“Quality assurance is not about perfection; it’s about dealing with uncertainty with intelligence, agility and empathy,says Senior Software Quality Supervisor, Sindhuri Korrapati. The comment, made during a recent leadership panel on digital risk management, reflects the subtle shift in the software industry: a transition from risk-agnostic testing to risk-based assurance.
In an industry where software bugs can shut down markets, compromise patient data or disrupt product quality, innovative leaders like Korrapati stand out not only for their technical mastery, but also for their cutting-edge thinking. Her vision is emblematic of a new class of leaders who are moving software quality beyond scripts and scorecards and toward strategic foresight. “The speed of digital transformation leaves no room for reactive quality,she continues,Risk information must be at the core of assurance.”
The New Economy of Software Assurance
The software assurance market – the broad umbrella of practices that ensure the reliability, security and compliance of software – is expected to jump from approximately $10 billion in 2023 to $25 billion in 2032, growing at an annual rate of approximately 11%. North America still has the largest share, but Asia Pacific is now leading the way in terms of growth, growing at nearly 13% annually as companies in India, China and Southeast Asia automate core industries and grapple with escalating cyber threats.
The urgency is undeniable. In the first half of 2025 alone, regulators around the world imposed fines totaling more than $2 billion for software-related compliance failures. These can be boiled down to three things: incomplete testing, blind spots in AI-driven systems, and the pressure to release faster than teams can safely validate.
For Korrapati, this landscape should be seen as an opportunity – a chance to apply modern, risk-based thinking that balances pace and confidence. “The traditional QA function was obsessed with rigorously testing every requirement,she discusses.But in complex systems powered by AI and microservices, predictive prevention (anticipating where risks will occur) is the new frontier of quality.”
From testing to certainty: a strategic turn
Over the past decade, quality engineering has evolved from manual verification to holistic assurance. The rise of DevSecOps, embedding security at every stage of the pipeline, was just the beginning; Consultants say RiskOps could be the next step, seamlessly integrating software assurance with enterprise risk functions.
“Testing is a verb. Security is a philosophy,Korrapati often told her peers. ‘When a release decision becomes a boardroom conversation, you know you’ve raised code quality to its conclusion.”
Consulting giants from IBM to Accenture have reshaped their offerings accordingly. IBM’s recent AI-driven assurance suite can identify vulnerability clusters before code reaches production servers, reducing incident-related costs by as much as 45% in pilot studies.
However, smaller companies, especially those in healthcare and fintech, struggle to apply these frameworks consistently. Critics, such as London-based analyst Ravi Naidu, warn that ‘risk-based assurance’ can too easily degenerate into mere jargon. “You can quantify probabilities all you want,he says,but culture, not tools, remains the weakest link.”
The double-edged role of AI
AI is both the cause and the cure in this unfolding drama. As machine learning models push automation deeper into test suites, the software development market – expected to reach $1 trillion by 2030 – is facing a paradox. Tools like autonomous code analyzers accelerate delivery and introduce opaque risks when systems learn imperfectly
Korrapati is cautious yet optimistic. “AI doesn’t eliminate QA tasks,she emphasizes.It reshapes them into roles that require critical judgment, ethical reasoning, and systems thinking.” She points to her teams, where generative AI helps simulate thousands of user scenarios, but human oversight decides which deviations matter.
When risk becomes design
The current wave of risk-based assurance methodologies comes intellectually from the manufacturing and financial sectors, industries that have long used Monte Carlo simulations and Value at Risk matrices. In software, this translates into mapping potential failure modes against business-critical outcomes rather than counting raw defects.
“Every part must earn its contribution,says Korrapati. Her teams perform ‘assurance sampling’, similar to financial stress tests, before going live. This strategy, she argues, scales quality much more sustainably than exhaustive regression runs.
Market data supports her claim. By 2024, enterprises that adopted risk-priority testing reported an average of 20% faster release cycles and 15% fewer post-release incidents. Even regulators are paying attention: the US National Institute of Standards and Technology (NIST) now recommends risk-weighted validation for critical AI software certifications.
Still, critics urge caution. “Risk-based does not mean risk-free,says Naidu.Without continuous validation loops, teams could normalize higher failure thresholds.”
Korrapati recognizes this. “It’s about knowing which risks to limit, which to monitor and which to accept.she says.Software today is a living system. If you strive for absolute safety, you paralyze innovation.”
Contributions by Sindhuri Korrapati
Sindhuri Korrapati has worked with some of the most influential organizations in the life sciences sector, including Medtronic, Zimmer Biomet and Gilead Sciences. Her extensive experience with these global leaders has given her a deep understanding of the challenges and opportunities surrounding software testing and validation in the regulated life sciences environment.
Korrapati is currently working with a pioneer in surgical robotics and is at the forefront of validating next-generation GxP software systems that ensure patient safety and maintain the highest product quality standards. Her work plays a critical role in maintaining the reliability and compliance of advanced medical technologies that have a direct impact on patient outcomes.
In addition to her professional contributions, Korrapati is also an active thought leader in the life sciences community. Her widely recognized article, “Trust but Verify: Validating AI in the GxP World of the Pharmaceutical Industry,” published in Pharmaceutical onlinehas attracted significant attention from industry experts. The piece highlights her leadership in shaping the conversation around responsible AI validation and compliance within the pharmaceutical and biotechnology sectors.
Regulation, reputation and the way forward
Experts predict that by 2030, more than 70% of enterprise software will be subject to stricter warranty obligations, driven by privacy laws and critical system regulations. Financial institutions are already faced with quarterly resilience statements; medical software will likely follow
As regulations evolve, software assurance remains a specialized field, valued for its niche expertise in ensuring compliance and security.
Yet she warns against overregulation. “Compliance should guide, not restrictshe says.When teams treat regulations as a checklist, they comply with the letter but miss the spirit of certainty.”
Korrapati envisions a future of co-evolution: humans and algorithms checking each other’s blind spots, business ecosystems behaving more like adaptive organisms than static hierarchies. “Resistance,she emphasizes,is not a characteristic, it is a result.”
Lessons from the risk limit
What ultimately sets leaders like Sindhuri Korrapati apart is technical mastery and the ability to translate complexity into clarity. Her approach collapses the divide: between developer and auditor, between short-term delivery and long-term reputation.
When asked what motivates her, she pauses. “Software runs the world, but people do run software,‘ she says softly. The better we understand risks, our own limits, our systems and those of our world, the more human our technology becomes.”
It’s a fitting coda for an industry that is learning to see quality not as flawlessness, but as foresight, a shift in perspective with consequences that go far beyond code.
