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whitePaper | February 23, 2023

In December 2022, Rackspace Technology® polled 1,420 IT professionals throughout the world and across multiple industry verticals. Survey respondents worked in financial services, manufacturing, retail, hospitality, government and healthcare in the Americas, Europe, Asia and the Middle East.

whitePaper | August 10, 2020

2020 has posed significant, unexpected challenges to the world – and to IT departments in most organizations. Work practices have shifted rapidly and, given the volatile economic climate, many organizations are looking to protect against uncertainty and ensure business continuity by implementing cost savings initiatives. As an IT leader, you and your team are uniquely positioned to deliver added value to the organization by leveraging Technology Intelligence data to find these additional cost savings opportunities.

whitePaper | April 16, 2020

To your credit, you’ve done a little research and picked up a drawing tool here, an inspections tool, a bidding tool, and a financials tool. You’ve embraced the future or The Present, as it’s now called and are keeping abreast of ever-changing best practices.

whitePaper | September 28, 2022

Architecting IT infrastructure has never been more challenging than it is today. Many enduser workloads, such as semiconductor design, autonomous driving development, and life sciences and healthcare are growing more complex every day. With that complexity comes growing demand on IT.

whitePaper | December 26, 2022

IBM embraces five foundational pillars of trustworthy AI: Explainability, Fairness, Robustness, Transparency, and Privacy. These pillars underpin the development, deployment and use of AI systems. This document and IBM’s trustworthy AI pillars are meant to help you align on both process and outcomes.

whitePaper | December 22, 2022

Machine learning, one of the key building blocks of AI, has been a part of the technological world since the 1950s, when the earliest programmers asked computers to make sense of large sets of data. Programmers have increasingly refined the ability of machines to study data in order to detect patterns that allow computers to then organise information, identify relationships, make predictions and detect anomalies. Today, modern applications of AI have already given us self-driving cars and virtual assistants and have helped us detect fraud and manage resources like electricity more efficiently. Sectors as diverse as retail, sports, banking, manufacturing and healthcare have all found applications for machine learning and AI.