Level Up the Workplace with Automation and AI

In this IndustryVoices piece, Chad Haftorson of Freshworks discusses the promise of AI and Machine Learning in the new working landscape.

Technology adoption is occurring rapidly, owing to the rampant increase in digital transformation initiatives. The Covid-19 pandemic, the Great Resignation, and the need for improved employee productivity and better customer experiences are key drivers to digital business initiatives.

As more and more technologies are implemented to enable business resilience and agility, the amount of information stored and saved for future analysis has only increased. The data ecosystem is expanding because tech leaders expect to invest more in artificial intelligence/machine learning and data analytics to achieve their business goals.

Here’s what’s expected of IT in the current scenario:

1. To support anywhere operations

Businesses should be prepared to support the distributed operations of an enterprise while working from anywhere. This provides more flexibility and allows organizations to broaden the talent landscape without getting tied to recruiting from a specific geographic location.

2. To support an always-on business

A business is expected to always be on, regardless of external factors. Hence, IT operations need to be combined with automation and zero-to-minimal touch maintenance to shift the organization towards operational continuity. This will benefit the organization in the form of increased efficiency, faster workload deployment, reduced costs, and consistency across processes.

3. To increase IT productivity through automation

Automation is the key to increasing IT operational efficiency and managing today’s complex IT environments with existing IT resources.

The State of Automation

Increasing operational efficiency to retain employees is a top priority, as inefficient processes can frustrate employees and make it harder for them to perform their duties. Improving customer experience is the main driver behind digital transformation goals. We are increasingly seeing customer experience become a competitive differentiator. Companies have successfully improved the customer experience by deploying AI and Machine Learning (ML) capabilities, transforming existing business processes (i.e., automation, integration). Automation can achieve operational efficiency and accelerate the digital growth journey that many organizations are embarking by:

Providing 24x7 services

With service-management automation, you can provide always-available services to employees, customers, and suppliers without implementing shift work for your staff or leveraging outsourced contact center services. Self-service capabilities can be made available on any device, at any time, at any location (even at home or while traveling). Some companies have even expanded these capabilities to support localized languages when working with people in different regions.

Minimizing the business disruption

When customers and employees must spend their time waiting for a response, waiting in line, or waiting on hold, it can be wasteful and disruptive to your business. For your employees, this is time that could be used to focus on their primary job responsibilities, and the hold time renders them essentially idle and unproductive. Service-management automation and self-service capabilities can help reduce the time staff members wait for support and increase their productivity.

Providing greater flexibility/adaptability

When things need to change, as they usually do, it’s easier to change automation-based activities than the people-based equivalents where the day-to-day practices are engrained. Changing day-to-day routines can be difficult to move on from, at least without some slippage back into the old routine.

Eight Ways to Leverage AIOps and IT Automation

AI and machine learning have transformed traditional ITOM capabilities. Here are eight ways you can leverage AIOps and IT automation to optimize their digital operations:

Intelligent or predictive alerting. This is when machine learning uses historical data to understand the future, i.e. that a given set of alerts or infrastructure attributes is a sign that something will eventually fail or perform unexpectedly. Corrective actions can thus be taken before an issue impacts business operations.

• Event prioritization - This is when AIOps solutions learn from your organization’s incident and event data to understand the likely business impact of a predicted or actual event, i.e. which IT or business services are affected, how badly, and what it means to business operations and outcomes. Events are prioritized in real-time based on their business context, and people can focus on what matters most.
• Root cause analysis - This is when AIOps uses event patterns and service topologies to identify service issues’ root cause or causes.
• Auto-remediation - This is when the AIOps solution understands an issue that needs fixing and the required fix. This fix is applied automatically, either with or without human authorization, using native capabilities or third-party tools via orchestration.
• Capacity and cost optimization - This is when AIOps solutions understand business demand for IT services and thus the IT infrastructure that supports them changes over time; an example would be a solution which recognizes seasonal peaks and troughs. As a result, AIOps solutions can automatically scale or shrink the available infrastructure and the associated costs to meet the predicted future demand.
• Intelligent automation solutions can help transform a company’s operational processes, such as automating the infrastructure, integrating service management with other systems, and ensuring security compliance to create zero-touch service management capabilities.
• To help transform the customer and employee experience, automation can provide self-service capabilities for customers and employees and allow for a 360-degree view of the customer journey; this view can provide key insights from data.
• On the development side, automation can transform a company’s business model by shortening the life cycle of software development, integrating with homegrown systems, and creating new value propositions through artificial intelligence and machine learning.

Final thoughts

Automation and AI can be a cost-effective way to manage IT incidents, allowing employees to focus on more high-value work. From enhancing service desk solutions to reducing redundant tasks, automation and AI will drive more value for businesses deploying these capabilities. Automating processes saves time and allows resources to be diverted elsewhere. It means companies can remain smaller and more agile. Increased efficiency, productivity, and lower costs all translate to healthier profit margins for businesses, regardless of the organization's size.