The profound idea that machines can exhibit human intelligence gives rise to a common perception: implementing complex AI technologies requires deep expertise, thorough planning, continuous testing and improvement, and drastic changes to the existing.
As AI technology becomes more advanced, the perception that implementing it is a complex and daunting process is increasingly becoming outdated. Solutions such as Swish’s hyperautomation intelligence platform are designed to make the implementation of complex AI technologies easy, fast, and efficient. This is particularly important in the context of IT service management, where businesses are under constant pressure to optimize their operations and improve their service delivery.
In the age of digital transformation where agility serves as a key competitive differentiation for business organizations, ITSM leaders are looking for technology solutions that are easy to implement and immediately transform traditional manual processes to automated, autonomous and data-driven digital operations. In this blog we will review the key capabilities of the Swish hyperautomation intelligence solution that offers a simplified integration process, low learning curve and immediate digital transformation:
Replacing legacy ITSM solutions and integrating multiple proprietary ITSM tools to realize end-to-end process automation is challenging for several reasons. These technologies are typically not designed to interface together as a single and unified hyperautomation solution. Significant customizations are required before these tools can collectively deliver the unique functionality required for your ITSM pipeline. This also limits the scalability of the platform due to static and hardcoded configurations, and a complex map of dependencies between various application components. Swish eliminates the risk by offering native integrations with most ITSM tools and using standardized API interfacing to extract relevant data and produce insights across all ITSM pipeline processes.
Traditional process automation solutions require coding expertise to automate individual components of the ITSM pipeline. As a result, in-house expertise is required to create specific automation use cases, dashboards and generate reports that contain the necessary insights. This process is slow, resource intensive and inflexible for automating an ITSM pipeline where the nature of IT incidents and service requests can change rapidly. Swish hyperautomation intelligence technology offers a graphical user interface to analyze and optimize the ITSM pipeline. Instead of manually scripting the configurations and automation cases, Swish integrates on top of your existing delivery management system and offers a rich set of features for ticket deflection and routing, incident prevention, people augmentation and anomaly detection.
Automating data-driven processes becomes challenging when users are overwhelmed by the volume and speed of new information that drives proactive decision making capabilities of an ITSM organization. ITSM data is generated across several isolated sources such as service requests via ticketing platform, knowledge base and storage databases, network logs and application performance metrics data. The idea of a hyperautomation intelligence is to capture data across all disparate sources, provide a mechanism to extract insights and leverage ITSM intelligence across various ITSM functions such as IT Service Desk optimization, incident prevention and business decision making. SwishAI automates this mechanism such that users can continue to use their existing ITSM tools to generate relevant data and leverage ITSM intelligence directly from the Swish platform and delivered to various tools that are integrated with it.
AI models learn from new streams of information as it is captured and are therefore adaptable. As the data evolves, it represents new patterns and insights that may be vastly different from previous data sets. With the traditional automation approach, automation scripts are developed under predefined assumptions and criteria, which govern how processes are automated. AI implementation removes the requirement on hard-coding process workflows through automation scripts, which itself requires deep technical expertise and careful analysis of your ITSM requirements. The AI models learn from data and represent a desired state of operation: this may be in terms of the ITSM workflows or system behavior of a range of performance metrics. AI models evaluate how new service requests and performance metrics differ from its learned representation of your systems, or the ITSM pipeline. Insights and patterns are extracted from new data streams automatically, anomalous behavior is identified and the insights are provided to decision makers in the form of an intuitive dashboard or report to trigger appropriate actions proactively.
Implementing ITSM technologies as part of a digital transformation initiative is a resource consuming project. Resources investments are incurred over the course of the technology’s life cycle in the form of operational expertise, maintenance and troubleshooting, upgrades and scalability, customizations and improvements to meet desired business objectives. As a result, digital transformation projects turn into a cost center that require continuous financial and human resource investments. Swish has developed its hyperautomation intelligence platform as a plug-and-play solution that not only requires no additional resource investments in transforming raw ITSM data to competitive business insights, but also complements the limited ITSM workforce with advanced cognitive capabilities. Hyperautomation intelligence alleviates the burden from the IT Service Desk with capabilities such as people augmentation for resource intensive tasks such as ticket handling and ITSM workflow optimization.
ITSM leaders view digital transformation initiatives as long-term projects for a few simple reasons: ROI is often delayed and the promised rewards take ongoing investments to realize. Swish hyperautomation intelligence technology is designed to work with your existing ITSM systems such that no customizations are required and users can transform raw ITSM data into ITSM intelligence with a few simple clicks. As a result, your organization is both agile and mature in terms of driving strategic ITSM decisions by tapping into the vast intelligence potential of your AI systems without having to build them internally.