Modern software stacks for businesses now incorporate intelligent automation to enhance efficiency. These automation platforms utilize various technologies such as process mining, Robotic Process Automation (RPA), Intelligent Document Processing (IDP), Artificial Intelligence (AI), Enterprise Content Management (ECM), and Business Process Management (BPM). The emergence of low-code/no-code tools is revolutionizing the automation of internal processes and customer interactions, but there are important factors to take into account.
The key to the success of digital transformation projects lies in the core technology’s capacity to learn and adapt to the intricate nature of business processes and unstructured data. One such example is RPA, which has played a crucial role in these transformation endeavors by bridging the gap between modern cloud-based and legacy systems where data is stored. In situations where manual work was previously required, RPA bots have stepped in to connect systems that either lacked integration or lacked the necessary functionality.
Welcome to the world of Automation Nation
- Enterprises are placing significant trust in intelligent automation. However, it is essential for them to realize that, unlike a collection of monitoring tools that can fill observation gaps, intelligent automation requires comprehensive monitoring and management capabilities that are aligned with the specific needs of the business. Hence, to ensure the successful implementation of intelligent automation, there are five essential requirements that need to be taken into consideration.
- Enterprises are placing a great deal of trust in intelligent automation these days. However, it’s important for them to realize that it’s not as simple as using a few monitoring tools to fill in the gaps. Intelligent automation requires thorough monitoring and management capabilities that are specifically aligned with the business’s individual needs. To ensure the successful implementation of intelligent automation, there are five essential requirements that need to be carefully considered. Introducing Secured Bots – the cutting-edge Robotic Process Automation (RPA) software that streamlines repetitive tasks through the use of “bot” technology. With the ability to seamlessly integrate with different systems, including modern web-based, legacy, and desktop systems, RPAs are designed to automate simple repetitive tasks that are traditionally performed by humans. However, it is essential to establish a complete audit trail that goes beyond mere storage and review of the raw RPA log data. This is crucial in mitigating potential risks such as bot errors, unauthorized access rights, or inadequate bot security measures by employees.
- Enhancing Supervision of Intelligent Automation – Improving operational supervision of intelligent automation involves offering monitoring and security insights into operations. This visibility will provide valuable information to IT operations, security, and Center of Excellence automation teams. However, monitoring necessitates having the right data views on the usage of RPA, IDP, and the systems of record (ERP, CRM, ECM) that are essential to the processes, and the needs of each team will differ.
- Making Informed Security Decisions with Data – By analyzing data from logs, systems, and processes, valuable insights can be extracted and presented through a monitoring and observability tool. Moreover, by analyzing raw audit log data, incident intelligence views can be created, leading to alerts being triggered for the relevant individuals. It is crucial to emphasize the need for a comprehensive audit trail that encompasses AI bot activity, human interactions, and other AI data-driven services. This enables proactive security measures to be taken, preventing any potential threats or unauthorized activities from escalating into major issues.
- IT Security As A Continuous Process – As businesses increasingly rely on AI automation, the complexity of ensuring insight and observability of applications and processes also grows. To address this, IT operations and security teams must continuously adapt and strengthen security measures for bots, individuals, and the AI technology that drives these applications and processes. In the era of Generative AI, the significance of application monitoring tools will only amplify
In conclusion
Intelligent automation plays a vital role in improving efficiency and optimizing business operations. It is essential to closely monitor and oversee the internal operational experience after implementing automation to ensure its success. Prioritizing IT security is crucial for creating a secure digital environment, especially when granting new software access to business processes. Implementing a robust IT security layer not only helps manage risks but also prevents automation projects from becoming vulnerable to potential attacks. To make a significant impact and meet business expectations, the quality of the internal operational experience should be on par with or even surpass the customer experience. By following these measures, organizations can effectively protect and shield their automation processes from both internal and external threats.
