Keeping apps reliable and customers loyal: Why AIOps matters in an always-on economy

A mobile banking transfer completes in seconds. Behind that transaction is a chain of systems working in concert: the app, network, cloud servers, payment gateways, security checks and backend databases. 

When one link falters, the customer feels it immediately. Worse, a security lapse can expose sensitive data and erode trust in an instant.

Keeping the entire chain reliable is a business priority across the digital economy so users can access a service when they need it – from e-government portals to healthcare apps.

With artificial intelligence for IT Operations (AIOps), vendors such as Elastic are helping organisations automate monitoring and cut through the noise, freeing teams from reactive firefighting so they can focus on strategy.

Every user’s tap or click leaves behind digital footprints – from activity records to error messages – that businesses must monitor 24/7 to keep services secure, available and fast. 

AIOps builds on the foundation of observability: the practice of collecting and analysing data from applications and infrastructure to understand the internal state of complex systems. As systems grow larger and more complex, the volume of such data is now too large for IT monitoring teams to review manually.

By adding AI and machine learning (ML) to this practice, operational data is no longer just stored – it is processed for insights.

There is a race to glean insights, and speed is of the essence. Elastic integrates search and AI capabilities to analyse telemetry from every corner of the business – from networks, servers, applications or digital services, and security systems.

AIOps involves searching through billions of data points to find the root cause of an issue, a search-powered foundation ensures that answers are found in milliseconds rather than hours. 

Says Elastic’s area vice-president for Asean, Hong Kong, Taiwan and South Korea, Ravi Rajendran: “AIOps ingests telemetry data from IT infrastructure and enables proactive troubleshooting by analysing past performance patterns. By presenting this information on a single dashboard, businesses can identify anomalies before they affect customers.”

Why AIOps matters now

The urgency for AIOps in Southeast Asia cannot be overstated. The region’s digital economy is projected to exceed US$300 billion (S$386 billion) in 2025, according to a November report by Bain & Company, Temasek and Google. As consumer activity continues its aggressive shift online, competition for the same pool of customers will intensify. 

In this crowded market, resilient infrastructure, which contributes to reliable service, makes the difference between customer retention and resentment. The cost of failure is high: if a payment app hangs or a delivery platform slows during peak times, a frustrated customer is only one app store away from finding a competitive alternative. 

In the public sector, the stakes are equally high. Outages in public services translate into delays and frustration for citizens trying to access essential information or services, resulting in eroded trust and reputation.

AIOps enables organisations to move from a reactive approach, fixing things after they break, to a proactive stance, preventing issues before they even occur.

Currently, many organisations are ill-equipped to respond to these pressures because their data is siloed. They deploy a dozen or more monitoring tools – one for networks, another for servers, yet another for applications – with data scattered across multiple clouds and on-premises environments.

When an outage occurs, IT teams have to manually sift through these disparate tools, wasting critical time while the business loses money. AIOps replaces this fragmented approach with a single “pane of glass”.

A consolidated platform can analyse multiple alert streams simultaneously, identify priority issues and provide clear troubleshooting guidance to prevent unplanned downtime.  This does not just help IT; it aligns security and operations teams under one unified view of the business.

How to implement AIOps: A practical roadmap

For business leaders, implementing AIOps is not merely about installing software; it is a journey toward operational excellence. Rajendran proposes a practical roadmap for moving from fragmented monitoring to predictive intelligence. 

He suggests three steps:

• Step 1: Take stock of your IT environment: Map out key systems, where they run (cloud and on-premises), and which tools are used to monitor them. In many organisations, overlapping tools have crept in over time and they should be streamlined to reduce costs and complexity.
• Step 2: Contextualise and enrich data: “AIOps is only as good as the information it learns from,” Rajendran stresses. Success depends on data quality and integration. Elastic helps organisations enrich their telemetry data by making it coherent and usable on a single platform. While this step can take several months depending on data volumes, it is the most critical phase for ensuring accuracy and actionable insights.
• Step 3: Move from siloed monitoring to shared dashboards: Replace stovepipe views – where each team watches its own slice of the system – with dashboards that show service health end-to-end, so teams can see what matters most and act faster, rather than reacting to a wall of alerts.

In practice, change takes time, Rajendran adds. One bank customer took 12 to 18 months to get up to speed, he recalls. The payoff is a significantly stronger operational foundation, with gains that show up at each stage.

Early adopters have seen quarterly improvements obvious to customers: fewer outages and faster resolutions. Teams also spend less time troubleshooting and more time improving services. 

The momentum for AIOps is growing. Singaporean companies are already seeing the value, and adoption is expected to accelerate across the wider Asean region through 2026. Businesses are learning that waiting for a system to fail is no longer an option. 

“When problems occur and systems go down, it’s already too late,” Rajendran points out. “For any organisation providing digital services, observability cannot be a reactive afterthought – it must be a core component of the business strategy. 

“By adopting AIOps, firms are not just fixing IT; they are building the predictive intelligence necessary to remain secure, resilient and efficient in a US$300 billion digital economy.”

Learn how Elastic enhances observability and monitoring with AI at Elastic{ON} Singapore on March 17.