Automation at scale introduces new responsibilities to enterprise IT teams

Federal agencies continue to invest in automation to advance missions and improve operations. As part of our 2023 Voice of our Clients, CGI executives asked federal leaders specifically about the role of automation within their organizations, and the results are interesting: 

• Government leaders are leaning into simple automation, with 45% indicating they have processes implemented
• The biggest growth area has been robotic process automation (RPA), with usage up 17 percentage points compared to 2022
• 53% are investigating algorithmic automation and 21% are building proofs of concept (POCs) in this area
• 70% indicated that they are investigating or creating prototypes involving artificial intelligence (AI)

Due to the increasing number and complexity of automation implementations at agencies, enterprise IT organizations must be ready for this new paradigm. Those responsible for governance, application and platform lifecycle management, release management and DevSecOps must be ready to support automation at scale.

Selecting processes for automation and developing the capabilities may seem like the largest challenges to automation initiatives. However, from a technical perspective, numerous other issues could impact the implementation of automation. Proper planning and the right stakeholder engagement—established early in the process—are necessary to ensure that concerns as diverse as governance, DevSecOps and application lifecycle management (ALM) proceed smoothly.

Automation evangelists and sponsors must team up with enterprise IT—including the ALM, DevSecOps and release management teams—in devising the strategy to effectively move capabilities to production. The increased adoption of automation adds new responsibilities to enterprise IT teams, and you will need their buy-in to achieve your objectives.

The role of ALM and DevOps in implementing automation

ALM teams may look at automation as a completely new animal within their enterprise IT kingdom. With these new technologies—from RPA to algorithmic automation and artificial intelligence—they wonder, how do we track issues, verify code quality or create and maintain operational documentation?

Leading RPA platforms include integrated development environments (IDEs) that provide visual RPA design. This might give the impression that RPA is code-free. In fact, IDEs produce RPA application project files, usually in the form of XML; developers create extensions to the platforms with common programming languages such as Python. Enterprises can, therefore, treat RPA applications and extensions just as they would custom applications, mitigating their ALM teams’ concerns by, for example, using their existing methodologies for application source code management and code quality management.

While DevOps merges development and operations ecosystems, automation demands separation. Hybrid DevOps operating models that encourage agility and meld traditional testing methodologies are required for successful DevOps. As use of automation expands, I envision models that encourage Continuous Integration (CI) but take a more traditional system testing and deployment approach instead of a Continuous Delivery (CD) approach given inadequate test automation coverage.

Automation release management

Enterprise IT teams mandate application development teams to use enterprise release management strategies. Automation applications adhere to source code promotion, release nomenclature, system testing, user acceptance testing and related release management policies. Developers create and integrate automations in a development environment, with testing in one or more testing environments. After adequate testing, automations are finally released to perform production work.

Automation platforms require enterprise authority to operate based on adherence to information security controls. However, not all enterprise IT controls fit well with automation.

For example, I recently supported an RPA implementation that was blocked by the requirement for two-factor identification―something bots are not easily able to accommodate. I collaborated with our IT and enterprise security subject matter experts to define alternate operating environments and security controls that do not force RPA to engage mechanisms designed for human users. Our experience tells us that enterprises must budget and prioritize sufficient subject matter expert time to unblock automation implementations.

Impacts of automation on enterprise systems

Enterprise IT teams are sensitive to the impact of robotic activity on enterprise applications. They take on a new set of IT responsibilities including definition, documentation, credentialing and measurement of automation activities within the enterprise. Teams leveraging automation within their solutions must clearly document architectural implications. Clarity around these new responsibilities—and management of the enabling automation technologies at scale—is essential.

Assurance of automation activity via audits, simplification of architecture and a gradual automation approach all help teams successfully manage implementations.

To learn more about CGI’s global capabilities in intelligent automation and how we’re helping organizations adopt automation at scale, visit our Intelligent Automation Services page