As AI reshapes how enterprises think, decide, and deliver, the conversation is shifting from automation to intelligence at scale. From GenAI-led engineering to responsible AI adoption, organizations are embedding AI deep into their decision-making core. Sanjay Jupudi, Founder and CEO of Qentelli, shares how this shift is transforming enterprises and positioning India as a global AI innovation hub, in an exclusive conversation with Elets News Network (ENN). Edited excerpts:
AI is rapidly reshaping enterprise transformation worldwide. From your vantage point, which areas of the modern enterprise are seeing the most immediate and tangible impact of AI adoption?
The most tangible impact of AI today is in decision-making at scale. Enterprises are moving beyond automating tasks to designing systems that can learn from data, predict outcomes, and offer real-time insights. This shift from rule-based execution to intelligence-driven choices is transforming industries like BFSI and healthcare through engineering and operations.
We work with many clients in these fields. For instance, in financial services, AI is now being used to dynamically assess credit risk during loan approvals by analyzing real-time financial behaviours rather than relying on static credit scores. In healthcare and pharma, AI-driven analysis of clinical data, patient demographics, and historical success rates is accelerating trial selection and improving outcomes. The real transformation happens when AI is embedded into the core of how decisions are made, not layered on as an afterthought.
Generative AI is moving from experimentation to real enterprise use cases. How do you see GenAI transforming software engineering, testing, and product delivery over the next 3–5 years?
Generative AI is set to redefine the software lifecycle from end to end. Engineering will move away from manual, code-intensive execution toward a model where teams articulate intent, business outcomes, and system design, while AI accelerates development through intelligent code generation, optimization, and validation. We are already seeing vibe coding taking shape in this ecosystem.
In quality engineering, which is my expertise, GenAI will shift testing from a reactive checkpoint to a continuous, intelligent capability automatically creating tests, adapting to change, and ensuring quality is embedded throughout the delivery pipeline. Product releases will become quicker and more adaptive, shaped by realtime usage patterns and customer feedback. As this evolution unfolds, I believe AI will no longer just support delivery but actively influence how software is designed, built, and evolved, resulting in systems that are more agile, predictive, and resilient.
As businesses scale their AI initiatives, data quality, governance, and readiness become major hurdles. What foundational steps should enterprises prioritize to ensure successful and responsible AI implementation?
Successful AI adoption starts with strong foundations. Enterprises must treat data as a strategic asset by ensuring it is clean, connected, contextual, and governed. Without this, even the most advanced AI models will fail to deliver meaningful outcomes.
Equally important is building responsible AI frameworks that prioritize transparency, security, and ethical use. With the rapid mainstream adoption of AI, the ecosystem today is shaped by numerous directives and guidelines, and a universal framework for ethical AI is fast becoming a reality. At Qentelli, we proactively align with this shift.
We have built our own AI-driven products, tools, and governance frameworks, supported by proven methodologies and process playbooks, to help enterprises accelerate and scale digital transformation across cloud adoption, DevOps, and quality engineering with responsibility at the core.
But readiness is not just technical; it needs to be built within organizational DNA. Leaders must invest in AI literacy, crossfunctional collaboration, and change management, so teams understand, trust, and act on AI-driven insights. AI should be designed as a continuous learning system, not a one-time deployment.
AI-driven automation is unlocking new levels of efficiency. How can companies balance this automation with human insight to create highperformance, AI-augmented teams?
The objective of AI-driven automation is not workforce replacement, but workforce amplification. A sense of balance and harmony between humans and machines is the need of the hour. We’re now seeing leading enterprises use AI to eliminate repetitive, low-value work, allowing teams to focus on higher-order thinking, strategic judgment, and innovation.
The most effective AI-augmented teams maintain humans in the loop. AI delivers recommendations and pattern recognition at scale, while people provide context, ethical judgment, and accountability. When designed correctly, this partnership results in faster decisions, better outcomes, and a more resilient organization without compromising trust or responsibility.
India is positioning itself as a global AI innovation hub. What unique advantages does India offer in the global AI landscape, and how can enterprises leverage this opportunity to accelerate transformation?
India’s emergence as a global AI innovation hub is driven by a rare convergence of scale, engineering depth, and real-world enterprise exposure. The country has one of the world’s largest pools of digital and AI talent, with hands-on experience building, operating, and modernizing complex enterprise systems across industries. This is further strengthened by a vibrant startup ecosystem and growing institutional support through government-led centres of excellence, national AI initiatives, and platforms such as IndiaAI that are helping build robust datasets and foster responsible AI adoption.
What is fundamentally changing is India’s role in the global value chain. The shift is from executionled services to innovation-driven solutions. India is increasingly becoming a centre for AI co-creation, where platforms, products, and industry-specific solutions are designed and scaled for global markets. Enterprises that view India as a strategic innovation partner can accelerate transformation while building future-ready capabilities.
A use case of this shift is the rise of AI-powered Global Capability Centers (GCCs). By establishing India-based hubs focused on AI architecture, data engineering, and applied intelligence, enterprises can combine deep technical expertise with cost efficiency to drive global impact in areas like personalized financial services, intelligent healthcare platforms, or next-generation enterprise software. Our country is not just supporting AI adoption but also shaping how AI is built, applied, and scaled worldwide.
Also Read: AI Impact on Governance & Economy: The iDetect Paradigm in Citizen Service Transformation
Qentelli has been at the forefront of digital and AIled transformation. What differentiates Qentelli’s approach to helping enterprises transition into AI-powered organizations?
What sets Qentelli apart is our focus on outcomes, not hype. We don’t treat AI as a plug-and-play solution or a set of isolated use cases. Instead, we help enterprises embed AI directly into their decision-making fabric.
Our approach focuses on reimagining workflows with AI as a decision partner, not a service provider. We unify data across silos, design modular and APIdriven architectures, and embed AI models that provide real-time recommendations, not just automation. Across industries like healthcare, retail, aviation and financial services, this has enabled predictive decision-making, risk observability, and faster time to market.
Most importantly, we align AI initiatives to business KPIs that matter such as growth, speed, and resilience. Our role is to help organizations move from fragmented systems to intelligent, decision-ready enterprises that can adapt and lead through change.
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