New Study Reveals More Than 78% of Companies Cite AI as a Key Revenue Driver in 2022
Enterprise technology leaders are investing more in artificial intelligence and machine learning, though they need solutions to obstacles blocking AI deployment at scale
PALO ALTO, Calif., January 18, 2022 – SambaNova Systems, the company building the industry’s most advanced software, hardware and services to run artificial intelligence (AI) applications, today 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.
While organizations understand AI/ML is needed to drive revenue and business goals, only a quarter of top companies report they’ve scaled their AI/ML initiatives across their organization, leaving the remaining three-fourths well behind in the next wave of technology advancement. Despite growing investment and excitement about AI driving innovation and revenue, many organizations 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.”
The research shows:
- AI/ML is important for driving revenue: More than three-quarters (78%) of respondents report that AI/ML is very important for driving revenue. Two-thirds (68%) say their AI/ML strategy is aligned with business goals; cost savings is still the top KPI to measure success.
- Deep learning (DL) is critical for new innovation: Three-quarters of respondents (75%) say improving access to deep learning is important for innovation within their industry. Organizations are exploring deep learning applications with natural language processing (NLP) (81%), computer vision (61%) and recommendation algorithms (55%).
- Enterprises 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.
- Organizations face multiple barriers to scaling AI/ML initiatives: Fifty percent (50%) of respondents say they have difficulties customizing 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.
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, organizations 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.”
SambaNova’s report surveyed 600 full-time AI/ML, data, research, experience and cloud infrastructure leaders at the director level and above In August 2021. The survey captured 100 responses from each of six key industries: financial services, healthcare and life sciences, manufacturing and auto, retail and e-commerce, public sector and oil and gas.