Intelligent Automation: Application Priorities for CIOs in 2023

Gone are the days of implementing the technology needed just to get by. Today, CIOs need to be intentional about what applications are going to help their association thrive. This can be done by selecting applications that will help build a strong foundation moving forward. In this three-part blog series, we’re going to focus on recent InfoTech research that suggests the application priorities when it comes to reaching your goals and objectives in 2023. While part one discussed what considerations should be made when exploring your Digital Experience plan, part two is going to cover the importance of Intelligent Automation and how it can become a part of your association’s digital strategy.  

Intelligent automation (IA) is the combination of traditional automation technologies, such as business process management (BPM), robotic process automation (RPA), and machine learning (ML). The goal is to further streamline and scale decision-making across various business processes by removing human interactions, addressing decisions that involve complex variables, automatically adapting processes to changing conditions, and bridging disparate automation technologies into an integrated end-to-end value delivery pipeline.  

As AI and ML continue to rapidly grow, organizations are seeing the value of machines intelligently executing high-performance and dynamic tasks such as driving cars and detecting fraud. It’s no surprise that senior leaders recognize opportunities to extend their business process automation investments. 

There are a variety of tools and technologies that are involved in Intelligent Automation and include:  

• Artificial intelligence (AI) & Machine Learning (ML): AI involves making its own decisions without human intervention. These systems perform tasks mimicking human intelligence such as learning from experience and problem-solving. Machine learning systems are different in that they learn from experience and without explicit instructions. They learn patterns from data then analyze and make predictions based on past behavior and the patterns learned. It’s important to note that AI is a combination of technologies and can include machine learning.  
• Intelligent Business Process Management System (iBPMS): Combination of BPM tools with AI and other intelligence capabilities.  
• Robotic Process Automation (RPA): Robots leveraging an application’s UI rather than programmatic access. Automate rules-based, repetitive tasks performed by human workers with AI/ML. 
• Process Mining & Discovery: Process mining involves reading system event logs and application transactions and applying algorithmic analysis to automatically identify and map inferred business processes. Process discovery involves unintrusive virtual agents that sit on a user’s desktop and record and monitor how they interact with applications to perform tasks and processes. Algorithms are then used to map and analyze the processes.  
• Intelligent Document Processing: The conversion of physical or unstructured documents into a structured, digital format that can be used in automation solutions. Optical character recognition (OCR) and natural language processing (NPL) are standard tools used to enable this capability. 
• Advanced Analytics: The gathering, synthesis, transformation, and delivery of insightful and consumable information that supports data-driven decision-making. Data is queried from various disparate sources and can take on a variety of structured and unstructured formats. 

Why Consider Intelligent Automation (IA) Applications 

Good Process Management Practices 

Not only does IA magnify existing inefficiencies in your business process management practice, such as unclear and outdated process documentation and incorrect assumptions, it also reinforces the importance of good business process optimization practices. This includes removing waste and inefficiencies in a thoughtful way, choosing the most appropriate automation solutions, and configuring the process in the right way to maximize the solution’s value. 

Quality & Consistency 

When products and services are delivered via an undefined and manual process, you risk the creation of preventable and catchable defects, security flaws and holes, missing information, and other quality issues. IA solutions consistently reinforce quality standards the same way across all products and services while tailoring outputs to meet an individual’s specific needs. Success is dependent on the accurate interpretation and application of quality standards and the user’s expectations. 

Worker Productivity 

IA removes the tedious, routine, and mundane tasks that distract and restrict employees from doing more valuable, impactful, and cognitively focused activities. Practical insights can also be generated through IA tools that help employees make data-driven decisions, evaluate problems from different angles, and improve the usability and value of the products and services they produce. 

Benefits of Intelligent Automation

• All business processes must be mapped and documented to be automated, including business rules, data entities, applications, and control points. 
• IA can be configured and orchestrated to automatically execute when certain business, process, or technology conditions are met in an unattended or attended manner. 
• IA is applicable in use cases beyond traditional business processes, such as automated testing, quality control, audit, website scraping, integration platform, customer service, and data transfer. 

Risks of Intelligent Automation

• The accuracy and relevance of the decisions IA makes are dependent on the overall quality of the data used to train it. 

• Some decisions can have significant reputational, moral, and ethical impacts if made incorrectly. The question is whether it is appropriate for a non-human to make that decision. 
• IA is composed of technologies that can fail or be compromised. Without the proper monitoring, controls, and recovery protocols, impacted IA will generate significant business and IT costs and potentially harm customers, employees, and the organization. 
• Low- and no-code capabilities ease and streamline IA development, which makes it susceptible to becoming unmanageable. Discipline is needed to ensure IA owners are aware of the size and health of the IA portfolio. 

Getting Started with Intelligent Automation 

It’s important to formalize your business process automation practice with a good toolkit that includes a repeatable set of tactics and techniques. This will help clarify the problem that is being solved with AI along with applying positive practices designed to first optimize and then automate key business processes. This will prepare you when it comes to exploring the various IA tooling options available. Keep in mind that each IA tool will address a different problem. Which tool to choose will depend on a variety of factors, such as functional suitability, technology suitability, delivery and support capabilities, alignment to strategic business goals, and the value it is designed to deliver. 

It’s not uncommon for associations to struggle when it comes to realizing the full potential of AI. This may be due to a lack of understanding when these technologies should and shouldn’t be used along with a fear of the unknown. The plan to adopt AI should include understanding of what AI really means in practice, identifying specific applications of AI in the business, and understanding the type of AI applicable to the situation. Implementing AI and ML thoughtfully and with a plan will go a long way toward its success.  

Recognizing that biases can be introduced into an IA system at any stage of the development process is important. From the data you collect to the way you collect it, to which algorithms are used and what assumptions were made, it’s imperative to be aware of these pitfalls in order to mitigate these biases. While they may not be intentional, early detection, good design, and other proactive preventative steps can be taken to minimize their scope and impact. 

Wrapping IT Up 

With Intelligent Automation, CIOs can help foster more efficient operations and streamline processes while integrating technologies like BPM, RPA, and machine learning into reliable workflows. Though it’s never easy to make these kinds of decisions—CIOs must dive deeper and recognize the advent of new tech trends in order for their organization to remain competitive. The right application selection is essential when it comes to achieving success both now and in the future. CIOs must carefully consider what applications will strengthen their foundation while still allowing their association to seize the potential opportunities that arise down the road.  At Cimatri, we have knowledgeable experts ready to work with you to build and adopt AI into your IT strategy.

Is your association ready to unlock the transformative potential of AI? If so, contact us to plan your personalized AI Workshop.