AI has certainly become the hallmark of digital transformation strategy. According to IDC, global AI spending is forecasted to reach $500 billion in 2024 with a CAGR of 17.5%. Likewise, Gartner predicts low-code application platforms (LCAP), robotic process automation (RPA) and AI are fueling the growth for hyperautomation, and the market will reach $596 billion in 2022, up nearly 24%.

According to Norton’s Cyber Safety Pulse Report, India faced over 18 million cyber threats in only Q1 2022, roughly 200,000 threats every day. Of the bulk, 60,000 were phishing attempts, and 30,000 were tech support scams. For perspective, phishing attempts around the world during the same period counted for approximately 16 million. CERT-In also reported over 2.12 lakh (~0.1 million) cybersecurity incidents until February 2022.

Digital-first businesses are striving for service assurance, which has become the lifeblood for their businesses processes. But they are increasingly getting complex across legacy and cloud-native applications, multi-cloud distributed services, with the rise of edge and when leveraged with Kubernetes and microservices architectures. Service assurance needs full-stack observability; however, customers need an approach to tame the data deluge while enabling actionable insights.

Enterprises today want real-time business insights to make decisions that improve operational efficiency and customer engagement and present newer revenue opportunities. However, the promise of the data-driven business falls short due to gaps in data management. These gaps exist because data in the modern enterprise doesn’t exist only behind firewalls and within organizational premises.

My market trends and predictions for 2021, be it for AI-based drug discovery or cybersecurity, have certainly accelerated in 2022 as a result of Covid-19 and the ongoing pandemic. This has brought unprecedented uncertainty, fear and challenges to how we do business, work, live and play.

Artificial intelligence for IT Operations (AIOps) encompasses technologies that augment human decision-making with autonomous decision-making driven by AI and ML technologies that learn patterns and relationships from underlying datasets.

One of our partners in the LATAM region is working with an end customer, to implement a custom predictive maintenance dashboard, by pulling in and correlating data from multiple sources (like Zabbix, Jira Cloud, Cato Networks, Extreme Networks CloudIQ, etc.) and sending out the data to update a Grafana dashboard, which can read data from OpenSearch. Partner is using our data bots and low-code/no-code pipelines to implement this project.

According to Insight Partners, the AIOps platform market size is expected to grow from $2.83 billion in 2021 to $19.92 billion by 2028 at a compounded annual growth rate of 32.2%. This skyrocketing growth is fueled by the pace of the IT data deluge getting out of the human hand and the need for resource optimization. Every organization is increasingly producing more IT data, whether in a siloed or unified form.