The use of AI in IT services: Understanding the shift
Artificial Intelligence (AI) is making its presence felt everywhere, even in IT operations, and most definitely in the area of cloud management, cloud services and service desks.
Zoho Labs’ Product Manager, Ramprakash Ramamoorthy talks to Enterprise IT News about trends and use cases.
EITN: Please share trends about the use of AI in a) cloud management and cloud services, b) service desks ie. Chatbots, virtual assistants, contextual knowledge, predictive analytics etc, c) other IT functions that support business services.
Trends of AI in cloud management and cloud services
The enormous growth of cloud computing has resulted in a huge amount of data generated from cloud management systems. Proper analysis of these data points is crucial for businesses to provide the best customer experience and better manage cloud costs, but traditional rule-based systems don’t offer clear insights on the huge volume of data available for analysis. This is where AI steps in. Utilising AI to analyse vast amounts of collected data helps techs gain a deep understand of their systems. This means better alerting, proactive monitoring of availability, identification of the root cause of failure events, etc. For example, when deployed correctly, AI systems can predict outages, help provide proactive infrastructure management, and ensure better service availability.
Trends of AI in Service Desks
Managing the service desk is a different ball game compared to managing cloud services. In cloud management, most data is machine generated, whereas in service desks, most data is human generated. Powerful natural language processing (NLP) techniques are being deployed in modern service desk solutions, such as through chatbots. Simply put, AI in service desks can offer a productivity boost and better turn around times for service tickets. For instance, whenever a new ticket comes in via email, the NLP techniques can recognize the context of the email and assign it to the right technician based on similar interactions from the past. This helps improve the speed of ticket resolution and ensures better productivity by service agents. Chatbots could also help users receive immediate assistance for simpler queries.
EITN: What do all of the trends above translate to for the business? Please share top 3 examples?
Ramprakash: Infrastructure management is crucial for any business today. Non-availability of services could mean huge revenue losses and can negatively affect an organisation’s reputation. With the right adoption of AI, companies can maximize employee productivity and enhance the customer experience.
Consider this scenario for AI automating your IT infrastructure:
- Your logs and security platform determine there is an unusual surge of web traffic for a particular time of the day.
- Your monitoring systems predict that your system might go down in an hour given the current traffic. It also raises a ticket in your service desk with the highest priority.
- The service desk assigns the ticket to the correct technician and also pulls up a similar, past ticket that indicates the issue was resolved last time by adding more servers. It also points out that there are sufficient servers in the inventory.
- The agent then validates the recommendation of the service desk and will add the servers available in the inventory to production if requested. The system becomes stable, and the monitoring system sends out a detailed root cause analysis (RCA) to the stake holders.
This is how AI can connect the dots and ensure seamless IT infrastructure management.
EITN: What must CIOs do to prepare their IT teams for a shift in IT infrastructure? Please also explain this IT infrastructure shift, what is it and what does it mean for a business organisation?
Ramprakash: With AI incorporated into multiple aspects of IT infrastructure management, organisations will have to adapt to the changes that come along with implementing this technology. AI is enabling decision automation across the stack. Businesses have to ensure that the existing process hierarchy also factors in the decisions obtained from the AI system.
What has traditionally been a deterministic process, now has a tinge of probability to it. Traditionally, decision-making has been a yes-no procedure, but AI has introduced a tinge of probability to the process. In many organisations today, monitoring systems issue an alert when there is trouble with a particular server. But an AI-powered monitoring system can advise that there will be a 60 percent chance a particular service will fail in the next hour. The impact of advisories of this type can be factored into the organisation’s IT workflows if management choose to embrace AI.
It will be up to the CIO to drive the change to adopt AI across the organisation. Designing and modifying existing hierarchies to make them flexible enough to accommodate probabilistic decisions across various workflows in the organisation is the most important role of a CIO in enabling AI. In short, businesses will need to make quick adjustments to their existing workflows to reap the benefits that AI can provide.