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Artificial Intelligence. Machine Learning. Concepts that render an equal semblance of vagueness and daunt, especially to those who are still testing the unsure waters of digital transformation. With the accelerated trajectory for a highly digital economy, integrating AI and Machine Learning in the workplace is the path forward \u2013 the future of work.<\/p>\n
Efforts to advance AI and Machine Learning processes and dispel the myths looming around them are becoming more evident as today\u2019s leading organizations continue to push for these concepts in the workplace. Recent studies show that AI<\/a> is predicted to become a $266 billion market by 2027 and\u00a0Machine Learning<\/a> to grow from $1.03 billion in 2016 to $8.81 billion by 2022.\u00a0Improving efficiency and productivity is the biggest selling point of these technologies, and here\u2019s an overview of how AI and machine learning is can play an increasingly prominent role in today\u2019s economy.<\/p>\n <\/p>\n Perhaps the most commonly utilized product of AI and machine learning technology, automation delivers higher production rates and increased productivity across the many microcosms of an organization; transcending a labyrinth of processes into a well-oiled, highly-profitable machine. According to a recent study from Accenture<\/a>, AI can increase productivity by 40% or more by 2035.\u00a0Businesses of all shapes and sizes are no stranger to repetitive work, but it’s always the employees’ productivity that gets burdened from the brain-sucking toll of it all. Sooner or later, companies become an unintentional breeding ground for mindless zombies. Through automation and the use of smarter applications, we can make repetitive tasks less painful \u2013 giving employees the proper bandwidth for more meaningful and creative pursuits, for which they were initially hired for. To put it simply, with automation comes the freedom from the mundane and fatigue.<\/p>\n <\/p>\n In a competitive business landscape, data makes the world go round. But obtaining large amount of data is not the ceiling to one\u2019s competitive edge \u2013 it all boils down to interpretation and how these data are translated as valuable insights in creating a profitable business. And in the world of AI and machine learning, applications yielded from these technologies have mastered the craft of delivering data analysis to optimize best practices, isolate weak points, and identify trends that can help organizations draft long-term, big-picture goals. By creating a link between AI and machine learning technology and big data, businesses can make a better sense of how the market moves, how to disrupt it to their advantage, and build that momentum even further through predictive analytics. Twitter<\/a> is the perfect poster model on how to leverage an insurmountable amount of data; one of their primary use for AI and machine learning technology is to evaluate tweets from their users and predict recommendations and ads parallel to the personal literature they have on their timelines.<\/p>\n <\/p>\nAutomation to Boost Efficiency and Productivity<\/h2>\n
Big Data into Big Insights<\/h2>\n
Remedy for Human Error<\/h2>\n