Challenges in Intelligent Automation
This chapter is meant for highlighting the most common challenges that business organizations face when implementing Intelligent Automation. Here you will also find some possible solutions to overcome these challenges. The increasing accessibility of artificial intelligence (AI) allows businesses to implement intelligent automation for minimizing errors, enhancing decision-making, and improving productivity in their processes and workflows.
The use of Intelligent Automation also reduces the time and resources required for executing repetitive tasks.
Despite its several benefits, businesses also face multiple challenges along the way of implementing intelligent automation in their organizations. Let's discuss about these challenges in detail.
Common Challenges in Implementing Intelligent Automation
As we know, intelligent automation combines multiple advanced technologies like AI, workflow management, RPA, NLP, etc. to automate processes, enhance efficiency, and reduce time. However, the successful integration of these technologies and implementation of intelligent automation come with its own challenges. Some of the major issues and challenges that organizations face in their way to IA implementation and their possible practical solutions are explained below.
Resistance to Change
It is a basic human nature to oppose to changes, and this resistance to change becomes more intense when it involves the use of technology. This is mainly because human employees in any business organization feel that automation will displace their jobs or require them to learn entirely new things.
However, this challenge can be easily rectified by following below mentioned practices −
- Educating employees about the advantages of intelligent automation
- Providing trainings to employees to understand how to use IA tools and integrate them into their workflows
- Assuring employees that IA is meant to enhance their productivity and not for replacing them.
Integration Challenges
Most business organizations have their manual, legacy systems, and integrating intelligent automation with these existing systems can have compatibility issues. In that case, integration of intelligent automation becomes complicated and may lead to low-quality outcomes.
To overcome this issue, the following can be some practical solutions −
- Create a strategic technology plan
- Determine the systems that require custom integration and that can be integrated with read-made solutions
- Use clean and well-organized data for seamless integration
- Use appropriate integration techniques depending on the system needs, etc.
Data Privacy Concerns
Data is the foundation for intelligent automation, and the increasing data breaches and risks can increase the data privacy concerns for businesses, such as how the system will use and store their sensitive data. Any kind of data breaches can result in complications like legal matters, financial consequences, loss of trust, and more.
Businesses can reduce the risks of facing this challenge by implementing intelligent automation with strict data privacy practices, like as follows −
- Providing clear information about how data is used and stored
- Adhering to regulatory compliance and standards
- Providing extra layers of security to sensitive data, etc.
Unexpected Disruptions in IA Operations
There can be certain unexpected disruptions in intelligent automation processes, such as cyber threats, power outages, etc. These disruptions can affect the entire automation process of business operations.
This issue can be handled by following some practices like −
- Implementing redundancy measures
- Using cloud-based backup systems
- Regular testing and maintenance of IA system
- Implementing IA as per industry standards, etc.
Unrealistic Expectations from IA Systems
Sometimes business organizations expect that intelligent automation can automate their all the processes and solve every operational issue. In actual, intelligent automation is a powerful technology but it is not the solution for everything. Also, it requires continuous improvement to deliver the desired outcomes.
The following can be some practical solutions to overcome this IA related issue −
- Set a clear and achievable goal for intelligent automation
- Continuously improve the processes
- Regularly update the intelligent automation systems
- Understand and achieve the realistic goals, etc.
Conclusion
In this chapter, we highlighted some of the major challenges in implementing Intelligent Automation. However, these challenges can be addressed by following some practices like careful planning, open communication, training employees, and following regulatory standards, etc.