5 Emerging Machine Learning and AI Trends To Watch in 2021

Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords that nearly everyone has heard these days. But, even those who aren’t familiar with them encounter these new technologies almost every day. Research shows that 77% of the devices that we currently use have AI built into them. From a bevy of “smart” devices to Netflix recommendations to products like Amazon’s Alexa and Google Home, AI is the force behind many modern technological comforts that are now part of our day-to-day lives.

Besides, there are tons of innovative uses for Artificial Intelligence and Machine Learning. Think of IBM’s Chef Watson that could create a quintillion possible combinations from just four ingredients. Also, AI-powered virtual nurses such as “Molly” and “Angel” are already saving lives and costs, while robots are assisting with everything, from less invasive procedures to open-heart surgery.

With the surge in demand and interest in these technologies, many new trends are emerging in this space. If you’re a tech professional or involved with technology in some capacity, it’s exciting to see what’s next in the realm of Artificial Intelligence and Machine Learning. So, let’s explore machine learning and AI trends.

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1. Increasing Use of AI and Machine Learning 

According to Gartner's 2019 CIO Agenda survey, the percentage of organizations adopting AI jumped from four to 14% between 2018 and 2019. Given the benefits that AI/ML offers in business analysis, risk assessment, R&D, and resulting cost-savings, AI implementation will continue to rise in 2020. 

However, many organizations that adopt AI and Machine Learning don’t fully understand these technologies. In fact, Forbes points out that 40% of the European companies claiming to be ‘AI startups’ don’t use the technology.

While the benefits of AI and ML are becoming more evident, businesses will need to step up and hire people with the right skills to implement these technologies. Some are well on their way. KPMG’s recent survey of Global 500 companies shows that most of those surveyed expect their investment in AI-related talent to increase by 50-100% over the next three years.  

Despite becoming so ubiquitous, AI suffers from trust issues. As businesses plan to increase their use of AI systems, they will want to do so more confidently. After all, no one wants to trust the decisions of a system that they don’t understand. 

Hence, there will be a bigger push for deploying AI in a transparent and clearly-defined manner in 2021. While companies will make efforts to understand how AI models and algorithms work, AI/ML software providers will need to make sophisticated ML solutions more explainable to users. 

With transparency becoming a key conversation in the AI space, the roles of professionals who are in the trenches of programming and algorithm development will become more critical.

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3. Rising Emphasis on Data Security and Regulations

Data is the new currency. In other words, it’s the most valuable resource that organizations need to protect. With AI and ML Being thrown into the mix, it’s only going to increase the amount of data they handle and the risks associated with it. For example, today’s organizations backup and archive massive amounts of sensitive personal data, which is predicted to become a top privacy risk for 70% of organizations in 2020. 

Regulations like GDPR and, more recently, the California Consumer Privacy Act — which became effective in 2020 — have made privacy violations very expensive. In 2019 alone, the Information Commissioner's Office (ICO) issued fines over $300M to British Airways and Marriott International for GDPR violations.  

As the pressure to meet these regulations mounts, companies will need to have data scientists and analysts on hand to stay compliant.

4. The Overlap Between AI and IoT 

The lines between AI and IoT are increasingly blurring. While both technologies have independent qualities, used together, they are opening up better and more unique opportunities. In fact, the confluence of AI and IoT is the reason we have smart voice assistants like Alexa and Siri.  

So, why do these two technologies work so well together? You can think of IoT as the digital nervous system and AI as the brain that makes the decisions. AI’s ability to rapidly glean insights from data makes IoT systems more intelligent. Gartner predicts that by 2022, more than 80% of enterprise IoT projects will incorporate AI in some form, up from just 10% today.

This trend gives software developers and embedded engineers one more reason to add AI/ML capabilities to their resume.

5. Augmented Intelligence is on the Rise

For those that may still be worried about AI cannibalizing their jobs, the rise of Augmented Intelligence should be a refreshing trend. It brings together the best capabilities of both humans and technology, giving organizations the ability to improve the efficiency and performance of their workforce.

By 2023, Gartner predicts that 40% of infrastructure and operations teams in large enterprises will use AI-augmented automation, resulting in higher productivity. Naturally, their employees should be skilled in data science and analytics or get the opportunity to upskill on the latest AI and ML technologies to achieve optimal results.

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Wrapping up

This Year 2021 only a couple of months away, we’re eager to see how these Machine Learning and AI trends play out and what innovations they bring to the table. Despite being around for a while, these technologies are far from mature. As a tech professional, if you’re looking to get on the latest advancements in technology, now is the time to learn. Our comprehensive AI Courses will equip you with everything you need to know about how AI can help you thrive in your career.

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Simplilearn is one of the world’s leading providers of online training for Digital Marketing, Cloud Computing, Project Management, Data Science, IT, Software Development, and many other emerging technologies.

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