It's not an exaggeration to say that when it comes to the future of human progress, nothing is more important than Artificial Intelligence (AI). Although often thought to only be associated with everyday entities such as self-driving cars and Google search rankings, AI is in fact the driving force behind virtually every major and minor technology that's bringing people together and solving humanity's problems. You'd be hard-pressed to find an industry that hasn't embraced AI in some shape or form, and our reliance on this field is only going to grow in the coming years--as microchips become more powerful and quantum computing begins to be more accessible. So it should go without saying that if you're truly interested in staying ahead of the curve in an AI-driven world, you're going to have to have at least a baseline understanding of the methodologies, programming languages, and platforms that are used by AI professionals around the world. This can be an understandably intimidating reality for anyone who doesn't already have years of experience in tech or programming, but the good news is that you can master the basics and even some of the more advanced elements of AI and all of its various implications without spending an obscene amount of time or money on a traditional education.

THE BIGGEST CHANGE being brought about by AI is not human replicas, but the emergence of digital operating models. These models aren't the sexy, headline-grabbing side of AI, but they are profoundly affecting how we do business and the way leaders of the twenty-first century must think. Marco Iansiti and Karim Lakhani, professors at Harvard Business School, explore these changes in Competing in the Age of AI with examples of businesses in many industries. "When a business is driven by AI, software instructions, and algorithms make up the critical path in the way the firm delivers value." And thus, how we think about the work we do and how we compete in the marketplace. The business plan describes the problem that is being solved for the customer--a reason to buy.

"The attention around AI tends to focus on the latest technologies," Iansiti argues, "but the firms that are thriving have harnessed the subtle, inherent power of AI to break down traditional operational constraints, capture new value, and accelerate growth and innovation." What sets AI-driven firms apart is their ability to avoid the inefficiencies and bottlenecks that plague growth when complexity -- primarily caused by humans -- outstrips organizational capacity. These firms strive to construct a model for operational execution that does not require human intervention (ideally, no real-time "human bottlenecks"). In the new digital operating model, most operational tasks circumvent humans entirely. The ultimate aim is to automate and digitize as many operational processes as possible to take advantage of digital reliability and scalability.

The world's biggest companies are coming to India for data analytics, artificial intelligence (AI) and machine learning (ML) skills. But renowned mathematicians believe the country needs to significantly improve its mathematics capabilities to be able to use these technologies to create really innovative and robust solutions – both for itself and the world. Manjul Bhargava, mathematics professor at Princeton University and winner of the Fields Medal, one of the highest honours in math, says India can't hope to lead the fourth industrial revolution, "if we don't have strong mathematical talent coming up very soon." Srinivasa Varadhan, mathematics professor at New York University, agrees. He says if you want to provide some guarantee that a certain machine learning algorithm will work the way it's supposed to, then you have to do the math.

As the transformative potential of AI technologies becomes clear, companies and countries around the world are frenetically competing to become leaders. They're doing so because evidence increasingly suggests that AI will be one of the leading economic drivers of our time, with recent estimates of worldwide AI spending reaching US$78 billion by 2022--creating worldwide business value of US$3.9 trillion.1 Thanks to the leadership of a small group of academics and institutions, Canada has been an early research and talent leader in the AI space to date. But the state of Canada's leadership in AI is precarious at best. Our research shows that Canada's current efforts are insufficient if we truly want to lead in an AI-driven world and shape what it might look like. Not enough Canadian businesses are investing in AI, given its transformative potential.

Large enterprises, startups and high-performance businesses across industries are increasingly turning to Artificial Intelligence and advanced analytics to make faster, more effective, data-driven decisions. The volume of unstructured and structured data stored by enterprises is growing at an accelerating rate. The demand for skilled data scientists and candidates with AI skills is at an all-time high. Yet developing those skills typically requires significant investments of time, energy and money. Businesses are struggling to successfully deploy and manage AI projects due to lack of resources.

In the late 1960s and early 70s, the first computer-aided design (CAD) software packages began to appear. Initially, they were mostly used for high-end engineering tasks, but as they got cheaper and simpler to use, they became a basic tool to automate the work of engineers and architects. According to a certain logic, with so much of the heavy work being shifted to machines, a lot of engineers and architects must have been put out of work, but in fact just the opposite happened. There are far more of them today than 20 years ago and employment in the sector is supposed to grow another 7% by 2024. Still, while the dystopian visions of robots taking our jobs are almost certainly overblown, Josh Sutton, Global Head, Data & Artificial Intelligence at Publicis.Sapient, sees significant disruption ahead.

IBM on Tuesday unveiled a chip that is designed for the new Artificial Intelligence-powered world that requires crunching of humongous amounts of data at high speeds to get the most accurate results. Called POWER9, it uses some of the latest technologies, resulting in two significant advantages: one, increased bandwidth, and two, ability for main processors and accelerators to work coherently and simultaneously on data. Stating that it is a one of its kind in the industry, Dipankar Sarma, distinguished engineer, Linux Technology Center, IBM Systems, said the new chip doubles the bandwidth by which one can get more data really fast. "We significantly increase the ability to process data; five to 10 times faster," he said. He spoke of two applications.

In the late 1960s and early 70s, the first computer-aided design (CAD) software packages began to appear. Initially, they were mostly used for high-end engineering tasks, but as they got cheaper and simpler to use, they became a basic tool to automate the work of engineers and architects. According to a certain logic, with so much of the heavy work being shifted to machines, a lot of engineers and architects must have been put out of work, but in fact just the opposite happened. There are far more of them today than 20 years ago and employment in the sector is supposed to grow another 7% by 2024. Still, while the dystopian visions of robots taking our jobs are almost certainly overblown, Josh Sutton, Global Head, Data & Artificial Intelligence at Publicis.Sapient sees significant disruption ahead.

A panel of experts at the recent 2017 Wharton Global Forum in Hong Kong outlined their views on the future for artificial intelligence (AI), robots, drones, other tech advances and how it all might affect employment in the future. Their comments came in a panel session titled, "Engineering the Future of Business," with Wharton Dean Geoffrey Garrett moderating and speakers Pascale Fung, a professor of electronic and computer engineering at Hong Kong University of Science and Technology; Vijay Kumar, dean of engineering at the University of Pennsylvania, and Nicolas Aguzin, Asian-Pacific chairman and CEO for J.P.Morgan. A fundamental problem is that most observers do not realize just how vast an amount of data is needed to operate in the physical world -- ever-increasing amounts, or, as Kumar calls it -- "exponential" amounts. "To have electric power and motors and batteries to power drones that can lift people in the air -- I think this is a pipe dream.