The Navisite Executive Guide for AI in Digital Transformation: Practical Solutions for Adopting AI Part II
In part one of our blog series on the transformative power of artificial intelligence (AI) in HR and IT, we examined three key areas of AI adoption: automation, Generative AI (GenAI), and multimodal unlocks. In this installment, we’ll delve into the realm of hyperautomation.
As we transition from understanding the practical applications of AI to implementing them on a broader scale, the concept of hyperautomation emerges as a pivotal framework for organizational transformation. But why the term “hyper”?
Understanding Hyperautomation
Hyperautomation refers to the integration of advanced technologies, including AI, machine learning (ML), and robotic process automation (RPA), to automate and optimize workflows comprehensively. Unlike traditional automation, which focuses on individual tasks or processes, hyperautomation aims to automate entire end-to-end workflows, spanning across departments and functions.
The term “hyper” underscores the scale, speed, and complexity of automation achievable through this approach. By harnessing the combined power of AI and automation technologies, organizations can achieve unprecedented levels of efficiency, agility, and innovation across their operations. A practical example of this would be creating a workflow for updating a support case that leverages Natural Language Understanding (NLU) to create a better user experience that creates deflection. In other words, the user never needs to speak with support to have their question answered – and it will still be answered the right way, the first time. This is when automation goes into hyperdrive.
There are three key pillars of hyperautomation: workflows, summarization, and knowledge creation. Following, we’ll take a deep dive into all three areas, examining real-world examples and best practices to uncover how hyperautomation revolutionizes processes, drives productivity, and fosters continuous improvement in organizations. Let’s dive in.
Workflows: Optimizing Operational Processes
Workflows lie at the core of organizational operations, dictating how tasks are initiated, executed, and completed. Using hyperautomation, however, workflows undergo a paradigm shift, transitioning from manual and siloed processes to automated, integrated, and agile systems.
In HR, hyperautomation streamlines various processes, including onboarding, performance management, and leave management. Automated workflows ensure seamless coordination between different stakeholders, reducing manual effort and minimizing errors. For example, ServiceNow HR Service Delivery (HRSD) automates the onboarding process by managing tasks such as sending welcome emails, setting up IT equipment, and completing required documentation – significantly enhancing the efficiency and experience for new employees.
Similarly, in IT, hyperautomation optimizes workflows related to incident management, system updates, and software deployment. Automated incident response systems detect, classify, and resolve issues in real-time, reducing response times and minimizing disruptions. Google’s utilization of AI to predict hardware failures and optimize energy usage in its data centers exemplifies how hyperautomation enhances IT service management efficiency, ensuring optimal performance and reliability.
Summarization: Distilling Insights From Data
Summarization is just what it sounds like: using AI tools to process source materials and output key information and main points.
In HR, AI-driven summarization tools streamline the recruitment process by scanning and summarizing resumes, highlighting key qualifications, and matching candidates to job descriptions. HireVue’s use of AI to summarize resumes and rank candidates exemplifies how summarization enhances the efficiency and accuracy of candidate selection, enabling HR teams to identify top talent effectively.
In IT, summarization aids in analyzing and summarizing log data, which highlights critical events and trends for IT teams. For example, Palo Alto Networks’ Cortex XDR uses AI to summarize security incident reports, helping IT teams quickly understand the nature and impact of threats – improving response times and effectiveness in resolving security issues. This approach ensures smooth IT operations and minimizes downtime, providing a robust defense against potential cyber threats.
Knowledge Creation: Fostering Learning and Innovation
In HR, AI assists in creating and managing knowledge repositories, facilitating continuous learning and development within the organization. Platforms such as Microsoft Dynamics 365 Human Resources utilize AI to build and maintain these repositories, ensuring information accessibility and promoting knowledge sharing among HR professionals. By centralizing knowledge resources, organizations empower HR teams to access relevant information quickly, make informed decisions, and drive strategic initiatives.
In the world of IT, AI-powered knowledge management systems play a crucial role in organizing technical documentation, code repositories, and IT knowledge bases. GitHub’s Copilot leverages AI to suggest code snippets and documentation, streamlining the development process and promoting knowledge sharing among developers. By harnessing AI-driven knowledge creation tools, IT teams can accelerate problem-solving and optimize IT operations.
This dual application of AI in HR and IT underscores its potential to enhance organizational efficiency and effectiveness.
Roadmap for Practical Hyperautomation Deployments
Embracing hyperautomation is not just about adopting cutting-edge technologies; it’s about fundamentally reimagining how work gets done. Here’s a roadmap tailored to real-world deployments, focused on actionable steps for achieving tangible results:
Demonstrate Immediate Impact: Begin by identifying high-impact processes within workflows, summarization, and knowledge management that exemplify the value of hyperautomation. For instance, consider automating routine data entry tasks such as updating customer records or processing invoices. By automating these processes, organizations can significantly reduce manual effort, minimize errors, and free up valuable time for employees to focus on more strategic initiatives. Additionally, automating repetitive report generation tasks, such as monthly sales reports or financial statements, through dashboarding and automated report delivery can streamline workflows, enhance accuracy, and improve operational efficiency.
Leverage Existing Systems and Technologies: Explore opportunities to integrate hyperautomation solutions with existing systems and technologies. Utilize APIs, connectors, and middleware to bridge the gap between legacy systems and modern automation platforms. For instance, integrating RPA bots with customer relationship management (CRM) systems can automate customer data updates and streamline lead management processes, improving sales efficiency and customer satisfaction.
Empower Citizen Developers: Empower non-technical users, or citizen developers, to build and deploy automation solutions tailored to their specific needs. Provide training, support, and resources to enable employees across departments to automate their workflows independently. For example, empowering sales representatives to create and automate email marketing campaigns using drag-and-drop automation platforms can accelerate lead generation and conversion rates.
Iterate and Evolve: Embrace an iterative approach to hyperautomation deployment where continuous improvement is the norm. Solicit feedback from end users and stakeholders at every stage of the deployment process and use data-driven insights to identify areas for optimization and refinement. Iterate rapidly, deploying new features and enhancements in short cycles to keep pace with evolving business needs.
Measure Impact and Return on Investment (ROI): Establish key performance indicators (KPIs) to measure the impact of hyperautomation on business outcomes. Track metrics such as process efficiency, cost savings, error reduction, and employee productivity to gauge the success of your automation initiatives. Calculate ROI to demonstrate the tangible value generated by hyperautomation and justify future investments.
Scale Across the Organization: Once you’ve proven the value of hyperautomation through pilot projects, scale your initiatives across the organization systematically. Identify opportunities to replicate successful deployments in other departments or business units, leveraging lessons learned and best practices from previous implementations. Build a scalable infrastructure and governance framework to support enterprise-wide hyperautomation adoption.
By following this roadmap, organizations can embark on a practical hyperautomation journey that delivers real, measurable value. From automating routine data entry tasks and report generation processes to empowering citizen developers and scaling deployments across the organization, every step is designed to accelerate the pace of innovation and drive business transformation.