For several reasons, the pandemic only sped up the adoption of AI in the enterprise. Here’s what to watch in the year ahead with regard to AI talent, tools, and ethics, and other key issues: AI trends in 2021

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningPre-pandemic,  artificial intelligence was already poised for huge growth in 2020. Back in September 2019, IDC predicted that spending on AI technologies would grow more than two and a half times to $97.9 billion by 2023. Since then, COVID-19 has only increased the potential value of AI to the enterprise. According to McKinsey’s State of AI survey published in November 2020, half of respondents say their organizations have adopted AI in at least one function.

“As the grip of the pandemic continues to affect the ability of the enterprise to operate, AI in many guises will become increasingly important as businesses seek to understand their COVID- affected data sets and continue to automate day-to-day tasks,” says Wayne Butterfield, director of ISG Automation, a unit of global technology research and advisory firm ISG.

Also, IT operations faced a lot of challenges and stress in 2020 given all of the shifts toward work-from-home capabilities, and that will most likely continue in 2021. AI plays here, too: “With businesses more digitally connected than ever before,” says Dan Simion, vice president of AI and analytics at Capgemini North America, “AI can ensure that they stay operational.”

AI trends 2021: What’s happening in the enterprise

However, the focus of AI adoption will not be simply to improve the efficiency or effectiveness of operations. “There has been a visible shift towards leveraging AI to improve stakeholder experience owing to the pandemic,” says Alisha Mittal, practice director with management consultancy and research firm Everest Group.

The AI trends expected in 2021 that IT leaders should monitor include the following:

1. AI talent will remain tight

Talent supply is expected to be a key issue accompanying the accelerated adoption of AI going into 2021. “Enterprises have started realizing the importance of democratizing AI to address this persistent AI talent gap,” Mittal says.

Just as CIOs have worked to make data accessible to non-technical users, they will need to make sure AI is usable by a wider set of users. “Successful implementation of AI democratization requires focus on key aspects of data, technology, and learning strategy, supported by a decentralized governance model,” says Mittal. “Enterprises must also focus on contextualization, change management, and governance.”

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2. AI fuels self-directed IT

In 2021, we will see more AI solutions that can detect and remediate common IT problems on their own, predicts Simion of CapGemini. “These solutions will self-correct and self-heal any malfunctions or issues in a proactive way, reducing the downtime of a system or critical application,” Simion says. “This will allow teams to allocate their resources to the complex and higher-priority projects they should be focusing on.”

3. AI structures unstructured data

In the year ahead, enterprises will leverage machine vision and natural language processing (NLP) to facilitate the structuring of unstructured data such as images or emails, says ISG’s Butterfield. The goal? To create data that robotic process automation (RPA) technology can more readily use to automate transactional activity in the enterprise.

“We have seen a rise in RPA, which is the fastest-growing area of software adoption in the last 24 months. But RPA has its limitations – predominantly in that it can only process structured data,” Butterfield explains. “Using AI to complete the complex task of understanding unstructured data and then provide a defined output such as a customer’s intention will enable RPA to complete the action.”

4. IT pushes AI at a larger scale

“In 2020, we continued to observe significant AI adoption within IT organizations,” says Simion. “In 2021, I expect organizations to start to see the benefits of executing their AI and ML models – not only getting them into production, but also pushing them to scale.” One of the advantages of AI is that it can achieve ROI in real time, Simion notes, so this could be the year many organizations see their AI efforts begin to pay off. […] 

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