| |December 20199AI can offer middle level managers a helping hand and reduce their workload while allowing them to make better business decisionsexecutives are increasingly relying on a diverse set of technology-based tools and techniques to enable au-tomated/semi-automated decision making as well as higher revenue generation. Among other emerg-ing technologies, AI (artificial intel-ligence) and ML (machine learning) have emerged as the indispensable part of modern business operations; especially in critical sectors such as fi-nance, legal and sales. Thanks to data driven AI, sales, finance and business development professionals have ac-cess to real-time insights and can bet-ter identify opportunities, make more informed decisions and ultimately accelerate the business growth. As chronicled in many reports, adoption of algorithm system in businesses has increased in recent years. But, one of the less talked about aspect of how data-driven algorithms are addressing the middle management issues in particular. Middle management in the age of AIAdvancements in AI seemingly pose a great threat to middle managers, sparking discussions on if middle management will become virtually extinct. However, layers of man-agement exist for a reason and their jobs can't be replaced. It's often been observed that organizations have faced a crisis following the loss of experienced middle managers who could have foreseen the impending situation. Of course, AI and machine learning can do tasks on par with hu-mans, sometimes even better in terms of accuracy and timeliness. But, they can't take over the job humans does, just not yet. On the contrary, AI-based algo-rithms can add more value to their work, enabling them to achieve their goals in less time. The skills and specs offered by middle managers are un-matched, and with their expertise combined with the accuracy of algo-rithms can truly strengthen the foun-dation of a company. Many decisions require insight that goes beyond what AI can derive from data sets alone. And, that's why human insights are irreplaceable. They can apply their knowledge, experience and cognitive skills to such critical business de-cisions as well as practices. Hence, it's safe to say that AI and other emerg-ing technologies can be leveraged to complement/support rather than to replace middle managers. AI can take the stress of mid-dle managers by performing dull, repetitive tasksMiddle managers are referred to as the `glue' that holds an organization together. They work as the bridge be-tween the senior leaders and the entry-level employees. According to data released by Great Place to Work over the span of six years, from 429 pub-licly traded companies and more than 450,000 employee responses, middle managers are the most valuable asset of any entity, irrespective of its size and industry. However, it is also the middle managers who have massive work. From planning and executing corporate strategies to organizing and redefining business goals, their re-sponsibilities are endless. Industry estimates suggest that managers across the hierarchy spend almost half their time on repetitive but important tasks, such as adminis-tration coordination. This is where AI and machine learning comes into the picture. In some sectors, in particular, AI's contribution can be huge. For in-stance, news agency Associated Press increased its quarterly earnings report-ing to approximately 4,400 from just 300 with the help of AI-powered soft-ware robots. In doing so, the journal-ists got more time to file more detailed and interpretative stories. Similarly, in any corporate setting, AI can take over dull, repetitive tasks, thus allowing the middle managers to focus on more important work. This, in turn, would push their productivity and help them hone their skills set. In today's increasingly digital era, AI's invasion is inevitable. But, this doesn't have to be bad news. Especially for middle level manag-ers as it can offer them a helping hand and reduce their workload while allowing them to make better business decisions. Ashish Shah
< Page 8 | Page 10 >