A pair of surveys suggest that when it comes to artificial intelligence (AI) the biggest winners just might be managed service providers (MSPs) that have much needed data management expertise.
The first survey of over 830 senior data and analytics practitioners conducted by the Futurum Group finds generative and agentic AI are the top areas of investment (52 percent), followed by data platforms such as data lakes (41 percent) and data quality and observability tools (40 percent).
The second survey of 600 IT leaders across the U.S., Europe, Middle East and Africa, and Asia-Pacific regions, from Cloudera finds that 88 percent of respondents work for organizations adopting AI technologies. However, there are significant barriers to adoption, most notably security and compliance issues (74 percent), followed by a lack of proper training or talent to manage AI tools effectively (38 percent).
Data management woes threaten to derail progress
Organizations are facing a range of data-related challenges that are slowing down AI adoption. Forty-nine percent of respondents said they struggle with contradictory datasets. Thirty-six percent struggle to govern data across multiple platforms, and 35 percent feel overwhelmed by the growing volume of information. Despite these challenges, only 9 percent say all their organization’s data is accessible to AI models.
Technical issues are also contributing to the problem. Thirty-seven percent of respondents cited data integration challenges. Seventeen percent pointed to limitations in storage performance, compute power, and lack of automation, while 12 percent expressed concerns about latency.
Interestingly, while 94 percent of respondents expressed confidence in the quality of their data, 55 percent admitted they would rather undergo a root canal than attempt to access all the information their organization creates. Finally, concerns about cost are growing with 42 percent of respondents said they are now worried that AI-related expenses are becoming too high.
As more organizations look to operationalize AI, these challenges are likely to intensify. While many are adept at creating, processing, and storing data, most have never been particularly strong at managing it. That issue is now coming to a head in the age of AI, where AI-powered applications need the right data in the right place at the right time. Much like the companies that sold shovels during a gold rush, MSPs that help organizations achieve this goal are likely to generate long-term revenue equal to, or even greater than, the companies building and deploying the AI applications themselves.
MSPs face a pivotal AI data opportunity
Each MSP will need to determine the level of investment they’re willing to make in offering managed services for data used in AI applications. As organizations move forward with building and deploying these tools, success won’t hinge solely on AI expertise. It will depend heavily on the number of data engineers they can hire and retain. That’s where MSPs have a significant opportunity to step in and fill the gap at scale, potentially serving thousands of customers.
The challenge, as always, will be balancing the cost of building such a service against what organizations are willing to pay for it. In the case of AI, however, the fear of missing out remains strong. For the foreseeable future, many organizations appear willing to pay a premium for managed data services that help them stay competitive in the AI race.
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