Three Mistakes IT Makes That Could Cost Your Organization Millions

whitePaper | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.

whitePaper | December 30, 2022

The technological development of artificial intelligence (AI) is proceeding rapidly, with investment in AI-based solutions dramatically increasing across the globe. Europe is no exception.

whitePaper | March 22, 2023

Artificial intelligence is increasingly becoming a part of our everyday lives, whether at home, in industry or in the public sector. The technology poses risks, but also opens up new opportunities. This presents the institutions in Brussels with the challenge of finding a balance between innovation and regulation for AI in the EU.

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.

whitePaper | August 5, 2020

Your cloud-enabled future loomed bright. Major budgets were allocated. Agonising hours were spent herding stakeholders. You’re now using cloud, but your teams and the wider business aren’t reaping the expected benefits. Even with the best intentions, tech leaders are struggling to fill those skills gaps, particularly when it comes to cloud implementation, migration and net new deployments. As a result, the business is held back – from capitalising on the cloud’s potential to deliver value internally (boosting efficiency and agility) and externally (delivering products and services that boost revenue).

whitePaper | November 1, 2019

It's futile to deny it, but Artificial Intelligence (AI) is no longer the buzzword of tomorrow, it's a striking reality of today, and the enterprise landscape of AI has never looked more promising than it does today! Indian Enterprise Market for AI to be estimated to be $100 million, growing at 200-250% CAGR. Futuristic growth of this sort clearly underscores the potential in the big revolution that business leaders should prepare for!