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451 Research
S&P Global
Market Intelligence
Top Considerations for AI Decision Makers
AI Decision-Makers Face Multiple Data Challenges
AI decision-makers require improved data storage visibility, mobility and performance
The amount of data used for AI/ML processing continues to grow at a rapid rate
AI/ML workload data is collected and generated in multiple venues, increasing the need for data mobility
Performance enhancements are required in multiple dimensions
A unified view of data is essential
A unified data view allows organizations to see where data is distributed and where it needs to go for processing and long-term retention
87%
Of respondents are willing to pay to have a unified view of data for AI/ML initiatives
How important is it to have a unified view of your entire data for your AI/ML initiatives?
Base: All respondents (n=687)
31%
Would pay a premium for a unified view
37%
Of digital transformation leaders would pay a premium for it
Data volume increase is a top concern
74%
Of digital transformation leaders are expecting an increase in the amount of data they use to train AI/ML models and the data used to make predictions. Only half (51%) of digital transformation laggards are expecting increases.
Rapid data growth will only accelerate, increasing the need for storage scalability and proactive management capabilities to keep workloads in check.
Data related to AI/ML workloads is collected/generated in multiple venues
82%
Of digital transformation leaders have AI/ML workload data in multiple venues.
Only 26%
Of digital transformation laggards have data in a single venue.
AI decision-makers need to be able to manage data across multiple venues including core, edge and cloud environments.
Active data sets must be quickly and transparently moved to the appropriate execution venue for rapid processing.
As data becomes inactive, archiving to lower-cost storage can reduce costs for AI decision-makers.
Performance improvements are required in multiple areas
Which performance aspect of storage would your organization want to improve the most?
Base: All respondents (n=407)
Storage systems must provide performance across multiple dimensions to meet the needs of complex workloads such as AI/ML
Sources: 451 Research's Voice of the Enterprise: AI & Machine Learning, Infrastructure 2021; Storage, Transformation 2020
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