Blind spots in data management can hinder AI deployment

“While it is important to build a robust data framework with enterprise-wide data utilization, change management is equally essential for transformation readiness,” says Wells Vaughan, APAC Chief Technology Officer of SoftServe.

As a premier IT consulting and digital services provider, SoftServe is focused on enabling businesses to understand what’s needed to have a successful AI journey. According to SoftServe’s latest research with Wakefield on the state of data management practices in 2025, there’s a gap between what is expected of business leaders and what they are actually accomplishing when it comes to data transformation.

While this is a global problem, in the Asia Pacific region, the study revealed similar problems among businesses as well. This can not only lead to a mismatch in use cases being developed by AI but also have organizations lose out on harnessing the full potential of their data.

In an interview with CRN Asia, Wells Vaughan, APAC Chief Technology Officer of SoftServe discusses the findings of the study as well as some of the common blind spots in data management that organizations experience.

What are the common blind spots in data management that organizations experience, and are they aware of it?

For many organizations, their data blind spots come from leadership itself. Too often, business leaders prioritize rapid innovation and AI adoption without ensuring that their organization’s data foundation is trustworthy, accessible, and well-governed. Neglecting their fundamentals for trends, this “leapfrog” mindset often results in significant disconnects between strategic ambition and operational readiness, leading to poorly informed decision-making and limited ROI from technology investments.

SoftServe’s latest research shows that organizations are becoming cognizant of this issue. In our recent Wakefield report on the state of data management practices in 2025, 68% of APAC respondents said that their leadership does not know how to generate value from data. Even more concerning was that 65% saw strategic business decisions being made based on inaccurate or inconsistent data. When organizations operate without a reliable data infrastructure, they not only miss critical business opportunities but also risk making flawed strategic decisions that can lead to significant competitive disadvantages and substantial financial losses.

How can businesses implement the right data strategy to deal with challenges in data management?

Many companies still face significant roadblocks in implementing the right data management strategies for their business needs. This often stems from legacy systems, siloed processes, and organizational inertia. While it is important to build a robust data framework with enterprise-wide data utilization, change management is equally essential for transformation readiness. By integrating change management into their data strategy, leaders can foster cross-functional alignment, establish clear data ownership, and drive the cultural shift needed to embed new data practices into daily operations.

Localization is also crucial. In a diverse region like APAC, businesses operate within vastly different regulatory, cultural, and technological contexts. Whether it is data sovereignty laws in Singapore, compliance requirements in Australia, or the pace of digital transformation in markets like Indonesia and Vietnam, organizations must tailor their data approaches accordingly. Localizing a data strategy ensures better compliance, deeper insights, and greater agility in responding to customer needs.

Lastly, no strategy is complete without a focus on people. Building data literacy across the organization is essential for turning strategy into action. Change doesn’t happen overnight; it requires consistent leadership, continuous reinforcement, and a clear vision of how data drives growth. When organizations combine robust data strategies with deliberate change management, they unlock their data’s full potential while future-proofing their digital transformation efforts.

Strong data foundations optimize AI adoption immensely, but organizations are still inhibited by a lack of knowledge/skills, and their inability to capture/access the right data. How is SoftServe helping with this?

As AI continues to advance, leaders are eager to adopt the technology but tend to forget that the foundation of good AI is good data. 78% of APAC leaders agree that their existing data strategies require major updates before they are AI-ready, yet 80% of those same leaders report seeing their organization prioritizing GenAI investment at the expense of more valuable data and analytics initiatives. This underscores a need for organizations to prioritize data management and governance first, before they can fully leverage the potential of AI and other advanced technologies.

SoftServe addresses these challenges by providing end-to-end solutions that help organizations unlock measurable business value, step by step, through practical prioritization and execution. Starting with business priorities, we help companies identify where better data can make a difference. Thereafter, we are then able to align potential data projects with real use cases that bring material benefits to their organization. Our AI Launchpad program acts as a sandbox for rapid experimentation of new use cases to explore deployment feasibility, and AI Adoption to help clients rapidly scale their Generative AI solutions across the whole enterprise. This comprehensive support ensures that organizations have the necessary infrastructure, governance, and expertise to deploy AI effectively.

How can partners in the tech ecosystem help businesses in their data strategy, and how is SoftServe enabling them as well?

Partners in the tech ecosystem can play a pivotal role in enhancing an organization’s data strategy by providing specialized expertise and advanced technologies. As a global IT consulting and digital services provider, SoftServe acts as the agile tech partner businesses need for successful digital transformation, solving complex challenges and achieving meaningful outcomes based on business priorities. Our expertise stems from successful tech partnerships with industry leaders such as AWS, Google Cloud, Microsoft, NVIDIA, and SAS, empowering businesses to leverage cutting-edge technologies and best practices. These partnerships are particularly valuable in APAC’s diverse markets and regulatory environments, providing localized support and insights for tailored data strategies.

SoftServe also actively invests in talent development and innovation, as demonstrated by initiatives like our Quantum Bootcamp in Singapore (organized in collaboration with the National Quantum Computing Hub (NQCH) and the Infocomm Media Development Authority). Through partner collaboration and talent investment, we ensure businesses have the necessary resources and capabilities to implement effective data strategies and drive sustainable growth.

Lastly, how can leaders spearhead the need for modern data management in the boardroom, especially with business leaders remaining focused on ROI when making business decisions?

First and foremost, leaders need to recognize that fully realized data maturity is a business imperative. Leaders must take ownership of their organization’s data strategy, fostering an environment where data is recognized as a core business tenet — central to decision-making, innovation, and long-term growth. In APAC, over half of organizations that have invested in strong data management report improved customer service (52%) and enhanced operational efficiency and productivity (55%). This proves that treating data as a strategic asset can drive positive business performance.

Leaders thus should frame data investments through business outcomes: reduced costs, increased customer retention, or faster go-to-market. SoftServe’s APAC research also showed that 85% of companies with mature data strategies were able to monetize their data, enhance services, or add new revenue streams. These are the results that boardrooms value. By demonstrating how data quality directly impacts enterprise KPIs, they build compelling investment cases.

This demands a cultural mindset shift where leaders must model data-driven thinking themselves—requesting insights, questioning assumptions, and ensuring data transparency. They need to empower their teams with not just the tools, but the training and clarity of purpose to manage and act on data effectively. At SoftServe, we equip our clients in APAC to help bridge this gap with the frameworks, business cases, and strategies to transform data into a strategic lever. These roadmaps help improve service delivery, enable AI adoption, and unlock new commercial models.