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Fifty-three percent of enterprise technology leaders worry that they will run out of computing power in the next decade – one of the many challenges facing organizations looking to scale up the Artificial Intelligence initiative, according to a new report from Sambanova Systems.
As AI and ML become ubiquitous in all industries, it has the potential to refine the Fortune 500 as much as the Internet has had in the last few decades. But as the AI revolution picks up speed, there is a widening gap between those who have it and those who don’t. That is, a growing number of top companies are exploring how to scale AI initiatives that can gain a competitive edge against businesses that have yet to do so.
So, why are some enterprises reaping the benefits of AI, while others are at risk of being left behind?
The report’s findings show that most people are optimistic about the potential of AI and ML technology; Two-thirds of technology leaders plan to significantly increase their AI and ML investments over the next five years. In addition, more than three-quarters (78%) say AI and ML are important for revenue growth.
But even as organizations look to AI to drive innovation and revenue, many AI and ML initiatives remain in the early stages of implementation – plenty of obstacles holding them back. More than half cite customizing AI models as their top challenge, while nearly a third blame computing infrastructure (35%) or lack of trained talent (28%).
In the years ahead, the enterprise is tasked with resolving the complexities of AI / ML scaling to keep pace with competitors. AI will only continue to expand and evolve rapidly, leaving technology leaders to determine which use cases will drive revenue and innovation for their business and identify how to deploy AI technology at the enterprise level.
For this report, SambaNova surveyed 600 AI and ML, data, research, customer experience and cloud infrastructure leaders in six industries.
Read SambaNova’s full report.
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