Enhancing the Software Product Lifecycle with Sky tap Cloud

whitePaper | August 25, 2022

Businesses are in different stages with their artificial intelligence (AI) technologies. Even today, after many years of evaluating AI, only one third of organizations have actually put AI into production (31%1 ). Organizations that started somewhat later are currently prototyping their AI solutions (20%). Companies that only recently came on board with AI are experimenting with AI technologies for their business cases (25%). And a relatively large portion (24%) have only just begun evaluating AI for their business cases.

whitePaper | September 23, 2022

According to the research published by Microsoft3 on Global Customer Service, 58% of customers feel the importance of Customer Experience (CX), and 61% stopped doing business with a brand due to poor CX and go for different brands.

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

whitePaper | October 20, 2022

Artificial intelligence has already started to have an impact on urban settings at an unprecedented pace, with sophisticated solutions being deployed in the streets, at airports and in other city installations. In fact, cities are becoming experimental sites for new forms of artificial intelligence and automation technologies that are applied across a wide variety of sectors and places.

whitePaper | July 20, 2020

Privileged access is the gateway to an organization’s most valuable assets and is at the core of nearly every major security breach. Organizations must have a strategy in place to manage and monitor privileged access, as well as detect and respond to threats if they’d like to mitigate risk from today’s advanced attacks. Your application stack and infrastructure is likely quite complex and it can be hard to identify which assets are the most sensitive. And there is a never-ending supply of vendors knocking down your door competing for your time and attention. These two realities make it increasingly difficult to identify which security project to tackle next. When thinking about how to prioritize, it is advantageous to take a step back and think about your businesses goals, albeit in a slightly different way: try to envision what you would be looking for if you were an external attacker or malicious insider looking to steal sensitive data, commit Ransomware, or use your infrastructure for illicit cryptomining.

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.