Artificial Intelligence (AI): What’s In Store For 2021?

 Side face of AI robot network with data.

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This was a banner week for AI (Artificial Intelligence). The reason? Well, C3.ai came public and soared on its debut. It’s certainly a validation of the importance of enterprise AI. Keep in mind that C3.ai provides comprehensive software solutions and services for a myriad of large companies, including 3M, Royal Dutch Shell, Raytheon, Baker Hughes, and condition.


“The use of AI and data analytics will become increasingly important in IT as organizations aim to deliver seamless support and predictive capabilities,” said Amit Sawhney, who is the Vice President of Services Operations at Dell Technologies.


So then, given all the investment and innovation, what might we see next year with AI? As should be no surprise, there is quite a bit. So let’s take a look:


Sri Viswanath, the Chief Technology Officer of Atlassian:


“In the next 5 years, increased data and privacy regulation will have a big impact on the way we design AI/ML models. As a result, investment in data management is going to be critical in determining the success of AI systems. Companies that have better data management frameworks, platforms, and systems will win in building effective AI tools.”


Anand Rao, the Global Artificial Intelligence Lead at PwC:


“Our latest AI research shows 86% of businesses currently reaping the benefits of the better customer experience through AI, and 25% of companies with widespread AI adoption expect to see the tech payout in increased revenue during 2021.  The pandemic has uncovered the value of AI, lending itself to enhancing tasks related to workforce planning, simulation modeling, and demand projection.”


Rohan Amin, the Chief Information Officer at Chase:


“In 2021, we will see more sophisticated applications of artificial intelligence and machine learning (AI/ML) across industries, including financial services. There will be greater integration of AI/ML models and capabilities into multiple business processes and operations to drive improved insights and better serve customers.”


Kimberly Nevala, the AI Strategic Advisor at SAS:


“AI adoption will continue to gain traction in 2021 with emphasis on decisions that are not at the mercy of seismic shifts resulting from the ongoing pandemic. The focus will remain on applying AI to automating and augmenting core business processes where the problem space is relatively stable and desired outcomes are well-bounded. While this may seem reactionary, this continues a 2020 trend in which AI adopters at all levels reported that enhancing existing products and services was their number one AI priority.”


Wilson Pang, the Chief Technology Officer at Appen:


“In 2021, we’ll see organizations moving past just acknowledging and ‘worrying’ about bias in AI and start to make more significant moves to solve for it–because it will be required. Specific teams and/or initiatives will be formed to combat all the concerns that fall under the umbrella of responsible AI, including everything from inherent bias in data to treating data trainers fairly.”


Michael Berthold, the CEO, and co-founder of KNIME:


"Because cloud and hybrid environments will become much more prevalent, data science will have to adapt. It will need to be conducted in a variety of environments and shared across them in order to maximize effectiveness."


Steve Grobman, the Chief Technology Officer of McAfee:


“Advances in AI technologies, including generative adversarial networks, will make disinformation through fake content, such as deepfake videos and auto-generated social media posts, virtually indistinguishable from real content.” 


Ram Chakravarti, the Chief Technology Officer at BMC:


“In 2021 we will see the impacts of AI on today’s enterprise via pervasive intelligence. This will have significant effects on how companies approach enterprise automation as well as their basis for the growth strategy.”


Peter Reinhardt, the CEO, and co-founder of Segment:


“Consumer companies, which tend to have more traffic and data than B2B businesses, will see the most (and quickest) improvement in their AI/ML applications if they test with customers and iterate. While these use cases (e.g. content ranking) may not seem futuristic, they will drive meaningful business impact.”


Bill Scudder, the General Manager of AIoT Solutions at AspenTech:


“In 2021, we’ll see more industrial organizations increase investment in lowering the barriers to AI adoption by deploying targeted embedded Industrial AI applications that combine data science and AI with purpose-built software and domain expertise. This will be the key to overcome a lack of skills and drastically reduce the need for many data scientists.”


Scott Prevost, the Vice President of Engineering at Adobe Sensei:


“The most powerful application of AI will be the complement of human EQ with machine IQ–where human ingenuity will merge with the power of machines to enhance human creativity and intelligence (not replace it). AI is evolving from being another technology in one’s arsenal to a virtual ‘co-pilot’ that can help businesses achieve their goals faster and streamline consumer workflows.”


Clemens Mewald, the Director of Product Management of Machine Learning and Data Science at Databricks:


“We’ll see enterprise customers moving away from building their own machine learning platforms, recognizing that it’s not their core competency. They’ll realize that more value comes from applying ML to business problems versus spending the time to build and maintain the tools themselves.” 


Bob Friday, the Chief Technology Officer at Mist Systems, a Juniper Networks company:


“Cloud and AI will turn the customer support between both the enterprise and their customers/employees and between the enterprise and their infrastructure vendor upside down. With cloud AI, the vendor will let the enterprise customer know when there is a hardware or software problem. The days of arguing with their vendors on hardware and software problems are over.”


Michael Beckley, the Chief Technology Officer and co-founder of Appian:


“Software vendors and AI providers such as Google and AWS will continue to strip the complexities out of operationalizing AI by using low-code techniques. In 2021, the use of broadly-applicable and high-value use cases like AI-enabled Document Processing will become widespread.”


Jason Tan, the CEO of Sift:


“In 2021 we will see a marked increase in the number of lawsuits filed implicating artificial intelligence technologies. While we’ve seen high-profile suits brought against companies over the last few years, AI is simply more prevalent in our everyday lives. As an immature technology, we’re going to see AI systems make more (and new) mistakes that carry real human impact. When mistakes are made, consumers will take legal action.”


Tim Tully, the Chief Technology Officer at Splunk:


“More and more is happening at the edge, because we can do more and more computation as the hardware and software get more sophisticated. Local processing reduces the latency of moving the data to the cloud to process, and you get the same results.”


Christine Boles, the Vice President of the IoT Group and General Manager of the Industrial Solutions Division at Intel:


“The pandemic has greatly accelerated the need for companies to complete their Industry 4.0 transformations with solutions that allow them to have more flexibility, visibility, and efficiency in their operations. We’ll see an acceleration of adoption of solutions that help address that need, ranging from AI including machine learning, machine vision, and advanced analytics.”


Dr. Rana el Kaliouby, the co-founder and CEO of Affectiva:


“Emotion AI software that can understand nuanced human emotions and complex cognitive states based on facial and vocal expression will address some of technology’s shortcomings in light of the pandemic, and we’ll see companies using it for new use cases.”


Rick Rider, who is the Vice President of Product Management at Infor:


“In the unpredictable job market of 2021, it will be critical for organizations to leverage AI to ensure they find the right candidate for the job. AI will enable HR departments to become more proactive in their hiring and help them determine a candidate’s cultural fit by using data to measure the quality of hire.”


Richard Tomlison, the Senior Director of Product Marketing at DataRobot:


“In 2021 we expect budgets to be consolidated and organizations will be looking to minimize the number of AI software vendors they deal with. The market has moved from point solutions and towards full solutions with end-to-end value. It is no longer acceptable or even feasible to have multiple disparate products solving multiple disparate problems.”


Flavio Bonomi, the Board Advisor to Lynx Software Technologies:


“2021 is the year where AI will get embedded into existing devices and make certain functionality faster and more accurate as standard. Sensors can now detect any of the five senses (yes, including smell) and we will see AI increasingly applied to all of those. Examples include the ability to detect vibrations or unusual noises in a factory that ensures maintenance is performed on equipment prior to it malfunctioning. Not as sexy or as obvious as a self-driving vehicle, but practical and with a measurable ROI.”


Jason Shepherd, the Vice President of Ecosystems at ZEDEDA:


“The TinyML conversation that started heating up in late 2019 will reach full-on buzz in 2021. This means more on-device processing, including in smart cameras, and further realization by the telcos and traditional IT players that not all edge processing will happen in a data center.”


Jan Gilg, the President of SAP S/4HANA:


“In 2021, we will continue to see companies leverage data and intelligent technologies to realize smart, data-driven insights that they have never had access to before without a large-scale implementation.”


Dan Simion, the Vice President of AI and Analytics at Capgemini North America:


“In 2021, we will see an evolution of AI solutions to solve technical problems automatically and without human intervention. This self-healing mechanism will self-correct malfunctions proactively to keep critical applications operational and reduce the risk of systems shutting down.”


Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction and The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems. He also has developed various online courses, such as for the COBOL and Python programming languages.

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