This research report categorizes the AIOps Platform market based on Offering, Services, Deployment Mode, Application, Vertical, and Region.

Northbrook, IL 60062 -- (SBWire) -- 08/17/2023 --The global AIOps Platform Market size is projected to grow from USD 11.7 billion in 2023 to USD 32.4 billion by 2028, at a CAGR of 22.7% during the forecast period, according to research report by MarketsandMarkets™

AIOps platforms are being adopted across various verticals to optimize IT operations and drive business success. In finance and banking, AIOps aids in fraud detection and real-time transaction monitoring. Healthcare benefits from improved patient data management and diagnostics. Retail and e-commerce use AIOps for demand forecasting and personalized customer experiences. Telecommunications enhances network performance and customer satisfaction. Manufacturing optimizes production with predictive maintenance. Governments improve citizen services and cybersecurity. Energy and utilities optimize distribution and predict maintenance needs. Transportation and logistics streamline operations for cost-effective efficiency.

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306 - Tables
59 - Figures
347 – Pages

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Healthcare & Lifesciences to account for higher CAGR during the forecast period

Healthcare and life sciences are adopting AIOps platforms to revolutionize patient care and research. AIOps efficiently manages patient data, enhances diagnostic accuracy, and accelerates drug discovery. Real-time monitoring ensures timely interventions and improves patient safety. Predictive analytics aids in proactive care and resource allocation, reducing hospital readmissions. AIOps automates healthcare IT management, enhancing system reliability. Additionally, it ensures regulatory compliance and strengthens cybersecurity measures, safeguarding patient data. By leveraging AIOps, the healthcare industry gains access to advanced analytics, automation, and real-time insights, driving data-driven decision-making and improved patient care.

Services Segment to account for higher CAGR during the forecast period

The market for AIOps Platform is bifurcated based on offering into platform and services. The CAGR of services is estimated to be highest during the forecast period. AIOps platforms were revolutionizing traditional IT service management practices by introducing intelligent automation, proactive monitoring, and predictive analytics. The shift towards AIOps was streamlining incident management, optimizing resource allocation, and improving overall service delivery. By leveraging AI algorithms to analyze large volumes of data, AIOps enabled faster incident resolution, reduced downtime, and enhanced service reliability. This transformation was empowering IT teams to be more proactive and data-driven, thus significantly improving the efficiency and effectiveness of service management processes.

Asia Pacific to exhibit the highest CAGR during the forecast period

The CAGR of Asia Pacific is estimated to be highest during the forecast period. AIOps Platform is rapidly growing in Asia Pacific, which includes China, India, Japan, ASEAN, South Korea and ANZ (Australia and New Zealand). AIOps adoption was growing rapidly as businesses in the region recognized its potential to enhance IT operations and drive digital transformation. Organizations in various industries were embracing AIOps to optimize their IT infrastructures, improve service reliability, and enhance customer experiences. The increasing complexity of IT environments in the region, driven by digitalization and cloud adoption, was fueling the demand for AIOps platforms. Additionally, the presence of a large tech-savvy workforce and a flourishing startup ecosystem contributed to the rapid adoption of AIOps technologies in the Asia Pacific region.

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Market Players

Major vendors in the global AIOps Platform market are IBM (US), Splunk (US), Broadcom (US), OpenText (Canada), Dynatrace (US), Cisco (US), HCL Technologies (India), Elastic (US), ServiceNow (US), HPE (US), Datadog (US), New Relic (US), SolarWinds (US), BMC Software (US), ScienceLogic (US), BigPanda (US), LogicMonitor (US), Sumo Logic (US), Moogsoft (US), Resolve Systems (US), AIMS Innovation (Norway), Interlink Software (UK), CloudFabrix (US), PagerDuty (US), Aisera (US), ManageEngine (US), Digitate (US), ZIF.ai (US), Autointelli (India), UST (US), Freshworks (US), Everbridge (US), StackState (US), Logz.io (US).

Key Dynamic Factors For AIOps Platform Market:

The Artificial Intelligence for IT Operations (AIOps) platform market was expanding and changing significantly. AIOps systems improve the management and monitoring of complex IT environments by integrating artificial intelligence (AI) and machine learning (ML) technologies with IT operations.

Rapidly Changing IT Infrastructure: The need for advanced monitoring and management solutions was being driven by the complexity of modern IT systems, such as hybrid and multi-cloud configurations, containerization, and microservices. AIOps solutions were sought after to offer real-time intelligence and intelligence that could be used to manage these complex situations.

Data Volume and diversity: As IT infrastructure and digital processes grew, traditional monitoring technologies were unable to keep up with the volume and diversity of data being collected. AIOps solutions were tackling this problem by utilising AI and ML algorithms to examine massive amounts of data from numerous sources, including logs, metrics, and events, in order to find trends, anomalies, and potential problems.

Efficiency and Automation: AIOps systems allowed IT teams to simplify operations, automate routine processes, and minimise manual intervention. IT specialists were able to concentrate on strategic duties rather than time-consuming repetitive operations thanks to this efficiency increase.

Real-time Insights: Businesses have been requesting more and more real-time information on how their IT services are performing. Predictive and prescriptive insights from AIOps systems might inform IT teams of possible problems before they resulted in substantial disruptions.

Machine learning and AI Advancements: AIOps platforms' capabilities were being driven by the ongoing development of machine learning and AI technologies. In order to deliver more precise anomaly identification, root cause analysis, and intelligent automation, these systems were utilising cutting-edge algorithms.

Vendor Landscape and Competition: There were an increasing number of startups and established companies providing specialised AIOps solutions in the AIOps industry. This contest encouraged creativity and sped up the creation of new features and functionalities.

AIOps is becoming a crucial part of DevOps and Agile practises, and they are integrated with one other. Organisations may close the gap between development and operations by integrating AIOps capabilities, which would speed up application delivery and increase reliability.

Security and compliance: AIOps systems were also used to improve compliance enforcement and security monitoring. These platforms could more effectively identify anomalous activity and potential security breaches by analysing a variety of data sources.

Organisations were increasingly recognising the value of data-driven decision-making, signalling a cultural shift towards data-driven operations. AIOps systems assisted in this culture change by offering data-driven, actionable insights.

Adoption difficulties: Despite the enormous advantages of AIOps, there were difficulties with integration, data quality, cultural change, and skill shortages. To use and benefit from AIOps platforms, organisations required to properly overcome these issues.

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Competitive and Segmentation Analysis:

As businesses look to improve their IT operations and management through AI-driven solutions, the AIOps (Artificial Intelligence for IT Operations) platform industry has experienced rapid growth and fierce competition. Established tech behemoths, new startups, and specialised players have all entered this industry to gain a foothold. Important businesses like IBM, Splunk, Broadcom, and Dynatrace have developed solid AIOps platforms that serve a variety of industries by utilising their considerable knowledge in IT solutions. These well-established firms frequently provide extensive toolkits that include real-time monitoring, automation, AI-driven anomaly detection, and predictive analytics.

The market has also witnessed the emergence of creative firms like Moogsoft, BigPanda, and OpsRamp, which concentrate on specialised AIOps skills and target certain pain points in IT operations. These firms frequently push the limits of what is possible in terms of AI-driven insights and automation by introducing novel viewpoints and cutting-edge technologies to the market.

The continuous developments in AI and machine learning are further enhancing the competitive environment. Businesses that can take use of the most recent innovations to provide superior anomaly detection, root cause analysis, and sophisticated automation are likely to gain a competitive advantage. Additionally, a key element for success in this industry is the capability to seamlessly interface with current IT infrastructure and other technologies in the DevOps and IT operations ecosystem.

AIOps platforms can be deployed in one of three ways: on-premises, in the cloud, or using a hybrid architecture that combines both. Deployment options are determined by an organization's existing infrastructure, security concerns, and scalability requirements.

Organisation Size: AIOps platforms serve businesses of all sizes, ranging from small and medium-sized firms to huge corporations. Smaller organisations may place a higher priority on simplicity and ease of deployment whereas larger enterprises frequently need complete solutions that can handle complex and diversified IT infrastructures.

Industry Vertical: Each industry has its own unique IT needs and difficulties. AIOps platforms can be customised to particular verticals including finance, healthcare, e-commerce, telecommunications, and more to meet industry-specific pain points and regulatory requirements.

Functionality: Real-time monitoring, anomaly detection, incident response, automation, and predictive analytics are just a few of the features that AIOps systems provide. While some systems offer a wider range of capabilities, some platforms may concentrate more on specific features, including automated incident resolution.

Geographical disparities in IT maturity, regulatory environments, and business priorities can affect the market adoption of AIOps systems. Vendors frequently customise their products to satisfy the unique requirements of several international locations.

Integration Capabilities: AIOps platforms must have the capacity to integrate with existing IT tools, monitoring programmes, and DevOps procedures. Efficiency is increased, and businesses can make the most of their current investments thanks to seamless connectivity.

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