Top 3 Hurdles to Getting AI (and How to Maneuver Them)

AI initiatives rarely fail because the technology isn’t powerful enough. More often, they stall long before delivering measurable impact, stuck in pilot mode due to gaps in data readiness, architecture, and long-term sustainability.

In this episode of Exchanges with Hitachi Solutions, I sat down with Evan Sotos, Senior Manager of Engineering, to break down the three most common hurdles that slow AI progress, and how organizations can move through them faster. From unclear data foundations to time-consuming infrastructure work and ongoing maintenance fatigue, these challenges are familiar to any team trying to operationalize AI.

Evan shares a practical perspective shaped by real-world implementations, along with how the Hitachi Unified Data Accelerator helps organizations bypass months of setup and complexity. By providing a proven foundation, built on best practices, flexible architecture, and preconfigured connectivity, teams can spend less time standing up environments and more time actually using their data to drive outcomes.

This conversation sets the stage for what it really takes to move from experimentation to execution, and how to build an AI foundation that’s designed to scale.

Key Takeaways

AI Stalls at the Starting Line
Most AI projects don’t fail because of weak models. Instead, they stall because the data isn’t ready. As a result, teams get stuck before they can show real business value.

Data Readiness Is Ongoing
There’s no finish line for data readiness. Instead, it depends on the outcomes you want to drive. As goals change, your data needs to evolve with them.

Setup Slows Progress
Before AI can deliver value, teams must build the foundation. That includes setting up environments, connecting data, and testing models. However, this work can take months and delay impact.

Governance Enables Scale
As AI expands, so does access to data. Therefore, strong governance is critical. Teams need clear controls for access, security, and data lineage to reduce risk.

Manual Work Holds Teams Back
Much of the effort goes into building and maintaining pipelines. Because of this, teams spend less time solving real business problems with data.

A Faster Way to Get Started
The Hitachi Unified Data Accelerator helps teams move faster. It brings together best practices, proven architecture, and prebuilt connectors. As a result, organizations can skip setup and focus on outcomes.

Less Maintenance, More Impact
Instead of adding another layer of work, the accelerator reduces it. For example, it minimizes ongoing fixes and updates. This allows teams to focus on insights and innovation.

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