JUNE 2019CIOAPPLICATIONSEUROPE.COM 19cXoinsightsDell Customer Communication Digitally Transforming IT InfrastructuresTPAUL BROOK, DIRECTOR, DATA ANALYTICS, DELL EMChe terms `Automation' and `Artificial Intelligence (AI)' are often used conversely by firms in the current technological landscape. These two computational superpowers have brought about a revolutionary change in terms of how automation capabilities drive productivity for organisations worldwide. For example, enterprises are opting for coding paradigms that provide advanced automation capabilities to overhaul business outcomes. With over 30 years of experience in this realm, Paul Brook, director of data analytics at Dell EMC, discusses his journey in the artificial intelligence landscape, highlighting the advantages of data analytics and machine learning that could add value to a multitude of business processes. What is Your View on the Ethical Aspects of AI?I would say the purpose of an industrial revolution or any advanced automation strategy is to replace with technology what has become inefficient labour; this axiom has carried great significance since the very first industrial revolution. The spinning jenny invented by James Hargreaves during the industrial revolution has had a significant impact on the textile industry by replacing manual, unproductive labour. Likewise, AI and automation reduce costs, increase revenue, and optimise workflows; these processes cut down the repetitive and mundane tasks. If you crucially analyse artificial intelligence with the same idea, it does not necessarily eliminate workforces, but on the contrary, streamlines labour, making business processes much more effective in the current day and age. AI and automation will most likely do away with mundane and repetitive tasks and help us plan strategic outcomes for a myriad of industry verticals. They have evolved into vital prerequisites of development, reducing costs and errors to bring about an improvement in quality. Along with automation comes the Internet of things, which utilises a multitude of sensors and standalone computational peripherals, coupled with data analytics and machine learning algorithms to form an ecosystem driven by automation. Adopting such strategies will enable organisations to effectively manage the already available abundance of data in order to overhaul operational workflows.
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