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4 AI Trends Set To Accelerate In 2021
by Daniel Newman | November 24, 2020

There’s one thing that none of us saw coming this year — rapid digital transformation that saw years of innovation in about 5-6 months (and in some cases less). We saw companies shifting and technologies getting adopted almost overnight, and I don’t think it’s going to stop, especially in some areas like AI, which was already seeing rapid acceleration. Those of us working in the tech field see a solid expansion and development of the use of AI in really cool, important, and meaningful ways in 2021 and beyond. While the past few years have allowed many companies to dip their toe into AI, ML, intelligent automation, and other similar solutions, 2020 proved to be the year to dive in headfirst.

The proliferation of AI is happening at a great pace both at the chip level and the software level, and make no mistake; the two things are deeply intertwined. Chipmakers like NVIDIA, Intel, and Qualcomm are rapidly developing AI into their systems. This translates to greater democratization of AI that enterprise and software developers can apply to data and applications—which has been notable with cloud providers like AWS, Azure, Google, Oracle, and IBM all embedding and expanding their AI offerings for public and hybrid cloud deployments. Ultimately, this translates to more accessibility to the compute power, frameworks, and algorithms required to apply AI to everything from your smart speaker to your mobile device to your enterprise sales and planning software.

With all of this in mind, It’s my guess that the coming year will be a big year for AI growth where many AI applications themselves take off, truly delivering insights, efficiencies, and cost savings for the digital marketplace. While AI is going to continue to impact our lives in dozens of ways, from chatbots to assisted driving (ADAS), the following reflects a few solutions that I have my eye on for 2021 as we close out this year.

The Growth of RPA and AI-Driven Automation

In my 2020 digital transformation predictions, I said that RPA would catch its second wind this year. And that definitely happened. With the pandemic forcing us all to keep a close eye on budgets, businesses were turning to RPA and IPA to do tasks in order to free up employees to do other more complex things. This isn’t going to slow down in 2021 with the growth of RPA companies like UiPath.

One company, Automation Anywhere, has developed a digital assistant, AARI, which goes beyond consumer use cases to help employees learn to “connect the dots” in business processes to help expand automation. Scaling has traditionally been a difficult process for robotic process automation (RPA), with only 15% of companies using it scaling past 50 bots.) AARI also helps employees get more comfortable working alongside AI, empowering them to make their work lives better.

This has been a big focus of the RPA space as we move toward greater levels of intelligent automation that ties traditional robots used for process automation to intelligent processes powered by cloud, ML, and AI. Microsoft has been deeply entrenched in this area as well with its rapidly growing Power Automate offering. Bottom line, companies recognize the power of matching traditional process automation with AI to deliver greater efficiency and accuracy of enterprise automation efforts.

A Consistent and Accelerated Shift Toward Cyber Security and AIOps

Heading into 2021, we’ll finally be seeing AI used specifically for preventative cybersecurity and automated resolution of IT issues through AIOps. That’s huge, especially in a time when we’re seeing even more employees working from home—often on unsecured devices. Several companies like HPE have set their sights on improving AIOps to deliver what customers need. At the securities analyst meeting in October, HPE CEO Antonio Neri reaffirmed the company’s mission to continue to improve HPE InfoSight, the AIOps platform that can currently predict and resolve 86% of issues. And they’re not the only ones making headlines in the field.

This morning, IBM announced its second acquisition this week, a deal to buy Chicago-based applications performance management platform, Instana. This deal fell squarely into the AIOps category. This follows another recent announcement from the company that it was expanding its partnership with ServiceNow to make its Watson AIOps program even stronger, enabling the reduction of resolution times by 65%, according to the company’s release.

Splunk is another platform seeing massive adoption and growth in AIOps and its near neighbor Security Ops. The company, which has recently expanded its offerings to scale more rapidly in the cloud, shared its growth trajectory at its annual .Conf event where it was able to tout more than seven straight quarters of 50% recurring revenue growth, making it an even faster growth trajectory than Workday, Salesforce, and ServiceNow at the same revenue stage (~$2 Billion).

It’s clear that many innovative tech companies worldwide are making investments in this area, indicating strong momentum in this space.

Confluence with the IoT

It took a while, but we’re finally starting to see seamless confluence between AI and the Internet of Things (IoT), which has been slow to get up on its feet, at least in the way most of us initially imagined. With AI’s prevalence of sensors and its quick ability to offer actionable insights, we’ll likely see strong foundational growth in the IoT in the coming year. Indeed, in the past, the IoT may have been able to monitor and store data—sometimes enabling some type of process or automation to occur.

With the help of AI (AIoT), systems can take actions on the data it monitors, locking doors, redirecting traffic, reducing in-home air temperatures, turning off lights, etc. For instance, it’s estimated that 28% of U.S. homes will be “smart” by 2021. This is unquestionably powered by affordable sensor-driven devices, integrated UX from companies like Amazon and Google, and improved machine learning and AI that can interact with real-time data and automate processes at scale. Of course, this will scale to smart buildings, cities, retail environments, and more, as the capabilities are similar, but the data can be captured and applied uniquely to deliver everything from greater security, and improved sustainability practices, to improved customer experience and real-time offer optimization. AI+IoT is a powerful combination that is still in its earliest days.

Personalized AI for Marketing

AI needs data. Marketing needs data. Put those two together, and you open up a world of possibilities. We’ve already seen how companies can use small bits of data to target the right audience (and some real misses as well) — so much so that Apple is making companies more open about the data they collect on you. I’m going to guess even with these new data “nutrition labels,” companies will still collect bits of information to use to target you, but that targeting — thanks to AI — will be better.

Much like how AI+IoT can use data for customer experience, the intentional application of personalized AI for marketing will take this one step further. As more data continues to be collected and optimized about a customer, the ability to predict the next best action or the perfect offer will continue to improve. Add more data, and AI can learn and further infer user preference. This cycle continues, and over time, the delivery of best in class personalization is the target outcome. Companies investing in personalized AI using the best of breed tools from CX platforms from the likes of Salesforce, Microsoft, Oracle, and SAP, to rapidly growing CDP tools from Segment (Twilio), Treasure Data, and ActionIQ, will enable better customer experiences and increased company loyalty, which is the ultimate goal in digital transformation.

If one thing is clear, AI is seeing notable momentum across use cases and is becoming an increasingly “normal” part of human life, even in a year that is anything but normal. From where I’m standing, at least from a technology standpoint, 2021 looks to be another year of strong adoption and expanding use cases for artificial intelligence.

Futurum Research provides industry research and analysis. These columns are for educational purposes only and should not be considered in any way investment advice.

The original version of this article was first published on Forbes.

Daniel Newman