Your digitally enabled workforce is swimming in communication at every turn. From email, Slack, Jira and back, there is no end to the volume of text and data corporate employees are tasked with reading. Is it any surprise that our reading habits have changed dramatically over the last decade? It turns out the modern workforce tends to skim and skip rather than read deeply for comprehension and introspection. Many digital influences, from our habitual scrolling through social media to the frantic pace of all-day meetings, have trained employees to minimize diligent reading and thorough comprehension practices.

Not biased or compromised by historical baggage, personal relationships or having to worry about their next job. In September, Dictador – a global spirits company – got exactly this type of leader when they placed an AI in the CEO's chair.1 Teneo's 2023 global CEO and Investor Outlook Survey demonstrated a resounding interest in the future of AI by CEOs and the investors who empower their agenda as a strong area of big bets for innovative tech. Half (48%) of CEOs from the world's leading public companies have already adopted AI, with another 58% actively investing to strengthen their AI capabilities. These systems have brought the world of frictionless autonomous computing to the masses and are beginning to challenge the fundamental understanding of what computers can do and what it means to create anything, from executive speeches to works of art, from lines of code. The success of these platforms has sparked an arms race with Google, Microsoft and others racing to incorporate or duplicate these technologies within their core products.

Although the capabilities of Artificial Intelligence vastly outweigh human capacity in rapidly analysing data, it is crucial to understand the limitations. The primary advantage of AI encompasses the proficiency in outputting patterns and decisions, gathered through the quick analysis of information. Contrary to this, traditional decision making by humans encompass a more experience orientated approach, taking the alignment of morals and ethics into consideration. By approaching this through numerous lenses, and considering the different stages of machine learning; Artificial Intelligence, machine & deep learning, we can understand the position & potential of AI in corporate governance. Exposing a unique risk, the basis for AI learning stems from man-made data, and can experience a sense of bias and human error in early stages.

Upside AI is one of the first funds in India to use machine learning to make fundamental investing decisions. The company was founded on the belief that technology will make better decisions than humans over the long term since machines are unbiased and unemotional decision-makers. Founded in 2018 by Kanika Agarrwal, Nikhil Hooda and Atanuu Agarrwal, Mumbai-based Upside AI uses technology to understand, recognise, and buy companies that are not only fundamentally good businesses but are also in-demand stocks. After two years in development, in July 2019 Upside AI came out of beta to start offering its investment products under a SEBI registered PMS license. For this week's startup column, we got in touch with one of the founders and Chief Investment Officer of Upside AI, Kanika Agarrwal to gain a more in-depth insight into how it drives AI and machine learning to provide fundamental investing. The algorithms then, over millions of portfolio iterations, learn how to pick companies that are not only fundamentally good businesses but also in-demand stocks.

Services that Blend Technology and People Are Optimal. Someday in the future complex processes will be able to operate without human intervention. Many complex autonomous processes won't occur in my lifetime. I don't consider warehouse robots nor autonomous vehicles to be terribly complex, it's more a question of repetitions (vehicle miles traveled).

This post by Parijat Garg, CFA was originally published on CFA Institute's Enterprising Investor. To a quantitative investor, discretionary investing is ridiculously subjective -- rife with confirmation bias, availability bias, base-rate ignorance, and more. To the discretionary investor, on the other hand, quantitative investing is hopelessly naive. A company is more than its price to book and return on capital employed. The worlds of these two investors are like East and West.

IT'S robots that mostly come to mind when you ask people about the future of work. Robots taking our jobs, to be specific. And it's a reaction that's two centuries old, in a replay of Lancashire weavers attacking looms and stocking frames at the start of the first Industrial Revolution. A secondary reaction, among a much smaller group, is the creation of new jobs in the coming fourth Industrial Revolution. On the left side are old industries, where some workers are being replaced by robots.

Just as artificial intelligence is helping doctors make better diagnoses and deliver better care, it is also poised to bring valuable insights to corporate leaders -- if they'll let it. At first blush, the idea of artificial intelligence (AI) in the boardroom may seem far-fetched. After all, board decisions are exactly the opposite of what conventional wisdom says can be automated. Judgment, shrewdness, and acumen acquired over decades of hard-won experience are required for the kinds of complicated matters boards wrestle with. But AI is already filtering into use in some extremely nuanced, complicated, and important decision processes.