June 23, 2020 By Matthias Funke 2 min read

Market intelligence firm IDC predicts that by 2024, enterprises that are powered by AI will be able to respond to customers, competitors, regulators and partners 50% faster than those that are not using AI.[1] This is good news for frustrated CIOs and IT departments that are struggling to use the vast volumes of data from IT sources to monitor and manage incidents in real time.

Unresolved incidents can lead to costly outages, impacting client experience and revenue. AIOps enables the IT department to predict or rapidly detect issues in near real time. As workloads shift to cloud environments, AI helps cope with new complexities proliferated by cloud-native architectures. AI also helps decide what action to take, ultimately automating the remediation or resolution activity.

IBM Watson AIOps, a new product that leverages machine learning, natural language understanding, explainable AI and other technologies to automate IT operations, is now generally available. Powered by innovations from IBM Research, Watson AIOps can help businesses transition from a reactive to proactive posture. It is designed to help businesses detect issues in real time to speed incident resolution.

Early clients have already seen results from Watson AIOps. CaixaBank is a leading financial institution in Spain and Portugal, the main banking relationship for 26.7% of Spaniards and a leader in online and mobile banking in Spain. They serve more than 15.5 million customers with 5,379 branches and 9,427 ATMs and continually aim to provide a best-in-class omnichannel platform.

“Using IBM’s Watson AIOps, we’ve gotten much better at understanding some of the issues buried within our data,” says David Almendros, Artificial Intelligence Director at CaixaBank. “Being able to draw insight from within our logs and other unstructured data has helped us to progress in addressing anomalies quickly. It also has addressed a challenge our engineers have had with the task of combining and working with data and chatter across different tools. Watson AIOps brings it all together, allowing our engineers to respond faster and much more effectively.”

Watson AIOps is also being explored within IBM to speed issue detection and resolution for cloud-based SaaS applications. In a recent simulation, Watson AIOps was able to detect anomalies in real time and provide easy tracing to the root cause leveraging log data. This enabled the simulation team to have headlights into irregular activity 47 minutes before the incident occurred, an advantage over their prior process, in which root causes of detected anomalies were difficult to uncover, taking around two hours on average to understand.

Watson AIOps integrates with various best-in-class monitoring solutions to deliver holistic insights across the IT environment. It is highly customizable and uses Red Hat OpenShift to run on any cloud. With the insight and recommendations from Watson AIOps, you can improve incident resolution, drive more automation and shift your operations teams to higher-value work.

[1] IDC FutureScape: Worldwide Digital Transformation 2020 Predictions, Doc #US45569118, Oct 2019

To learn more on how you could put Watson AIOps to work for your organization, explore the Watson AIOps product page.

Was this article helpful?

More from Artificial intelligence

In preview now: IBM watsonx BI Assistant is your AI-powered business analyst and advisor

3 min read - The business intelligence (BI) software market is projected to surge to USD 27.9 billion by 2027, yet only 30% of employees use these tools for decision-making. This gap between investment and usage highlights a significant missed opportunity. The primary hurdle in adopting BI tools is their complexity. Traditional BI tools, while powerful, are often too complex and slow for effective decision-making. Business decision-makers need insights tailored to their specific business contexts, not complex dashboards that are difficult to navigate. Organizations…

Introducing the watsonx platform on Microsoft Azure

4 min read - Artificial intelligence (AI) is revolutionizing industries by enabling advanced analytics, automation, and personalized experiences. According to The business value of AI, from the IBM Institute of Business Value, AI adoption has more than doubled since 2017. Enterprises are taking an intentional design approach to hybrid cloud and AI to drive technology decisions and enable adoption of Generative AI. According to the McKinsey report,  The economic potential of generative AI: The next productivity frontier, generative AI is projected to add $2.6…

Democratizing Large Language Model development with InstructLab support in watsonx.ai

5 min read - There is no doubt that generative AI is changing the game for many industries around the world due to its ability to automate and enhance creative and analytical processes. According to McKinsey, generative AI has a potential to add $4 trillion to the global economy. With the advent of generative AI and, more specifically, Large Language Models (LLMs), driving tremendous opportunities and efficiencies, we’re finding that the path to success for organizations to effectively use and scale their generative AI…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters