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?
YesNo

More from Artificial intelligence

AI transforms the IT support experience

5 min read - We know that understanding clients’ technical issues is paramount for delivering effective support service. Enterprises demand prompt and accurate solutions to their technical issues, requiring support teams to possess deep technical knowledge and communicate action plans clearly. Product-embedded or online support tools, such as virtual assistants, can drive more informed and efficient support interactions with client self-service. About 85% of execs say generative AI will be interacting directly with customers in the next two years. Those who implement self-service search…

Bigger isn’t always better: How hybrid AI pattern enables smaller language models

5 min read - As large language models (LLMs) have entered the common vernacular, people have discovered how to use apps that access them. Modern AI tools can generate, create, summarize, translate, classify and even converse. Tools in the generative AI domain allow us to generate responses to prompts after learning from existing artifacts. One area that has not seen much innovation is at the far edge and on constrained devices. We see some versions of AI apps running locally on mobile devices with…

Chat with watsonx models

3 min read - IBM is excited to offer a 30-day demo, in which you can chat with a solo model to experience working with generative AI in the IBM® watsonx.ai™ studio.   In the watsonx.ai demo, you can access some of our most popular AI models, ask them questions and see how they respond. This gives users a taste of some of the capabilities of large language models (LLMs). AI developers may also use this interface as an introduction to building more advanced…

IBM Newsletters

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