As the world continues to grow more dependent on artificial intelligence (AI), it’s no longer a question of whether to adopt AI but rather when.

With a multitude of industries using the various cloud solutions available today, let’s delve into which programming languages provide the most bang for their buck.

A deeper look at where artificial intelligence is set to go, as it disrupts business strategies and economies around the globe.

Active intelligence is a business state that is making organisations rethink what should be expected from their data and analytics capabilities.

The evolving set of practices is intended to address the shifts occurring in technology management that are being caused by digitisation.

Data fabric solves the challenge of seamlessly accessing and consuming data, and functions in distributed and remote ICT and business environments.

CIOs are familiar with the 3-2-1 rule when it comes to data protection, but it is now somewhat outdated due to the addition of immutable storage.

The close coupling of SD-WAN, SASE and SD-Branch will enhance security and lead to improved operational efficiencies in the remote-working age.

While static data analysis is still needed in most firms, dynamic analysis is not something everyone can fully grasp and deliver.

Artificial intelligence systems recognise objects, make decisions, solve problems, learn from experience and imitate examples, so what’s not to like?

Management consulting firm McKinsey’s three horizons of growth framework is a pragmatic template from which to plan sustainable business growth.

Passive BI is being overtaken by active intelligence − a state of continuous intelligence, where technology and processes support the triggering of immediate actions.