A good read. The words from AI vendor execs, including Mark Bryan and Wilson Pang of Appen instill confidence towards the future, specially the way things are turning in 2022. Hopefully Mark and Wilson can show similar confidence in Appen's future in the next FY report.
https://www.enterpriseai.news/2022/01/07/2022-technology-predictions-for-ai-in-the-enterprise/?utm_campaign=coschedule&utm_source=linkedin_company&utm_medium=Appen
The global use and further development of AI continued to grow in 2021 as enterprises found more ways to deploy it and developers discovered new ways to capture its possibilities for business users.
So, what might 2022 bring for AI and a wide range of related IT fields from MLOps to security, cloud and edge computing, open source, the metaverse and more?
To answer that question, we received a wide range of predictions from IT industry experts who shared their thoughts with EnterpriseAI. We are publishing them here, edited for clarity and brevity, to give our readers an early look at what may come in 2022 in enterprise AI and related technologies.
Rodrigo Liang, the CEO and co-founder of AI platform vendor , said he sees companies moving away from DIY AI and linking up with vendors who can help them better reach their business goals.
“Organizations recognize the talent shortage and internal inertia to technology advancements adds significant performance risk,” said Liang. “As a result, traction for AI-as-a-Service expands allowing for investment in applying insights over creating those insights. How many companies are going to be able to afford to hire hundreds of people just to manage one model and have thousands of GPUs interconnected to run one thing?”
In addition, business verticals including banking, financial services, insurance and manufacturing will further deploy AI in transformative ways to bolster their performance and operations and will never look back, said Liang. “Just like how the internet changed every facet of commercial transactions, AI will have the same level – if not more – of an impact. These industries will move from test deployments to production and will earn the returns promised with AI.”
Mark Brayan, the CEO of machine learning data training vendor , said that in 2022 he sees the idea of “responsible AI” shifting from an aspiration to a foundational requirement for most AI projects.
“In 2021, responsible AI was one of the hottest topics in the AI industry, but adoption remained relatively low,” he said. “In 2022, however, the stakes become much higher, as businesses recognize that responsible AI leads to better business outcomes. The principles of responsible AI are now well-established: unbiased data, fair treatment on the data collection and labeling side of the industry, and a recognition that AI projects should promote the social good, or at least avoid the potential for social harm. Implementing these principles ensures that AI projects work as expected and protects the brand.”
In addition, said Wilson Pang, Appen’s CTO, the new year will also see model evaluation and tuning going mainstream for enterprises.
“In 2022, the need for regular model evaluation and tuning becomes AI program table stakes,” said Pang. “Machine learning models are dynamic – they cannot be deployed and forgotten. ML models in production need to be updated and retrained based on a variety of factors, including the ongoing results, as well as changes in infrastructure, data sources and business models.”
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