AIOps Platforms Statistics 2024 – Everything You Need to Know

• According to a 2021 Rackspace Technology survey, poor data quality was the main reason for machine learning R&D failure among 34% of respondents. ^[0]

AIOps Platforms Adoption Statistics

• The most widely reported AI adoption (47%). ^[3]
• Moreover, the most widely reported adoption of AI (47%). ^[3]
• Gartner expects over 75% of large enterprises in mature economies will use container management by 2024 due to a growing adoption of cloud native applications and infrastructure. ^[4]
• That’s even higher than Forrester’s figures for adoption of what it calls “Intelligent Application and Service Monitoring,” with 51% already using and another 21% planning to adopt them within a year. ^[5]

AIOps Platforms Latest Statistics

• Moreover, according to a recent BigPanda survey, 42 percent of IT organizations use more than 10 different monitoring tools for their IT environments. ^[6]
• With the new system, utilization has increased from 70 to 92 percent, he says. ^[6]
• “It probably saved us 25 percent of infrastructure costs.”. ^[6]
• By 2024, 40 percent of companies will be using AIOps for application and infrastructure monitoring, according to Gartner. ^[6]
• According to a 2019 survey sponsored by Loom Systems, only 5 percent of companies have implemented AIOps so far. ^[6]
• And with 59 percent of organizations in the exploration phase, according to the Loom Systems report, it’s still hard for customers to figure out exactly what they’re offering. ^[6]
• According to a survey by Enterprise Management Associates, 81 percent of enterprises using AIOps report a positive return on investment. ^[6]
• In fact, 42 percent said that the value of AIOps “dramatically” exceeds the costs. ^[6]
• Now, over 50 percent of our customers are on the AIOps platform.”. ^[6]
• “Our response time to detect and take action has increased — our mean time to repair has become at least 30 percent faster after implementing AIOps,” Kamath says. ^[6]
• Gartner predicts that large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2024. ^[7]
• Europe CAGR 21.05 % Market Overview. ^[3]
• The AIOps Market was valued at USD 13.51 billion in 2020 and is projected to be worth USD 40.91 billion by 2026, registering a CAGR of approximately 21.05% during the forecast period of 2021. ^[3]
• For instance, according to IBM Security report 2020, about 54% of the organizations mentioned that they require remote working in response to Covid. ^[3]
• A recent study from New Relic found that 89% of 750 global senior IT decision makers surveyed believe that AI and machine learning are essential for how organizations run IT operations. ^[3]
• Nearly 84% have mentioned AI and machine learning will ultimately make their role more manageable. ^[3]
• According to LogicMonitor, 83% of enterprise workloads are expected to be in the cloud by 2020. ^[3]
• The company also estimated that, by 2020, 41% of enterprise workloads would be running on public cloud platforms. ^[3]
• An additional 20% are expected to be privatecloud based, followed by another 22% deploying on hybrid cloud platforms. ^[3]
• Also, on premise workloads are anticipated to shrink to 27% by 2020, from 37% in 2017. ^[3]
• The AIOps Market is growing at a CAGR of 21.05% over the next 5 years. ^[3]
• Demand for tools that can help organizations retrieve, analyze, and extract value from IT operations data will grow at a compound annual rate of 36.5% over the next several years. ^[1]
• Research and Markets 38.4 Percentage of organizations that take more than 30 minutes on average to resolve IT incidents impacting consumer. ^[1]
• Nearly one third (32.7%). ^[1]
• State of Digital Operations 39.5 Percentage of more than 300 IT personnel in development and operations who feel that the rise in digitization has made capacity planning. ^[1]
• Today’s State of Work At the Breaking Point 72 Percentage of ITSM professionals who feel that their work is not sufficiently recognized by management IT operations management roles are getting harder—and more critical to business success. ^[1]
• About 50% feel they get some, but not enough, and more than 20% feel underappreciated. ^[1]
• Although DevOps includes operations, only 13% of ITSM staff say they are fully involved in their organization’s DevOps activities; 70% say either that their involvement has been insufficient or that they have had no involvement at all. ^[1]
• Other major barriers included a reliance on manual processes (61%), a glut of tools (69%), the skills shortage (60%), and obsolete systems (62%). ^[1]
• More than half (51%). ^[1]
• About 44% believe that AI will reduce ITSM jobs, but not too dramatically, while 32% don’t see AI as a job threat at all. ^[1]
• IT operations services can help organizations in the digital transformation process, and there’s a 72% overlap between the goals of IT operations and digital transformation leaders. ^[1]
• Regardless of the business’s original data architecture and silos, data is streamed into one centralized analytics platform to analyze 100 percent of data streams and metrics. ^[8]
• By 2025, 40% of physical experience based businesses will improve financial results and outperform competitors by extending into paid virtual experiences. ^[4]
• By 2024, organizations with IT teams that understand the needs of customers will outperform other organizations’ customer experience metrics by 20%. ^[4]
• By 2024, 40% of all enterprise workloads will be deployed in cloud infrastructure and platform services, up from 20% in 2020. ^[4]
• Through 2024, enhancements in analytics and automatic remediation capabilities will refocus 30% of IT operations efforts, from support to continuous engineering. ^[4]
• By 2024, 40% of product and platform teams will use AIOps for automated change risk analysis in DevOps pipelines, reducing unplanned downtime by 20%. ^[4]
• By 2025, 50% of enterprises will have devised artificial intelligence orchestration platforms to operationalize , up from fewer than 10% in 2020. ^[4]
• By 2024, 30% of digital businesses will mandate DNA storage trials, addressing the exponential growth of data poised to overwhelm existing storage technology. ^[4]
• By 2024, 75% of organizations will have deployed multiple data hubs to drive mission critical data and analytics sharing and governance. ^[4]
• By 2025, customers will be the first humans to touch more than 20% of all products and produce. ^[4]
• By 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes. ^[4]
• By 2024, 80% of hyperautomation offerings will have limited industry specific depth mandating additional investment for IP, curated data, architecture, integration and development. ^[4]
• By 2024, more than 70% of the large global enterprises will have over 70 concurrent hyperautomation initiatives mandating governance or facing significant instability. ^[4]
• By 2025, more than 20% of all products will be manufactured, packed, shipped, and delivered without being touched —. ^[4]
• Technological progress is helping to drive hyperautomation as well Gartner expects that by 2024, organizations will be able to run a full 25% more tasks autonomously. ^[4]
• By 2024, 25% of traditional large enterprise CIOs will be held accountable for digital business operational results, effectively becoming “COO by proxy.”. ^[4]
• By 2024, 70% of customer experience projects will make use of information technology. ^[4]
• By 2025, more than 50% of organizations will use a distributed cloud option at the location of their choice, enabling transformational business models. ^[4]
• By year end 2024, 20% of installed edge computing platforms will be delivered and managed by hyperscale cloud providers, compared to less than 1% in 2020. ^[4]
• By 2024, 75% of organizations monitoring IaaS/PaaS environments will consume metrics via cloud providers’ APIs. ^[4]
• Through 2024, enhancements in digital workplace infrastructure processes driven by analytics and automatic remediation capabilities will refocus 30% of IT operations management, from support to continuous engineering. ^[4]
• By 2024, endpoint analytics and automation will help digital workplace service staff shift 30% of time spent on endpoint support and repair to continuous engineering. ^[4]
• 76% of survey respondents say that demand for new digital products and services increased in 2020. ^[4]
• Even more respondents (83%). ^[4]
• a majority of respondents to the OpsRamp survey said it takes three to six months to implement an AIOps solution, with 25% saying that it takes greater than six months. ^[0]
• 2021 AI Adoption in the Enterprise paper found that a lack of skilled people and difficulty hiring topped the list of challenges in AI, with 19% of respondents citing it as a “significant” blocker. ^[0]
• While 9 in 10 of C Suite survey respondents characterized AI as the “next technological revolution,” according to Edelman, Algorithmia found that a lack of executive buy in contributes to delays in AI deployment. ^[0]
• HPE InfoSight predicts and automatically resolves 86% of customer issues. ^[9]
• 86percentof issues automatically predicted and resolved1 of issues automatically predicted and resolved 85percentless time managing problems2 less time managing problems 54percentof problems resolved are beyond storage3 of problems resolved are beyond storage. ^[9]
• A recent survey from the AIOps Exchange illustrated both the scale of the problems AIOps was meant to solve and the level of interest in solving them, with 91% of those in the survey looking at machine learning powered tools to make ops teams more productive. ^[5]
• Interest is so high because some 40% of IT organizations in the AIOps Exchange report see over a million event alerts a day, with 11% receiving over 10 million alerts a day. ^[5]
• Abut “80% of IT leaders are looking to automate tedious tasks within incidents,” OpsRamp senior vice president Bhanu Singh told us. ^[5]
• “Most of our customers are looking at significantly cutting the cost of level one support, cutting the costs of alerts by 30% or 40%.”. ^[5]
• Because of costs, typically only 10% of an enterprise environment will use agents to collect application performance management data and that’s usually done by a DevOps team tracking customer experience with the application. ^[5]
• 80% of fortune 2000 companies rely on our research to identify new revenue sources. ^[2]
• Considering only 43% of companies across the industry are confident of their application’s performance, this is much. ^[10]
• A major FinTech leader, for example, managed to shave 61% off their costs with the help of our handy AIOps tool. ^[10]
• The same tool has also helped Ancestry, the global leader in family history and consumer genomics, achieve an average of 50% reduction in their operation costs, with no performance degradation. ^[10]
• According to Gartner, “By 2024, 40% of DevOps teams will augment application and infrastructure monitoring tools with artificial intelligence for IT operations platform capabilities.”. ^[11]

I know you want to use AIOps Platforms, thus we made this list of best AIOps Platforms. We also wrote about how to learn AIOps Platforms and how to install AIOps Platforms. Recently we wrote how to uninstall AIOps Platforms for newbie users. Don’t forgot to check latest AIOps Platformsstatistics of 2024.

Reference

1. venturebeat – https://venturebeat.com/2021/05/16/how-aiops-can-benefit-businesses/.
2. techbeacon – https://techbeacon.com/enterprise-it/20-it-ops-stats-matter.
3. marketsandmarkets – https://www.marketsandmarkets.com/Market-Reports/aiops-platform-market-251128836.html.
4. mordorintelligence – https://www.mordorintelligence.com/industry-reports/aiops-market.
5. advsyscon – https://www.advsyscon.com/blog/gartner-it-automation/.
6. thenewstack – https://thenewstack.io/the-current-state-of-aiops/.
7. cio – https://www.cio.com/article/196239/what-is-aiops-injecting-intelligence-into-it-operations.html.
8. gartner – https://www.gartner.com/smarterwithgartner/how-to-get-started-with-aiops.
9. anodot – https://www.anodot.com/learning-center/aiops/.
10. hpe – https://www.hpe.com/us/en/solutions/infosight.html.
11. opsani – https://opsani.com/resources/what-is-aiops/.
12. paloaltonetworks – https://www.paloaltonetworks.com/blog/2021/03/prisma-sd-wan-aiops/.

How Useful is Aiops Platforms

One of the key advantages of AIOps platforms is their ability to handle large volumes of complex data in real-time. Traditional IT operations management systems struggle to keep up with the vast amount of data generated by modern IT environments, leading to human error, inefficiency, and downtime. AIOps platforms, on the other hand, can process and analyze data from multiple sources at lightning speed, providing valuable insights and actionable intelligence to IT teams.

Furthermore, AIOps platforms can help IT teams proactively identify and address potential issues before they escalate into larger problems. By continuously monitoring and analyzing IT infrastructure, applications, and networks, AIOps platforms can detect anomalies, patterns, and trends that may indicate impending issues. This early detection allows IT teams to take corrective action swiftly, minimizing downtime and ensuring seamless operations.

Moreover, AIOps platforms can automate routine tasks and processes, freeing up IT teams to focus on more strategic initiatives. By leveraging AI and machine learning algorithms, AIOps platforms can automate repetitive, time-consuming tasks such as system monitoring, alert triage, and incident resolution. This automation not only increases operational efficiency but also reduces the likelihood of human error, improving overall system reliability and performance.

Another benefit of AIOps platforms is their ability to provide valuable insights and recommendations for optimizing IT operations. By analyzing historical data, performance metrics, and user behavior, AIOps platforms can identify opportunities for performance improvements, cost savings, and resource allocation. These insights empower IT teams to make data-driven decisions, prioritize tasks, and allocate resources more effectively, leading to better overall outcomes for the organization.

In conclusion, AIOps platforms have proven to be a valuable tool for businesses looking to streamline and optimize their IT operations. By harnessing the power of AI and machine learning, AIOps platforms can automate routine tasks, provide valuable insights, and proactively identify and address issues before they impact operations. As organizations continue to embrace digital transformation and adopt cloud-based, distributed IT environments, the need for AIOps platforms will only grow. Investing in AIOps platforms can help businesses stay ahead of the curve, improve operational efficiency, and drive better business outcomes in today’s rapidly evolving digital landscape.

In Conclusion

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