data intelligence
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AI-powered business intelligence firm AMPLYFI have conducted a report on the topic of AI and the creation of human potential in data intelligence

Political uncertainty, low productivity, a tech skills gap and slow wage growth are all factors contributing to an environment that is making it harder than ever to predict the outlying events that influence future trends.

In the age of Big Data – of mega data – it appears counterintuitive that this would be the case. With all this access to information, shouldn’t analytics be easier?

The emergence of Big Data has brought with it huge positives. We now have a better understanding of how people live, how they spend their money, their approaches to services (e.g. healthcare, transport, property, etc.), what they watch and why, the skills they possess and the skills they need to possess; strategic decisions at a business and governmental level are informed by insights that, pre-Big Data, simply weren’t available.

Big Data has also spawned a new industry in itself. The data economy – the roles and businesses created by management, understanding and development of approaches to data – is worth an estimated €75 billion (£65 billion) in the UK and supports 1.65 million jobs.

However, having access to all of this data brings unique challenges. For employers and employees, the gathering and maintenance of data can be laborious and mundane. Mining vast datasets to produce analytical insights can be draining on resources and time, and draw experts away from tasks that really add value – namely the analysis that informs strategic decisions.

Companies understand that Big Data is important. In 2017, a US study found that, for the first time, more than half of businesses professed to adopt Big Data strategies. Remarkably, this was up from 17% just two years earlier. Now, we are at the stage where the majority of organisations have not only taken moves to be part of the Big Data revolution, they are reaching a more sophisticated understanding of what Big Data can offer, and how greater analytical power will unlock new opportunities and protect against potential threats to business. Traditionally, this high level of analysis and management has been costly, with the means to do so controlled by either huge in-house teams or by expensive external agencies.

Enter artificial intelligence. Interest in the possibilities that this technology can enable has never been higher. Research completed by AMPLYFI confirmed that AI data collection and analysis will be one of the key trends of 2019, but what does this mean in practice for economists, businesses and government departments?

In previous years the mention of AI, machine learning or automation evoked a picture of robots taking over, leading to a diminished need for the human workforce. Today’s reality is no Philip K Dick dystopia – technology is creating jobs, spawning exciting new industries and enabling humans to do away with mundane tasks, so that they can focus on more complex activities that require delicacy, interaction and the application of human judgement.

In analytics, this application of technology is transformative. Companies are waking up to the potential benefits of insights that can be generated from applying advanced analytical techniques, such as AI and machine learning, to the vast quantum of open source data that is becoming increasingly accessible to those with the right tools.

The advantages are numerous. First, AI has the ability to analyse datasets immeasurably larger than those within the capability of a human data worker. Where humans may interrogate hundreds or thousands of items of data, a machine can do the same to hundreds of thousands or millions of items.

Second, this analysis comes with accuracy and speed unachievable under human power. Where large teams of expensive analysts might take weeks to complete a task, leaving natural human inaccuracies along the way, the machine will take hours or days and be devoid of errors.

Third, and incredibly important for data analysis, a machine can learn and identify trends without bias. Even the best-intentioned human experts will approach a dataset with biases based on their own experiences and knowledge. A machine holds none of this bias and will learn without any previous understanding of a subject or dataset. This provides huge potential for AI-driven analysis to uncover trends and insights that a human would either discount or not even consider. For businesses looking to gain an edge on their competitors, this can be critical.

Fourth, and most significant of all, is what this means for the human. With a machine doing the predominantly menial and often lengthy task of breaking down datasets into trends and insights, humans can spend their time developing the recommendations that will come from their own data analysis. The application of AI here is not a replacement for human ability, but rather an augmentation of the work they’re already doing. Rather than reducing the need for analysts, AI capability will open up a whole new realm of analytics.

Analytical platforms will also open up the world of data analytics to new audiences; non-subject matter experts will be able to interrogate areas that previously would have been restricted to experts in their field. This, crucially, allows outside thought to challenge received wisdom in any area of business and government thinking. In this way, could AI help us bring a new view of how we organise the NHS, or what investment in skills our schools should be leading with?~

We are at a crossroads on the application of AI. As public perception to its presence becomes ever more positive, we will see it used with more sophistication across all industries, and in every corner of the globe. The beauty of its capability within data analytics is that AI-driven business intelligence is sector agnostic – the machine will learn any subject in any realm of expertise. The potential benefits from AI are huge, and it is exciting to see that organisations of all sizes are now sitting up to take notice.


Chris Ganje




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