Enterprises are accelerating AI adoption at a rapid pace, but a new global report suggests many are building on unstable ground.
Cloudera’s latest research, based on a survey of nearly 1,300 IT leaders worldwide, finds that while AI use is nearly universal, most organizations still lack the data infrastructure needed to scale it effectively.
Why the gap between AI plans and execution is still impacting ROI
While it seems like every business is jumping on the AI bandwagon, Cloudera’s study shows a massive gap between what companies say they’re doing and what they can actually pull off.
Even though 96% of organizations claim they already use AI in their core business, roughly 80% admit they can’t access the data they need to make those tools effective.
This has created what experts are calling an “AI readiness illusion,” the idea that businesses are ready to scale up AI even though they haven’t fixed their basic data problems.
Cloudera’s Chief Technology Officer Sergio Gago doesn’t mince words about the situation.
In the report, Gago states, “Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments.” He further emphasizes the stakes, saying, “AI is only as effective as the data that fuels it,” and added, “You can’t do AI without data.”
Data quality, costs, and integration hurdles limit AI returns
Buying the latest AI tools is the easy part; getting them to pay for themselves is where things get tricky. When ROI falls short, IT leaders say the biggest headaches are:
- poor data quality (22%)
- unexpected costs (16%)
- trouble fitting the technology into their team’s daily routines (15%)
Data governance is another major sticking point. Only 18% of people surveyed feel their data is fully governed, meaning most companies are working with information that might be messy, siloed, or just plain hard to find.
To address this, 65% of businesses say they are increasing their cloud spending to improve performance.
For channel partners, this is driving demand for managed data services and AI-ready infrastructure to bridge the gap between tools and usable data.
Industry divide: telecom leads while public sector lags in data access
The struggle isn’t the same for everyone. Telecommunications companies are currently leading the pack in knowing where their data is, with 54% reporting total visibility.
On the flip side, the public sector is trailing far behind; only 16% of those respondents say they can access all their data at any time.
Despite these hurdles, there is significant pressure on leadership to figure it out. Most respondents (63%) believe the job of getting data ready for AI belongs to the CIO or CTO.
Despite the challenges, the report finds organizations are not in denial. Every single respondent said their organization was at least somewhat willing to adapt existing frameworks to address data readiness. More than half (54%) said they were “extremely willing.”
Leadership buy-in appears strong as well; 89% of respondents said their senior leadership understands and prioritizes the data infrastructure needed to scale AI.
What MSPs and IT channel partners need to know
For MSPs and IT channel partners, the findings reinforce a clear opportunity: helping customers move from AI experimentation to production-grade deployment will depend less on new tools and more on fixing foundational data challenges.
As enterprises increase cloud investments and prioritize governance, partners that can unify data environments, improve accessibility, and align AI initiatives with measurable business outcomes will be best positioned to capture the next phase of AI-driven spending.
For more insights into how channel partners are driving AI adoption, check out Channel Insider’s recent appearance on The Neuron podcast.