Q1: How is AIOps expected to grow in 2022? What factors are driving it?

Legacy IT systems are often complex, decentralised and slow. What’s worse, the exponential increase in complexity brought about by the surge in remote work has left IT departments grappling with outdated systems. The ability to manage complexity, however, ultimately requires technology that is capable of handling it, and Artificial Intelligence for IT Operations (AIOps) does just that.

We expect that the adoption of AIOps will grow in 2022, with 70% of enterprises and businesses planning to implement this technology to pivot their IT systems from reactive to proactive. AIOps is all about applying machine learning techniques to IT operations functions, allowing IT to correlate current and historical data with speed that operators are unable to achieve using traditional manual processes and tools that may have fallen into siloes. Predictive AIOps allows operations teams to see slow-forming anomalies before they become outages and fix the problem before users are impacted.

The COVID-19 pandemic has played a significant part in driving the growth of AIOps, as businesses were forced to get comfortable with making big adjustments– quickly. That said, the pandemic has also impacted the way that customers want to pay for services. People are no longer comfortable signing long-term agreements that are difficult to get out of, and this needs to be reflected in technology business’ service offerings.

Consumers want flexibility from their tech providers, whether that’s the option to sign shorter term contracts or opt into pay-as-you-go (PAYGO) subscription models. PAYGO payment methods are common in consumer contracts such as for mobile phones or utilities, but the demand is increasing across tech services like AIOps, too.

 

Q2: What challenges did the IT sector face in 2021 and what we can expect to see next year?

The past year has accelerated the pace of digital transformation for all businesses, presenting numerous challenges from cybersecurity to supply chain logistics. In 2022, I expect we’ll see businesses focus on forecasting and aiming to make proactive, preventative decisions after a year of firefighting.

Organisations will be looking for greater transparency across their IT systems in order to implement these preventative measures. The key is to bring together IT service management, operations management and predictive AIOps on a single platform. This allows AIOps to collect the data it needs and present it to the operations team, giving them the information they need to understand the root cause of an emerging anomaly or outage and fix it in near real time.

 

Q3: Where should an organisation start in terms of introducing AIOps into the business?

Introducing AIOps into IT operations is a straightforward and effective place to start for businesses that are new to the technology. AIOps can be set up to handle calls and create tickets in response to incoming problems, prioritising tasks based on service levels and allocation of need. On a wider scale, the technology can be deployed to help manage projects, helping to keep different aspects on track and ensuring systems are running effectively.

 

Q4: How do you feel AIOps will impact the supply chain in 2022?

The pandemic brought about enforced remote working and the closure of non-essential retail stores, and as such, we’ve become used to ordering everything online, from groceries to furniture. We also expect flexibility around delivery times. This surge in demand for online deliveries has wreaked havoc on supply chains that were already dealing with factory closures as a result of COVID-19 and that had already been burdened by economic changes such as Brexit.

Over the past few years, AI has proved transformational for numerous industries, including the manufacturing and logistics industry. As we move into 2022, more manufacturing and logistics companies will leverage AIOps to improve their productivity. Since user requirements are becoming more complex, data-driven platforms are used by firms to cater to the needs of customers. Due to increased competition and customer demands, there is a need for autonomous supply chains, and AIOps-based analytics platforms can help firms keep up with the increased customer demand.

 

Q5: What key pain points do you see customers using AIOps to solve?

Speed, scalability, and complexity are three major pain points of IT operations teams. AIOps helps to reduce meantime to resolution (MTR) to speed up operations, and supports organisations in accurately forecasting growth opportunities.

IT professionals can address hundreds of problems in a day. While they might fix one non-critical system error, the chances are they may miss another critical event (like a download). Here, AIOps helps in the detection of any unusual scenarios, notifying the operations team if any occur to help ensure the business runs smoothly.

 

Q6: How do you feel AIOps technology and use cases will grow over the next five years?

Artificial intelligence, machine learning and AIOps technology will become critical technologies as IT teams transition from traditional workloads to smarter, forecast based operations. AI is the next natural layer on top of observability platforms to ensure systems are synced up and any errors are identified at source.

Gartner notes in its Market Guide for AIOps that “there is no future of IT Operations that does not include AIOps”. AIOps ultimately means being more proactive, productive and collaborative, whatever the industry. The market for AIOps was forecast to grow 15% between 2020 and 2025, and I wouldn’t be surprised if it exceeds this expectation.