It starts in a boardroom. A strategy off-site. A digital reinvention mandate. Someone says, “We need to reimagine our business with AI.” Heads nod. Decks are built. A task force is formed. Then what? Everyone agrees it’s time to act. Yet, the leap from intent to implementation is where momentum often stalls. The ambition is clear; the path is not.

According to the 2025 Gartner CEO and Senior Business Executive Survey, 77% of CEOs believe AI is ushering in a new business era, yet only 44% consider their CIOs “AI-savvy.” This gap isn’t about skills but the ability to translate strategic intent into operational reality. AI-native transformation demands more than enthusiasm. It requires a shared understanding of where to begin, how to align business and technology, and what “AI-native” truly means for operations. That’s where Virtusa’s approach begins—with a model that connects ambition to execution.

One of the hardest truths leaders confront is that AI transformation isn’t just a tooling exercise or a cloud upgrade. It demands a ground-up rethinking of how value is created, delivered, and measured at the process level. It calls for what we define as AI-native process reimagination. But here’s the catch: while business stakeholders know their domains deeply, they often lack the language, frameworks, or confidence to define what AI-native looks like in their world. That’s why we believe successful transformation must start with a model that creates shared alignment—anchored in business goals, not just technical potential.

The desirability, viability, and feasibility (DVF) prism

We assess transformation opportunities through three dimensions:

Desirability – Is the change valuable for users?
Viability – Will it deliver meaningful business outcomes?
Feasibility – Can it be executed with available data, systems, and talent?

Each dimension is a checkpoint: Desirability tests user relevance, Viability measures business alignment, and Feasibility confirms operational readiness. This approach keeps initiatives practical and executable.

DVF creates a common framework for business and technology teams to evaluate opportunities. It shifts the conversation from tool adoption to outcome definition. For example, replacing “How do we use AI in HR?” with “Can we reduce onboarding time by 40% by removing paperwork and manual routing?”

The model supports priorities such as improving user experience, reducing time-to-value, and ensuring scalable architecture. Early involvement of BDAT (Business, Data, Application, Technology) teams avoids delays from sequential handoffs.

Within Virtusa Helio—our enterprise AI framework—DVF guides opportunity selection and execution, ensuring each initiative has a clear path, governance alignment, and scalable design.

For example, in modernizing benefit inquiry workflows for a global healthcare enterprise, DVF ensured call center representatives could respond to complex medical benefit queries while meeting compliance and financial accuracy requirements. Working with the company’s AI Review Board, we built safeguards against bias and operational risk. Where no governance structures exist, our process helps set them up.

The result: a governed, scalable model with over 96% accuracy, ready for deployment in high-stakes environments.

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