Intelligent automation initiatives help businesses identify, vet, and automate their processes to streamline organizational workflows. Robotic process automation (RPA), enterprise content management (ECM), business process management (BPM), process mining, and artificial intelligence (AI) fall under the banner of intelligent automation. These tools are often used with low-code or no-code options to automate business processes and speed up customer experience while increasing productivity and end-user satisfaction.
When approaching a new intelligent automation initiative, it’s essential to bear in mind that its success is predicated on the core technology involved and that technology’s ability to learn and adapt to new, complex business processes. Often, businesses expect that a patchwork collection of monitoring tools can cover their bases concerning monitoring various applications and the systems they work with. Still, in practice, a balance needs to be struck. Intelligent automation tools are advancing rapidly, and the technology stack needs to provide various capabilities that align with business requirements and the IT department’s capabilities. RPA, in particular, has distanced itself from the pack to this end.
RPA is one of the most relied-on technologies for transformation initiatives. It provides connectivity to legacy and newer cloud-based systems, removing the need for human intervention moving back and forth between applications. Due to these features, RPA can connect various systems previously unintegrated and have them begin to share data and pave the way for smoother processes.
Despite RPA’s prowess, security shouldn’t be an afterthought when building intelligent automation into the technology stack. As RPA moves data between systems, proper monitoring is essential, but the complexity of the technology can make it difficult. Below is a list of several ways enterprises can ensure their intelligent automation initiatives reach operational goals — without becoming a cybersecurity nightmare.
Bot security is paramount
Software that turns repetitive tasks into simple automation is called a “bot,” and it’s a vital part of any intelligent automation system. Bots can be used in virtually any digital environment and save IT departments many hours spent on repetitive manual tasks — tasks crucial to business operations.
With such vital placement in business workflows, ensuring these bots are secure is incredibly important. A bad actor looking to snarl operations to open a pathway into a system would love to gain access to a series of bots performing vital processes. Hardening RPA management consoles is essential, but it doesn’t stop there. Bots can also make mistakes or be misconfigured, so it’s a good practice to build comprehensive audit trails that can be relied on to show errors.
Establishing operational oversight
Enabling visibility into ERP, CRM, and ECM systems and the RPA and IDP processes involved in the automation initiative will provide accurate measurements for success. The visibility also allows insight to be passed along to stakeholders invested in the initiative’s success: security and IT departments, the Center-of-Excellence teams, and beyond. When done correctly, visibility will have the added benefit of providing a closer look at the automated cybersecurity activities.
Remember that stakeholders will require visibility into different aspects of the automation process. Those in the network, applications, and cybersecurity departments will want insight into the audit trails of all bots, including permission changes and other signals that bots may be compromised. Meanwhile, those who own automation processes, like the Center-of-Excellence team, will want to know the number of bots in operation at a given time and if they report errors. They’ll also want to know if tasks are building up in the queue and why — that way, they can prescribe methods of alleviating the backlog to get workflows back on track.
Integrating automation and AI
While many enterprises already have some level of AI-driven automation, not all have a way for their bots to connect and share data between them — at least, not securely. With innovation in this space happening faster than many security teams can keep up with and generative AI promising to have a hand in nearly every application throughout an organization, there’s no better time for companies to integrate AI with their automation processes. Intelligent automation tools, such as RPA, BPM, chatbots, or the like, will commonly share sensitive information as part of their functions. Because of the information sharing, application monitoring, and observation tools are crucial to prevent outages of critical processes and secure the data they’re transmitting.
Intelligent automation for today and tomorrow
As intelligent automation initiatives enhance a business’s workflows and competitiveness and improve customer experiences, the journey isn’t over once the software pieces are in place. Cybersecurity is ongoing and should be routinely updated to shore up defenses against the newest threats. Similarly, the rapidly innovating world of generative AI guarantees that application monitoring tools also have to evolve. These tools must simultaneously advance to ensure proper AI oversight while touching business processes and systems.
In addition, visibility and monitoring will be significant factors in determining which intelligent automation initiatives ultimately succeed. The customer and operational experience must improve to ensure the automation initiative has a significant business impact. The many RPA and IDP tools on the market, when paired with observation and monitoring software that integrates applications and systems, can enable an intelligent automation environment to give enterprises a competitive edge. Combined, they can keep workflows speedy and customers happy.
Brian DeWyer is CTO and Co-Founder of Reveille Software. With more than 25 years of experience in technology, he provides product strategy and technical leadership in his role as Reveille CTO and board member. Brian leverages his extensive knowledge from his tenure as a senior IT leader at an FSI and previous role as a process consulting practice leader for IBM Services delivering on-premises and cloud-based solution implementations for Fortune 1000 commercial and government clients. He has led process change efforts within large organizations, building on content-driven solutions for high-volume transaction processing applications. He is a past board member of the Association of Image and Information Management (AIIM) industry association. Brian graduated from Virginia Tech with a BSME and holds an MBA from Wake Forest University.