Industries Poised to Seek Growth with Machine Learning in 2021

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Author: Emylee Eyler
Emylee Eyler
Industries poised to seek growth with machine learning in 2021 graphic

According to a 2020 Refinitiv AI/ML Survey, 72% of respondents — including data scientists, quantitative analysts, technology and data decision-makers — say that artificial intelligence and machine learning capabilities are a core component of their business strategy and 80% reported making significant investments in AI and ML technologies. Industries like security, finance and advertising are no stranger to the benefits and possibilities within machine learning. In fact, since it was originally created in 1952, organizations have been fine-tuning machine learning capabilities to correspond with their needs. Whether that task was detecting fraudulent activity or predicting the impact of an upcoming advertising campaign, machine learning has been shown to greatly improve accuracy and efficiency while decreasing human error.

It is true that some industries aren’t prepared to fully buy-in to machine learning yet. Areas of business subject to interpretation, such as language translation, still need the perspective and attention of a human. Adrian Cohn, Head of Marketing at Smartling — a language translation technology and services company— shared his perspective with Fast Company: “Machine translation has come a long way and is evolving every day, but translations done by computer programs can sometimes alienate non-English speakers.” While some business functions may not be ready for full-reliance on machine learning yet, this technology is evolving and adding more smart capabilities to its skillset every day.

Machine learning advancements coupled with companies’ growing need for efficiency and accuracy has led to many new industries taking the leap and integrating machine learning into their business processes. Thought leaders from Brightflag and Greenlight Guru weigh in on two industries providing new and innovative capabilities with machine learning in 2021.

Legal: Spend and Budget Predictions


Historically, AI and ML capabilities in the legal sector have been largely utilized for tasks such as contract review, contract performance litigation prediction and legal research. So, widely-speaking, the legal industry knows a thing or two about machine learning.

Processes like legal spend predictions and legal matter management were traditionally outside of ML capabilities. As the legal industry shifts its focus to machine learning and big data analytics, these processes and more are now available to legal organizations. Ian Nolan, CEO and co-founder of Brightflag told VentureBeat, “For the second time in the last 15 years, companies are grappling with the legal and financial implications of a global recession. Brightflag is providing corporate legal departments with unparalleled visibility into their operations as they work to maximize the strategic value of their spending.”

The need for time efficiency, cost-savings and the importance of proactive efforts is not lost on the law industry. Machine learning innovations being brought to the industry allow these legal organizations to streamline processes and focus their time on providing better service as opposed to handling menial and time-consuming tasks. In fact, in an article for ITproportal James Loxam, Chief Technological Officer for Luminance shared that lawyers can increase time-savings of at least 50 percent from day one of the technology being deployed. By looking at the recent ML integrations alongside vast benefits associated with these technological capabilities, it is clear that the legal industry will continue its push for machine learning in 2021 and into the future.

Medical Device: Change Management


Similar to the legal industry, machine learning is fairly common within medical device companies. For example, machine learning is a key factor in wearable health technology — a smart sensor device that can predict the likeliness of heart failure — as well as imaging systems that use algorithms and data to identify skin cancer. However, as we head into 2021, more niche sectors within this industry are turning to machine learning for the first time.

Change management is one of the most cumbersome and high-priority tasks related to medical device quality management. As David DeRam, CEO of Greenlight Guru recently shared with Aithority, “28% of medical device professionals say it still takes a full day or more to run a change impact analysis. This tells us that medical device professionals are working from a reactive state that is tedious and error-prone, limiting organizations from gathering the quality insights that are needed to stay ahead of change.” To combat this, Greenlight Guru offers an AI and ML-powered change management solution.

Even the FDA has noticed the heightened focus of machine learning with the medical device industry. They have dedicated an action plan to address AI and machine learning in medical devices, proposed regulations and workshops that aim to share insights into this fast-approaching integration.

As we witness more industries integrating machine learning capabilities, it is clear machine learning will be a factor in the future of business success. Want to join the conversation around machine learning? Contact Lindsey Groepper to find out how PANBlast can help!