78% of companies see AI as a key revenue driver in 2022

Technology leaders are investing more in AI and machine learning (ML) but they need solutions to obstacles blocking AI deployment at scale, finds SambaNova

SambaNova Systems, an AI innovation company, has released a new study, “The Race to AI Value: Scaling AI/ML Ahead of Your Competition,” revealing 78% of top companies rate AI and machine learning (ML) as important revenue drivers for 2022.

Despite growing investment in AI, many organisations remain in the early stages of implementing AI initiatives and face varied challenges scaling their AI initiatives.

“To keep pace with the rapid evolution of AI/ML and deep learning, technical leaders need to determine which use cases will drive revenue and innovation for their business, and identify how to deploy them quickly at an enterprise level,” said Rodrigo Liang, co-founder and CEO of SambaNova Systems. “Those that haven’t made it a priority will need to do so in 2022 and then move quickly to stay competitive.”

Do companies have the right resources to implement AI and ML?  

75% of respondents said improving access to deep learning is important for innovation within their industry. Organisations are exploring deep learning applications with natural language processing (NLP) (81%), computer vision (61%) and recommendation algorithms (55%).

The study found that organisations are scaling up their investments in strategic technology, especially in the financial services industry. More than two-thirds (70%) of respondents plan to allocate more than $100 million of IT budget toward strategic technology goals, and almost one-third (32%) say 20% of their IT budget is dedicated to AI/ML. In the financial services industry, 81% plan to significantly increase their investments in AI/ML — the highest percentage of any industry.

Although companies are trying to incorporate AI and ML, many are facing barries which are holding them back. 50% of respondents said they have difficulties customising models, 35% have insufficient computing infrastructure to handle intensive AI/ML workloads, and 28% lack trained talent. 53% of respondents strongly agree that they’ll run out of computing power in the next decade without new architecture, while 42% say they either lack enough AI/ML engineers on staff.


Scaling up AI initiatives

IDC recently forecast that the global AI market will grow more than 18% year-over-year in 2022. As business leaders invest more time and money into AI/ML initiatives they remain challenged in taking the next steps on their AI journeys. By not untangling the complexities of scaling AI, organisations risk losing a competitive advantage that only AI technologies can deliver.

“As AI becomes ubiquitous across industries, it is driving innovation, disrupting entire markets and spurring profound transformation that has the potential to refactor the Fortune 500 just as the internet has over the past several decades,” Liang said. “To come out ahead, companies will need to scale up AI initiatives that boost efficiencies and streamline operations, as well as drive innovations that transform how people live and how business is done.”



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