I often like to say data is like water. The reason for this is that it is constantly flowing, you cannot survive without access to it, and it is constantly being used, cleaned, and recycled. Dirty water, however, is largely unusable – left to stagnate in water tanks or storage, it is quickly forgotten about and thrown away. But when we treat that water with care and make sure it is clean, we allow for the reallocation and consistent use and re-use of it in very different ways in everyday life. Data is exactly the same. If businesses do not have the right data, which is accessible, clean secure and consistent, AI projects will not survive.

Successful Artificial Intelligence (AI) initiatives require both structure and agility. Structure is critical to ensure that all aspects of an AI project are covered. Agility is crucial to learn and improve throughout the project. This requirement results into 12 iterative stages to ensure that AI projects contribute to the organisational strategy and deliver sustainable value.* The governance defines the boundaries of the project with respect to resources (both human and technical), scope, costs and time lines.

Data repositories can help businesses organise their data and improve its quality. Standard Bank of South Africa raised the quality of its data from six per cent to 98 per cent using IBM DataOps software. It now has a data catalogue to help it meet regulatory and compliance requirements. Before working with IBM, the bank which operates in 20 countries in Africa and has reported assets of approximately US$157 billion in 2019 was investing tens of millions of dollars on data fixes in disparate places, says Simphiwe Phakathi, Executive Head: Relationship Banking PBB Africa Regions at Standard Bank Group & Dumisani Mthimkhulu, Head of Data Asset Management Platforms at Standard Bank Group. "We needed a disciplined data lifecycle approach that was sustainable."

While neural networks seem to get all the glory, data is the unsung hero of AI projects – data lies at the heart of everything from model training to tuning to selection to validation. No matter how compelling the business case, or talented the team, without high-quality data, AI projects are doomed to fail. An example from the field of computer vision illustrates the challenge. While we marvel at the accuracy of image classification models such as vgg16 and ResNet[2], we may take it for granted that a database with over 14,000,000 hand-annotated images exists to train these models. These are hardly random images – rather, they are organized based on a similarly expansive effort called WordNet, an effort to build a lexical database for the English language started in 1985[3].

As enterprises enthusiastically invest in artificial intelligence (AI) and intelligent automation technologies to achieve productivity gains and other business objectives, the critical role that humans play is sometimes overlooked. Here, I'll explain why putting humans at the heart of every AI project, also known as a "human-in-the-loop" approach, is critical to success. Elon Musk learned an important lesson last year when Tesla was investing in robotics and other advanced technologies to ramp up production of its Model 3 electric vehicle. After initially trying to build the most automated automobile production facility in the world, Tesla failed. In an interview, Musk willingly admitted where he had gone wrong: "Yes, excessive automation at Tesla was a mistake.

"TensorFlow is by far the most popular tool among our respondents, with Keras in second place, and PyTorch in third. Other frameworks like MXNet, CNTK, and BigDL have growing audiences as well" As if businesses today didn't already have enough to worry about, then along comes a new wave of game-changing technologies that they must master quickly if they are not to fall behind their competitors, with pressure mounting to start using AI. . Artificial Intelligence is the most visible of these technologies – and arguably the most important. Open a newspaper, and it might seem as if every business is making great strides towards developing and using AI applications that will transform their operations and enable them to deliver new products and services to their customers. It's easy for businesses yet to achieve success by using AI – or even to get started on their journey – to get despondent about the lead they perceive their competitors to have.