How RPA and AI will impact IT asset management
- By Marcel Shaw
- Apr 24, 2019
Digital transformation initiatives are driving government agencies to develop integrated IT asset management strategies that can meet resource demands and reduce analyst workloads. To meet growing service and asset requests, agencies are looking to IT asset management solutions that incorporate robotic process automation and artificial intelligence.
IT asset management has typically been viewed as an operational solution that enables an agency to properly document IT assets along with associated contracts, license agreements and disposal information. However, in recent years, IT asset management has become an important part of an overall security strategy for many agencies after several highly publicized security breaches. Incorporating RPA with AI into next-generation IT asset management solutions will also help federal agencies that are struggling to meet IT asset management objectives due to limited resources.
Several key areas will see changes as a result of incorporating RPA and AI into IT asset management:
Governance with RPA. Comprehensive IT asset management solutions are heavily dependent on both manual and automated processes. These processes ensure that IT assets are properly discovered, managed, secured and supported across every department within an agency.
To ensure accuracy and to meet the demands of a digital transformation, agencies need advanced automation tools to eliminate redundant manual tasks associated with managing IT assets but still support legacy applications and operating systems.
RPA will expand IT asset management capabilities by facilitating automation that spans beyond traditional back-end workflows. By observing employee interactions with the graphical interface on user computers, RPA can create action lists for virtual robots that will do the repetitive, non-value-added tasks associated with IT asset management that are currently performed by human analysts. This will free up staff resources for agencies, allowing them to reassign employees to projects or tasks where they can add more value.
Unstructured data management with AI. Automating service fulfillment processes is much more challenging when a service request includes IT asset requests for software or hardware, which typically requires additional legal processes to handle approvals, signatures, contract negotiations, license modifications and clarifications. Tasks associated with these processes often contain unstructured data or images that are embedded in email correspondence, voicemail or chatbots.
RPA processes can feed this unstructured, raw data to AI components that can interpret the unstructured data and return meaningful results back to the RPA engine, which then links those results to the appropriate IT asset fulfillment process.
With unstructured data management capabilities, RPA evolves from a simple task-automation tool into an intelligent process automation solution. This model is already gaining traction. Gartner predicts "a renaissance of the existing market offerings -- a shift from task-centric to more process-level automation and eventually to process orchestration."
RPA and AI will enhance service and asset requests by automating processes from start to finish, facilitating requests from chatbots, email, and voicemail. As a result, agencies can improve customer experience with faster service-request fulfillment along with accurate status updates.
Accurate IT asset compliance audits with RPA and AI. IT asset audits ensure organizations are compliant with software license agreements and regulations. When software vendors or third-parties audit agencies to ensure license agreements are followed, the results are typically not favorable for the agency, especially when IT asset management best practices have not been followed.
To ensure compliance, agencies should regularly perform self-audits, but this requires significant time and resources. Without comprehensive IT asset management, agencies will struggle to conduct self-audits with results accurate enough to verify or challenge results produced by third-party auditors. Too often, agencies are left with no choice but to rely on the reports produced by the outside auditors.
Next-generation IT asset management solutions will minimize or eliminate manual, redundant tasks required for self-audits by incorporating RPA technology. As a result, internal auditors can spend more time focusing on results instead of operational tasks. Auditors will evolve into analysts, interpreting results and providing insights to the agency.
Reducing costs and increasing efficiency with RPA
RPA and AI will reduce the level of effort and the costs that are typically required to operate a comprehensive IT asset management solution. Analyst workloads will shift from performing redundant, manual tasks to managing virtual robots. When IT asset management best practices are followed, agencies will be in a much better position to reduce their IT asset costs by making informed acquisition decisions.
Marcel Shaw is the federal markets engineer for Ivanti.