Shedding light on AI and analytics blind spots

What makes a customer experience truly effective? What drives a smarter business decision or a more impactful AI initiative? Answering questions like these increasingly comes down to one core thing: data.

As enterprise operations evolve and organizations embrace cloud platforms to power AI and advanced analytics, the ability to fully harness data has become more complex, but it has also never been more critical.

For many companies, the most valuable data still resides in long-standing core transactional systems – systems that were never designed with modern analytics or AI in mind. These core systems sometimes hold decades of insights, yet poor visibility, fragmented governance, and entrenched data silos often prevent that data from being fully utilized. Adopting and translating AI and advanced analytics into favorable business outcomes starts with addressing common barriers to adoption while building trust and transparency into the framework.

Roadblocks on the path to AI and advanced analytics

Among the roadblocks to AI and advanced analytics success is data access. As organizations lean into multiple IT environments, across on-premises and cloud, data silos scattered enterprise-wide can mean an AI model, application, or analytics tool runs with faulty information.

This is particularly true when attempting to bridge the gap between mainframe systems – a place where often the most sensitive and crucial transactional information is stored – and cloud environments. In fact, Rocket Software research found that 76% of IT leaders reported difficulty accessing mainframe data and contextual metadata.

Even if an enterprise gets past that first data access hurdle, the question then turns to, “Can this data be trusted?” When dealing with multiple environments, data can move frequently from one place to another. That activity presents a data lineage challenge. What data is your AI initiative tapping into? Where did it come from? Has it been manipulated? Is it maintained in line with data governance best practices? Without an answer to questions like these, any resulting business decisions may be unreliable.

Then there’s the complex web of security and regulatory compliance that comes with effectively managing that data. These applications and tools leverage data that is often highly sensitive. As a result, organizations need to be prepared for what has become a rapidly shifting regulatory landscape—from DORA to PCI DSS 4.0.

Bringing blind spots into the light

Addressing these roadblocks boils down to how well enterprises can bridge the divide between on-premises systems and hybrid cloud environments.

Integrating the right tools can help break through these blockers. With data intelligence capabilities, like those in the Rocket DataEdge suite, IT leaders gain a powerful means to map data across their entire IT landscape, discover data more effectively, and build trust. The solution suite is purpose-built to integrate and optimize data operations across diverse environments, including mainframe, distributed, and cloud.

Solutions like this help eliminate blind spots by enabling key functionality such as real-time data streaming, transformation, and movement across systems to ensure data is accessible, trusted, and actionable wherever it’s needed. They also add automated lineage tracking and metadata management, offering a much clearer picture of how data flows through an organization, increasing trust in analytics outputs and ensuring regulatory compliance.

No matter what, AI integration can’t come at the cost of data protection. With the right data management solutions, enterprises can take advantage of embedded access controls, audit logging, and compliance frameworks, bringing each directly into their data workflows. At a time when AI initiatives are expanding rapidly, this builds a strong foundation to maintain trust and security at scale.

Elevating AI and advanced analytics

By confronting these blind spots head-on and adopting integrated solutions that work across a mix of on-premises and cloud systems, enterprises can fully unlock the value of their data.

Learn more about how Rocket Software can help break down some of the most common challenges with AI and advanced analytics.