Op-Ed: Four steps to unlocking the value of application insights with AI

As revealed in F5’s 2020 Curve of Convenience Report, while Australian consumers expect brands to implement strong encryption and security into every touchpoint, 60 per cent say convenience is more important to them. Such insights suggest that user experience now defines the value of a brand, with security now considered table stakes.

The reality is that applications are the driving force of the digital economy; they’re enabling businesses to move at speed. In the hybrid working era, in particular, secure and high-performing applications have become imperative for every organisation wanting to enhance the way it interacts with customers.

But with rising security threats coupled with complicated transformational challenges, mission-critical applications need to be able to keep pace with an ever-evolving technology and business landscape. They need to be able to adapt to their environment, defend themselves, and scale autonomously to meet demand.

At the core, however, lies a central problem: businesses struggle to unlock the full value of application insights to inform the critical decision making necessary to adapt to rising customer expectations and newly emerging threat vectors. Such a problem can hamstring any digital transformation, present security vulnerabilities, and impede the delivery of a great customer experience.

Application insights are an imperative for ANZ organisations

When we look at key market segments in ANZ such as the public sector, financial services, and telecommunications industries, we can start to understand why real-time insights are so important.

Take the public sector for example. In 2021, we are likely to see state-based attacks continue to be the biggest threat to government organisations. Because of this, having access to data that can provide real-time predictive analytics can significantly improve the way agencies detect and prevent bad actors intruding on a network.

For financial services institutions, the open banking era presents a whole new playing field between traditional organisations and new technology-born entrants, with the digital user experience fast becoming the currency of a brand. At the same time, banks are utilising APIs to enhance service offerings and gain granular insights into how consumers are making choices.

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With the adoption of APIs, however, comes an array of security concerns that financial institutions must be proactive in mitigating. Surprisingly, while F5’s 2021 State of Application Strategy report found that 69 per cent of ANZ business are using API gateways, only 46 per cent have implemented proper API security.

In a similar vein, telecommunications service providers are trying to gain a better understanding of their customers’ expectations of 5G, as well as the threats that come with the fifth generation of broadband cellular networks. A lack of visibility across multi-cloud environments is becoming a major hurdle for service providers with 90 per cent of service providers citing security concerns according to F5’s 2020 State of Application Services: Telecom Edition report.

From these industry examples, we can see how having access to real-time application insights can greatly enhance security and customer experience. On the flip side, not having an adequate understanding of how consumers are interacting with your brand or how cyber criminals are evolving their tactics can pose a serious detriment.

Unlocking the value of application insights in four steps

Fortunately, there are steps businesses can take to enhance the way they understand both their customers and their security vulnerabilities through the power of AI.

First, businesses must be in a position where they can leverage data effectively. This requires organisations to develop capabilities that allow them to analyse data from all angles — including sending telemetry to third-party locations — in order to capture a holistic understanding.

The second part involves training machine learning models on the basis of this data. This is where businesses can identify various patterns, anomalies, and areas in which they can make predictions. This will provide an opportunity to operationalise machine learning models to make predictions at scale.

Thirdly, to keep up with the pace of business, organisations need to be able to make predictions in real-time. This is where deploying machine learning models that can elucidate insights pertaining to mission-critical functions is paramount—whether this is related to an application’s performance or health, or a particular transaction on a device.

The last piece of the puzzle is automating actions on the basis of these predictions. The way this is traditionally executed is by providing a set of actions or suggestions — based on predictive analysis — to a group of decision-makers, such as the team responsible for the behaviour of a particular application or business operation.

However, when cherry-picking insights to inform business decisions, the process is often limited to the bandwidth of the manual, human decision-making process. Because of this, creating a closed loop that is completely automated can significantly improve the cadence and quality of insights gleaned from application data, streamlining business and operations processes as a result.

AI has the power to transform everything we do but it is only as useful as the data we can provide it. With these four steps in mind, I hope ANZ businesses can gain a better understanding of how to unlock the potential that already exists within their application portfolio to both enhance and secure the customer experience.

Shuman Ghosemajumder is the global head of artificial intelligence at F5