How the role of the business analyst has changed thanks to advances in AI and machine learning
Job adverts for analysts are now more likely to ask for programming and problem solving skills, while traditional number crunching has fallen out of favour, according to research.
The business intelligence and research firm AMPLYFI analysed more than 50,000 documents held across the surface and deep web, to identify the most common skills and requirements associated with the job role ‘analyst’ between 2009 and 2019.
It found the significance of artificial intelligence had risen by almost 2,000 per cent since 2009, while there was a reduction in the need for traditional number-crunching skills. There was also a marked increase in the demand for business and problem solving skills, up 79 and 112 per cent respectively, according to the research findings.
Programming skills increased the most, up nearly 700 per cent in 2015-2019, compared to the same period five years beforehand, demonstrating the need for new digital skills in the workplace.
“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,” said CEO and co-founder Chris Ganje.
The research was carried out using AMPLYFI’s DataVoyant programme that can review millions of documents in real time from the web. The company claim the software, which uses artificial intelligence and machine learning, could transform the way we conduct research by removing bias to improve decision making.
Ganje said he was concerned that the use of “excessive consultations” in business strategy meetings resulted in an “echo-chamber” of old ideas.
Speaking exclusively to Future London he said: “We were all reading the same material and going to the same events and watching the same news anchors. I wanted to find a better way to identify future discussions.”
Ganje said the DeepResearch and DataVoyant tools visualise search results in topic clusters specific to the content you are looking for, and provide details about the types of sources listed in the results, as well as their date and location of publication. They also allow users to click through to sources to double-check the AI’s conclusions and connections. Ganje said the programme can also monitor information about a topic over time and work out associations between individuals and companies on certain topics over time.