As enterprises increasingly turn to artificial intelligence to maintain a competitive edge, the challenge of preparing vast, often siloed, data reserves for AI applications comes to the forefront. Legacy infrastructure, coupled with the complexities of hybrid cloud environments, can hinder the agility required for successful AI integration. Addressing this, technology advisory firm Ensono is emphasizing a foundational approach focused on data mobility, enabling organizations to access and utilize their data assets across disparate systems securely and efficiently.
This strategy hinges on creating a fluid data environment where information can be extracted, processed, analyzed, and reintegrated seamlessly, regardless of whether it resides on a mainframe, in a private cloud, or on a public cloud platform. According to Ensono, true AI readiness is achieved not by first selecting a tool, but by first organizing data and establishing robust frameworks that allow for intelligent data orchestration. This method ensures that as businesses adopt AI, they are building on a resilient and scalable foundation, transforming their IT infrastructure from a simple support function into a strategic enabler of innovation and growth.
Modernizing Legacy Systems
A significant hurdle in enterprise modernization is the deep-seated reliance on legacy infrastructure, which often houses mission-critical workloads. Ensono advocates for a hybrid cloud transformation strategy that allows these core systems to operate efficiently while the organization progressively adopts modern platforms. This dual approach avoids the risks of a “one-size-fits-all” migration, recognizing that not all workloads are suitable for the cloud. The company’s methodology begins with hands-on problem-solving to stabilize existing environments, giving clients the operational space to focus on broader strategic priorities. The next step involves creating a sustainable plan for modernization that decouples dependencies on older infrastructure, a crucial move for unlocking future innovation. This process is not merely about technological transition but about aligning IT goals with tangible business outcomes, ensuring that modernization efforts directly contribute to growth and organizational agility.
Addressing the Talent Gap
The modernization of IT infrastructure is intrinsically linked to the availability of a skilled workforce capable of managing both legacy and contemporary systems. A major challenge for many organizations is the growing talent gap, particularly in mainframe management, where the average age of professionals is 55. This demographic shift poses a risk to the stability of critical systems. To combat this, Ensono has implemented strategic workforce development programs, such as its Mainframe Academy. This initiative is designed to cultivate a new generation of engineers, equipping them with the specialized skills needed to support and manage mainframe environments. By investing in talent, the company helps clients ensure operational continuity and bridge the expertise gap as they transition toward more modern architectures.
Achieving Data Fluidity for AI
For artificial intelligence to deliver on its promise, data readiness is a non-negotiable prerequisite. Ensono emphasizes that seamless data mobility across hybrid environments is the backbone of any successful AI implementation. The company’s approach prioritizes the organization and structure of data before the selection of specific AI tools. This ensures that data is accessible, manageable, and properly governed wherever it is stored. Rather than constructing massive, centralized data warehouses, Ensono focuses on building secure data pipelines and intelligent orchestration that allow information to flow securely between mainframes, private clouds, and public clouds. This “data fluidity” is essential for real-time analytics and enables innovation by allowing data to be extracted, processed, and fed back into systems to address specific use cases.
Orchestration Over Warehousing
Instead of locking data into a single repository, the focus is on creating dynamic connectivity. This involves establishing secure and efficient data flows that allow for cross-platform integration. According to Vineet Kapoor, SVP of Infrastructure at Ensono, this orchestration makes it easier to unlock both innovation and operational efficiencies. The company has developed AI-enabled tools to facilitate this process, ensuring that data can move intelligently and securely throughout the hybrid IT landscape.
Strategic Partner Ecosystem
Delivering comprehensive transformation requires collaboration. Ensono leverages a robust partner ecosystem, including technology leaders like Dell Technologies, IBM, AWS, Azure, Google, and Broadcom. This collaborative approach allows Ensono to focus on its core value proposition while integrating best-in-class technologies from its partners. The relationship with Dell Technologies, for instance, provides the high-performance server and storage capabilities that form the foundation for many of Ensono’s private cloud and infrastructure products. According to the company, these partnerships are built on trust, transparency, and a shared commitment to co-creating solutions that deliver measurable impact for clients.
Future of Enterprise AI
The pace of technological change shows no signs of slowing, with AI adoption accelerating from a boardroom topic to a foundational element of business strategy. This shift is driving a greater emphasis on multi-cloud integration, cyber resilience, and data agility. For business leaders, the conversation is evolving from whether to adopt AI to how it can be used to experiment and innovate. In this landscape, Ensono anticipates a heightened focus on unlocking the vast potential of data held within legacy systems. Making this data more mobile and integrating it into modern, AI-enabled workflows will be critical for enterprises seeking to drive growth and maintain a competitive edge in an increasingly complex digital world.
