Guide to level up intelligent automation technology skills

How to Level Up Your Intelligent Automation Technology Skills

As a business technology leader, you understand that you must be vigilant in keeping up with the latest technologies to stay competitive. The newest buzzword in digital transformation is intelligent automation, but it is no slight, flash-in-the-pan trend. By 2024, Gartner predicts that by combining intelligent automation with redesigned operational processes, organizations will reduce operating costs by 30 percent!


The Basics

intelligent automation is a disciplined approach to automating as many processes in your organization as possible, including business practices, customer service, and IT. It involves using digital tools, technologies, and platforms to identify, vet, and automate your organization’s best practices. These digital tools utilize user interfaces or applications to enable rapid, virtual integration between systems and processes.

Ideal basic candidates for intelligent automation are repetitive, defined tasks performed by many people at scale and error-prone manual processes. Those processes can include claims handling, customer onboarding, loan writing to marketing, order management, accounts payable, and processing documents. No matter how annoying, tasks that happen only once in a while are not good candidates for intelligent automation but may be suitable for robotic desktop automation (RDA) which operate as personal assistant macros.

There’s more to Hyperautomation or Intelligent Automation

Hyperautomation or intelligent automation goes beyond standard automation to include artificial intelligence, natural language processing (NLP), conversational UX, and advanced machine learning.

Hyperautomation utilizes digital workers, chatbots, APIs, and advanced algorithms to extend beyond basic automation. This allows systems to learn, track and improve the functions and results of automation processes. In layman’s terms, hyperautomated systems have the car keys to drive a substantial amount of business operations. However, this doesn’t mean humans are removed from the equation.


There are several critical skills your team must possess for automated processes to run smoothly. The human employee will be responsible for troubleshooting any issue beyond the machine’s control. Human employees will need subject-specific knowledge of machine intelligence processes and fields and strong problem-solving and communication skills for personal and team success.


With AI involved in most aspects of intelligent automation, human employees should have an excellent grasp of various programming languages. The most common AI languages include Java, Python, Prolog, LISP, and C++.

As a general-purpose, high-level programming language, it’s almost natural that Python has grown into is the most used language in Machine Learning, with specific frameworks for AI. And with Java being the prevalent language in app development, it too is a must.

C++ is known for its flexibility, Lisp for its importance in natural languages, and Prolog as creating artificial intelligence. R is another good language to learn due to its number-crunching abilities for statistical models and complex formulas.


Your team will ultimately be responsible for all your automated processes’ performance, functionality, and consistency. They will be the overseers of the backbone of your business. As such, they will need to track and control software changes, establish baselines, configure your critical systems, analyze issues, and verify final configurations.

Staff should be comfortable with creating and managing complex databases. They need to have an analytical mind, heightened attention to detail, and enjoy a structured work environment.


IT personnel working within AI and other advanced learning automation processes should possess the talent for writing new, unique scripts and carrying through with all aspects of script implementation and management.

This will involve monitoring scripts for performance, troubleshooting issues, and applying scripts to different automation scenarios. Staff should test and track scripts throughout the environment and down to the endpoints.

Attention must also continually focus on updating and modifying scripts, performance reporting and analytics, and following through with the proper documentation throughout the life cycle of the script.


Natural Language Processing is how intelligent automation tools interact via the spoken word with humans. NLP uses artificial intelligence to adequately understand human language, sentiment, and verbal cues to communicate with humans in multiple human languages.

Your team will need a strong understanding of deep learning models, sequential modeling, chatbots, and autoprocessing to implement practical solutions for automated communication.

CERTIFICATIONS for Intelligent Automation Technology Skills

As with any industry utilizing evolving technology, your team must maintain current and pursue new certifications. For intelligent automation, necessary certifications include the fields of programming languages, machine learning, and building ML models, artificial intelligence, and data sciences. Certifications bolster the importance of the employee and your organization’s skill set and reputation. Some of the technology platforms offer their own training and certification programs. You can also work with a services firm like WonderBotz to get guidance on training and certifications.

In Need of Hyperautomation Expertise?

WonderBotz is a global professional services firm that’s led world-class system integration and intelligent automation efforts for some of the biggest brands in the business. We partner with the leaders in intelligent automation, including Blue Prism, UiPath and Automation Anywhere, to get your organization past any automation skills gaps. Our prebuilt solutions and bundled programs can be customized to your organization’s specific needs to help you achieve true intelligent automation.