of intelligent automation solutions. If you need help in choosing an intelligent automation solution, we can help:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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