A PERSPECTIVE ON IT COST MANAGEMENT

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.

whitePaper | December 15, 2019

Artificial Intelligence (AI), and specifically Machine Learning (ML), are being tested in an increasing number of fields, including data-centric environments. Image or text analysis, speech recognition, chatbot interactions, custom machine learning models… all these are elements that could enable the AI journey of a public safety and security organisation. This document dives into different aspects of integrating AI & ML in Public Safety activities, at different levels and in different domains of activity. It presents ethical and regulatory considerations, real examples from Public Safety Answering Points (PSAPs) and Emergency Response Organisations (EROs), and also initiatives that can benefit the public sector greatly, with a series of recommendations at the end.

whitePaper | October 21, 2022

Oracle APEX is the world’s most popular low-code application platform for enterprise apps. It’s free to use with any Oracle database or database cloud service. Using a browser-based builder, you and your team create modern data-centric web apps that are reliable, scalable, and secure. End users access them with desktop or mobile browsers or install them like native apps in one click. Every day APEX developers the world over help each other succeed. They produce everything from small departmental apps done by one or two people, to complex, business critical systems engineered by a team of IT professionals.

whitePaper | November 30, 2019

The report on “Understanding the Dynamics of Artificial Intelligence in Intellectual Property” prepared by the Tata Consultancy Services in close association with the Confederation of Indian Industry (CII) captures global developments, practices of various intellectual property offices of the world, technology landscape and research outlook. This publication on IPR would provide useful information to educational & research institutions and industries doing research in this area and fill up gaps for moving forward. CII firmly believes that IPR should be at the centre stage in competing in the world of artificial intelligence in a meaningful manner. The report highlights an important recommendation that, “With evolution of new technology, it is essential to have change in the IP creation and protection ecosystem by mechanisms to develop new doctrines for new technologies, modifying the existing system to accommodate this new change and reshaping of new policies for enforcement of IPRs”.

whitePaper | September 28, 2022

As the speed of enterprise operations surge and expectations for quick responses rise, decision making increasingly migrates from data centers to the network’s edge. Whether it’s on the shop floor, where busy production lines must not stand idle, a doctor in a surgical suite waiting for answers, a fire crew needing orders to fight a frantically advancing wildfire, scientists looking for insights that will help a recovering coral reef, or a retail environment where impatient customers wait for help in making a purchase, enterprises must configure their systems to collect information, to develop actionable insights, and to provide decisions or answers in real time.

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.