AI to supercharge observability tools, but we’re still far from hands-off

Artificial intelligence will be far more embraced in 2024 than it has been thus far, in both the private and public sectors, but humans will, and must, remain in the loop as the technology evolves. 

“The expansion of AI in the new year is likely to be quite significant,” says Dhiraj Goklani, Vice President, Observability for APAC at Splunk. “I see a lot more advancements in AI, with a balance in the excitement for all the possibilities with the need to ensure it’s ethical and responsible AI.”

AI will be increasingly used to make predictions about consumer behaviour and supply chain, as well as to detect anomalies and potential threats in digital environments, aside from being used to improve operational efficiency, says Goklani. 

With the current rate of data proliferation, being able to utilise observability tools such as the Splunk platform would remain important to organisations seeking to innovate and grow. 

Goklani shares his thoughts with GovInsider as he discusses some of the key findings of the Predictions 2024 report, which Splunk has made available while examining how AI will continue to impact businesses, as well as disrupt observability tools. 

Improving the customer experience 

When it comes to AI-powered automation, most business leaders tell Goklani that they want to automate routine, repetitive tasks so that workers can focus on more complex and creative tasks. 

When businesses interact with their customers, they want to be able to give them the best possible experience. This usually entails better understanding the customer through data to provide a more personalised experience.  

Simple chatbots can only go so far, says Goklani, adding that “AI can do much more to learn and understand customer experiences and to put together tailored recommendations. We want that personalised experience that will drive more loyalty and customer satisfaction.” 

Goklani goes on to share that AI tools can also observe real-time customer behaviour, to derive patterns that can inform organisations and help them better forecast future behaviours, and provision for potential needs, such as for increased cloud or storage capacity.

“We are seeing organisations trying to find every way possible to get much more, deeper insights into market trends. Now there is the ability to do this with real-time data coming in and do it at scale,” he says.  

“Being able to see what impact certain [business decisions] will create, the predictive element of AI is becoming more real.” 

Public sector and AI 

There may be a perception that the private sector is more invested in AI, with some leading multi-national companies having announced the development of their own large language models (LLMs) and generative AI tools. 

However, Goklani believes that the public sector is not standing pat, for good reason, as more governments are starting to embrace digital transformation and delivery of e-services. 

For example, Singapore recently channelled US$52 million into a new national multimodal LLM programme to develop Southeast Asia’s first regional LLM, reported GovInsider previously. 

“They are trying to stay ahead and not become laggards, as there is a huge opportunity for them to drive better citizen experiences.” 

This is where the implementation of ethical AI becomes even more pertinent. 

“If you are a citizen going online and the government is [communicating or transacting] with you, and using AI in those interactions, the public-sector agencies that are dealing with citizen data have to build up a lot of trust, with clear regulations in place,” says Goklani. 

“When it comes to AI, key tenets like accountability, transparency, privacy and fairness help to ensure ethical AI is in place.”  

Fresh contextual insights

One of the key predictions in the Predictions 2024 report highlights that AI will disrupt observability, but the most revolutionary gains will only arrive in years to come. 

What Goklani believes we will start to see in 2024 is the derivation of more contextual observability insights. 

“With AI, the models are continuously learning. As they learn more about data, they can add more context to that data,” he says. “So it is one thing to learn the data, but it also increasingly add more context and metadata to the new information coming in, based on learned patterns.”

“Thus, with any change that happens in the environment, you can quickly understand why it happened, in real time.” 

According to Goklani, this is the “next horizon of observability” that companies such as Splunk are working hard towards.  

Having shared his thoughts and observations, Goklani cautioned about the ability of systems to self-heal or self-remediate after detecting anomalies, as they are still far from off in the horizon. 

“You don’t want to automate too much yet, without the human in the loop, or the ability to understand whether such actions might create separate set of issues,” he says. “If it is a benign AI automation such as adding more capacity to a server, then that’s fine. 

“But if it is something that might cause a system-wide reboot, that is not going to be good. So I think we are still not there yet.” 

On the verge of major disruption

So while Splunk’s Predictions 2024 report highlights that we are on the verge of major disruption, the prevailing view is that it can’t possibly all be good news – and the report provides more context and advice for C-suite leaders on how to navigate the way forward. 

"I think [AI] will help far more in operational efficiency in 2024,” says Goklani. “You’d be amazed that a huge part of the world is still operating on-premise with legacy architectures, with very traditional environments and applications.  

“AI will actually help fast-track the journey to the cloud or cloud-native applications, by driving more operational efficiencies and helping to reduce cost as well as be more creative in giving customers better experiences.”