Machine Learning in 2019 Was About Balancing Privacy and Progress

It was another big year for algorithms and analytics, as data became increasingly important to the enterprise in different ways.

Terri Coles, Contributor

December 19, 2019

4 Min Read
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The overall theme of the year was two-fold: how can this technology make our lives easier and how can we protect privacy while enjoying those benefits? Natural language processing development continued and enterprises increasingly looked to AI and machine learning in 2019 for automation. Meanwhile, consumers became more concerned about the privacy of all that data they’re creating and enterprises are collecting, with consequences for businesses — especially those that rely on said data for various technological processes or must invest in ensuring its security.

This year was a big one for analytics, big data and artificial intelligence — but at the current pace of development, every subsequent year in this sector seems bigger than the last. Here are five of the leading stories in big data, AI and machine learning in 2019, with an eye to how they may continue to unfold in 2020.

Natural Language Processing Advances Continued as Alexa Makes Moves to the Workplace

The dominance of Amazon’s digital personal assistant, Alexa, in the home is clear, but this fall’s slew of new Alexa product announcements was a sign that the workplace is the logical next step. An Alexa-powered enterprise seems increasingly likely as Facebook, Google and Microsoft all put their own resources into advancing natural language processing for both voice-powered assistants and chatbots. The tech will become even more important if the growth of robotic process automation (see below) also continues and it emerges as another way to automate things in the enterprise space.

Enterprise Moved from Prep to Action on Machine Learning in 2019

In 2019, it became increasingly clear that the enterprise is past preparing for the impact of machine learning on their operations and into the time for action for organizations that want to stay ahead of the enterprise machine learning curve. According to Gartner, seven out of 10 enterprises will be using some form of AI in the workplace by 2021.

California Passed a Data Privacy and Protection Law

The country’s most populous state — and one that’s home to many tech companies — finished negotiations for its GDPR-esque California Consumer Privacy Act in September, with the law taking effect on the first day of 2020. Many tech companies put up strong opposition to CCPR, but Microsoft unexpectedly announced in November that it would apply the regulations to customers across the country. It’s a sign that the tech giant anticipates that CCPR isn’t the only law of its kind likely to take effect in the U.S., especially as the push for federal regulations continues. Microsoft recently announced a regulatory compliance dashboard in Azure and AI-powered recommendations in the Microsoft 365 admin center to include guidance for compliance with the European Union’s General Data Protection Regulation.

Geopolitics Trickled Down to Affect AI, ML and Data Privacy at Work

The world beyond the United States continued to affect the adoption and use of machine learning and big data in this country in 2019. Visa issues affected not just talent acquisition — a challenge for the enterprise in taking AI and machine learning in 2019 from the organizational wishlist to implementation — but also research, as it hampered conference travel. China’s own advancements in artificial intelligence, and the ethical issues related to data privacy that have emerged, could also affect policy and practices in the U.S. — especially as things shift to 5G. Barring a sea change in China related to data collection and use, the country should continue to affect tech adoption here in the United States in 2020.

Robotic Process Automation Continued to Make Enterprise Inroads

Robotic process automation — a group of technologies that let line of business users set up, launch and administer virtual workers sans the IT department — is still a small sector in software. Worldwide revenue was at $850 million in 2018. However, it’s also a quickly growing one because it frees up workers from routine work and cuts labor costs. As automation becomes more robust, natural language processing continues to advance quickly and data quality improves, look for this sector’s growth to continue in 2020 -- with big potential in IT and HR departments in particular. Robotic process automation is here to assume the standardized, routine tasks for any organization that generates or uses data.

About the Author(s)

Terri Coles


Terri Coles is a freelance reporter based in St. John's, Newfoundland. She has worked for more than 15 years in digital media and communications, with experience in writing, editing, reporting, interviewing, content writing, copywriting, media relations, and social media. In addition to covering artificial intelligence, machine learning, big data, and other topics for IT Pro Today, she writes about health, politics, policy, and trends for several different publications.

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