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The AI-powered research points to how an analyst’s role has become elevated over time, delivering a much more integral business impact. The project found a marked rise in a need for business skills (up 76% in the last five years versus 2009-2014), problem-solving (112%), and verbal communications skills (19%). Meanwhile, the need for Microsoft Excel (-49%), along with quantitative (-69%) and data analysis (-16%) skills, have all fallen considerably.
Interpreting the results, Sir Cary Cooper, professor of organisational psychology at Alliance Manchester Business School, said: “In the future, the business analyst will be a different person. With AI and machine learning picking up mundane number-crunching work, the role now requires more innovative and original thinking.
“This poses a challenge for employers in making sure they have people with the right skills in their workforce. As new technology comes into play, employers will need to re-evaluate the skills of their employees and develop training and recruitment practices that can make the most of the opportunities available.
“In this scenario, we will always need analysts who can ultimately make decisions based on data available. Computers are still some way off understanding, for example, the political impact of a decision, or perhaps its effect on workforce motivation. The positive effect of the influx of new technology is that analysts will be able to spend less time collating, and more time looking at the implications of their data for an upcoming investment or strategic decision.”
Chris Ganje, CEO and co-founder of AMPLYFI, said: “We are witnessing a paradigm shift in the way that a business analyst operates, whereby talented people can spend more time on strategy, and less time on repetitive tasks such as reading, number crunching, or data gathering. Advances in AI and machine learning have been the single major driver of this change, creating huge efficiencies in both time and costs.”
As part of a wide ranging study, AMPLYFI’s research found that there has been an almost 19-fold (1,876%) rise in the significance of AI in relation to analyst job roles, a major indicator that the technology is becoming more widely implemented across industrial analytics. The significance of machine learning has risen by a factor of more than 15 (1,523%). The Internet of Things (IoT, rise of 435%), neural networks (392%), and big data analytics (223%) have also climbed strongly since 2009.
Programming (up 685% in 2015-2019 versus 2009-2014) was the single biggest skills requirement riser, demonstrating the impact made from the increase in the use of digital technologies in the past decade.
