This year, the majority of businesses failed to scale their AI deployments, but, will 2022 be the year when this happens? What does the next year have in store for AI? With the rise of augmented intelligence, AI in IoT, and a pivot to hyper automation, 2022 will definitely bring a lot to the table for artificial intelligence and machine learning.
In 2021, businesses expected artificial intelligence (AI) to help them make faster and better predictions in order to achieve a competitive advantage. Despite their best efforts, the majority of businesses have been unable to expand AI deployments across their organizations. However, AI is rapidly evolving, with the goal of delivering on its promise by 2022. Companies will overcome the challenges of implementing AI with a new wave of technology developments.
Mike Potter, CTO of Qlik says, “I see AI and machine learning (ML) gaining more widespread understanding and implementation, as they offer a tremendous upside to organizational ability to leverage data to plan for the unexpected.”
“Many times, there are elements of AI and ML already implemented within more modern business intelligence systems. With a commitment to becoming real-time, data-led organizations, business leaders are in a better place to have the right data they need to better leverage AI and ML within analytics for decision making,” he adds.
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Here are some of the innovations to look out for in the coming year.
Data scientists in 2021 spent majority of their time cleaning data, integrating different storage systems, and determining the storage capacity and processing power required to deploy AI and machine learning (ML) models. Because most models were constructed in a sterile setting with clean data, a significant amount of highly trained human resources were spent fixing operational concerns. Because of a lack of understanding of the complexities of integrating real data, models that were put into production did not perform as expected.
Data scientists can expect some reprieve in 2022, as more and more machine learning tasks become automated. In the coming year, many labor-intensive operations that entail repetitive and time-consuming functions will begin to be automated. Not only would automating the process results relieve data scientists by allowing them to focus on what they do best — improving algorithms — but it will also allow IT teams to deploy higher-performing AI/ML models faster.
Previously, only large corporations had the financial resources to make AI/ML models a reality. In 2022, developers at midsize businesses will employ more off-the-shelf technology to make AI/ML models more accessible. Making applications talk, automating video and picture analysis, converting speech to text, automatically removing illegal or improper content, and many more industry-specific use cases will all be possible.
Furthermore, when bring your own computing and storage (BYOCS) becomes a reality, there will be fewer hassles when selecting and porting AI software to different platforms. AI developers will be able to select the best compute and cloud solution for each machine learning model as AI/ML models consume more resources. Choosing the most efficient platform avoids vendor lock-in and gives data scientists the flexibility they need to optimize computing resources while also allowing them to experiment with new, innovative technologies without jeopardizing their entire AI/ML ecosystem.
Most businesses were still in the proof-of-concept or experimentation stages of AI in 2021. There will be a move towards AI-first initiatives in the coming year. Artificial intelligence (AI) applications will be at the forefront of business initiatives. Companies will see a steeper curve of development as AI/ML models become the standard, expanding AI to every department and touching every business function.
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AI will not only be more common, but it will also be more strategic in 2022. AI will be utilized to boost productivity in the future. Additionally, AI will be leveraged to rethink and rebuild services, products, business models, and overall strategy in the coming year. AI will not be a bolt-on to an existing infrastructure, but rather an essential element of a company’s technology stack, giving real-time insights to partners, employees and customers.
In 2022, organizations will strive to employ AI insights to become more competitive by being completely data driven, thanks to the new online economy. The increased research and development by big corporations will result in more innovation bringing AI within reach of smaller businesses as well.
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Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.
