Machine learning is expected to become common in drug production if industry, the tech sector, and regulators put in the groundwork [Oselote/Getty …

In 2016, Google's net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its users continuously. And how does it accomplish the difficult task of observing the browsing pattern of thousands (or millions) of its users? By analysing the data, which it has accumulated by introducing machine learning to its business operating model.

Machine learning and artificial intelligence have never been as red hot as they are now, as companies apply them for use in everything from autonomous vehicles to game systems to contact center software. However, not every industry has embraced the benefits of machine learning equally. Healthcare in particular is lagging behind significantly -- unfortunate since the use of machine learning and AI can positively impact society in a big way by enabling faster diagnosis. I know some, but not all, of you are aware that in late 2016 my wife, Christine, was diagnosed with something called "common variable immune disorder," or CVID, after being sick for the better part of three years. The diagnosis came only after she had gone from specialist to specialist, having had vials of blood drawn and having been poked and prodded only to hear, "We don't know what you have but it isn't X" (X the doctor's area of specialty).

In 2016, Google's net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its users continuously. And how does it accomplish the difficult task of observing the browsing pattern of thousands (or millions) of its users? By analysing the data, which it has accumulated by introducing machine learning to its business operating model.

If you're still unsure of machine learning and it's benefits, consider these scenarios In 2016, Google's net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its users continuously. And how does it accomplish the difficult task of observing the browsing pattern of thousands (or millions) of its users? By analysing the data, which it has accumulated by introducing machine learning to its business operating model.

If you're still unsure of machine learning and it's benefits, consider these scenarios In 2016, Google's net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its users continuously. And how does it accomplish the difficult task of observing the browsing pattern of thousands (or millions) of its users? By analysing the data, which it has accumulated by introducing machine learning to its business operating model.

A decade ago, IT systems were constructed to oversee a company's finances. While they could balance the books and provide valuable information over time, the manual process of reviewing Excel spreadsheets wasn't timely, left room for error and could take months to review and develop projections. With the role of finance shifting to encompass business strategy and leadership, machine learning's value lies in a CFO's ability to gain control and use analytics to support efforts to transform the business. In today's unprecedented era of economic and regulatory volatility, CFOs need access to real-time financial information to ensure they are making informed decisions to strategically manage an organization's day-to-day operations. Automating financial processes brings the flexibility needed to move beyond the annual budget cycle to deliver insights and inform decision-making on demand.