Technology Transformation Insights
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AIOps implementation challenges: obtaining business value
AIOps Implementation: Turning Hype into Value By Marzena Burakowska | February 9, 2024 As we continue our AIOps implementation challenges series, this article focuses on the three pivotal challenges in AIOps implementation: managing costs, measuring success and ROI, and navigating vendor selection and lock-in. These areas are particularly crucial when considering the overarching challenges of technology adoption, transformation cost, and long-term strategic planning ...
AIOps Implementation: Skills and Change Gaps
AIOps Implementation: Skills and Change Gaps By Marzena Burakowska | January 23, 2024 Introducing new technology to an organization is a challenging task. One of the main difficulties is the perception and capabilities of the current workforce. Often, employees are not prepared to adapt to changes due to the lack of skills or uncertainty about the innovations. This can hinder the successful deployment ...
AIOps implementation challenges
AIOps implementation challenges By Marzena Burakowska | December 11, 2023 In the fast-paced world of IT, Artificial Intelligence for IT Operations (AIOps) is revolutionizing the way organizations manage and optimize their IT infrastructures. However, implementing AIOps is not without its challenges. From data quality to skill gaps, organizations must navigate a complex landscape to claim the benefits of AIOps. Therefore I have decided ...
Leveraging AIOps to Transform IT Operations
Leveraging AIOps: Revolutionizing IT Operations in Modern Organizations By Marzena Burakowska | November 14, 2023 Modern Information Technology (IT) landscapes have evolved drastically with advancements like cloud computing, microservices architecture, containerization, and the Internet of Things (IoT), rendering the conventional manual management of IT operations less feasible. AIOps, or Artificial Intelligence for IT Operations, emerges as a solution by employing machine learning, data ...
AIOps and Data Quality: Vision for near future
AIOps and Data Quality: Vision for near future By Marzena Burakowska | October 24, 2024 Why data acquisition matters in AIOps? The data's quality and relevance determine how well AI systems can function and provide insights. But often, two significant hurdles stand in the way: unclear data requirements and inadequate validation processes. Let's explore these challenges and discover strategies to overcome them, ensuring ...
Generative AI in decision-making
Generative AI in decision-making By Marcin Burakowski | October 19, 2024 With AI reaching the peak of its hype through the utilization of generative models like GPT in the general public, many wonder if these tools can be useful within organizations. In this issue, we will specifically focus on the decision-making process of individuals in managerial or executive roles within ...
Data Readiness: The Hidden AIOps Challenge
Data Readiness: The Hidden AIOps Challenge By Marzena Burakowska | September 9, 2024 AIOps data readiness is essential for building reliable AI-driven IT operations. The quality, relevance and completeness of the data used by AIOps systems directly influence their ability to generate accurate insights, identify patterns and support better decision-making. Yet organizations often face two major challenges: unclear data requirements ...
AIOps Data Quality
AIOps Data Quality By Marzena Burakowska | June 23, 2024 In the fast-paced world of AIOps (Artificial Intelligence for IT Operations), the significance of data quality cannot be overstated. As businesses increasingly rely on AI to automate and improve their IT operations, the accuracy and dependability of the underlying data become crucial. From a data science perspective, there are several critical issues related ...