Insight: Tech Mahindra's Narasimham RV On Harnessing AI To Transform Product Engineering

Under the leadership of Narasimham RV, president – engineering services at Tech Mahindra, the company is driving a global engineering transformation agenda. With over three decades of engineering excellence, Tech Mahindra is uniquely positioned to enable end-to-end transformation — from chip design to enterprise solutions — spanning mechanical design, silicon engineering, embedded systems, electronics, connectivity, applications, and cloud-based back-end solutions across ten industries.

In an exclusive interview with OneArabia, Narasimham RV sheds light on how Tech Mahindra leverages artificial intelligence (AI) to revolutionise product engineering, addressing key advancements, challenges, and future trends.

How is Tech Mahindra utilising agentic AI and the power of autonomous decision-making in product engineering?

Agentic AI is transforming workflows by serving as an industrial workforce that augments human capabilities. In digital product engineering, Tech Mahindra employs AI agents across the software development lifecycle (SDLC), from requirements gathering to code generation, testing, and deployment, enhancing DevSecOps pipelines.

The AI-driven SDLC, powered by the Agentic AI application platform Swifter.io (a Tech Mahindra co-investment), accelerates application development cycles and improves developer experience by combining automation with human oversight.

In industrial and physical setups, AI agents streamline knowledge-intensive tasks, such as generating technical publications in aerospace, retrieving design specifications from historical records, and facilitating workforce training for operational procedures, all while adhering to engineering and regulatory constraints.

Tech Mahindra's Agentic RAG platform further enables powerful use cases in plants and warehouses, including visual inspection of manufactured goods and inventory management. The potential of AI agents, especially when orchestrated using AI, is immense.

What advancements in generative AI is Tech Mahindra exploring to accelerate product development cycles?

GenAI drives hyper-automation in knowledge-intensive use cases, transforming how products are designed, tested, and launched. It enables rapid design and simulation of concepts while balancing constraints such as performance, sustainability, and cost, alongside opportunities like design efficiency, material impact, usability, and aesthetics.

During prototyping, GenAI absorbs contextual insights and research feedback to evaluate user behavior and predict acceptance, significantly accelerating product improvement. When launching new product variants or customising for new markets, where many features remain consistent, GenAI streamlines processes by automatically generating regression test cases, reducing time and effort.

Beyond development and testing, GenAI simplifies downstream processes by auto-generating product datasheets and manuals, embedding intelligence into documentation and ensuring consistency.

Which industries are experiencing the most transformative impact from Tech Mahindra's AI-driven product design solutions?

AI adoption is notably high in automotive, aerospace, industrial, and consumer appliance sectors, followed by process industries such as oil and gas and chemicals. This impact stems from collaborative, consultative approaches with customers to identify optimal interventions and develop practical roadmaps for strong returns on investment (ROI).

Additionally, AI-powered digital platforms are delivering tangible benefits in service sectors like banking, financial services, and insurance (BFSI), communications, energy, and utilities, enabling rapid service rollouts and highly intuitive customer experiences at scale.

What role do digital twins and digital threads play in Tech Mahindra's AI-driven product design strategy?

Model-Based Engineering enhances interactions between physical and digital domains. By centering Product and Manufacturing Information (PMI) in product engineering, Tech Mahindra creates near real-time connections supported by digital twins and digital threads.

The company's AI-driven approach leverages this backbone to infuse AI across the product lifecycle—from reimagining designs based on real-world feedback to zero-physical prototyping, simulation, and validation, and even improving performance through AI-agent-enabled monitoring and prediction. This accelerates responses to market changes, enabling rapid development of innovative product variants.

How is Tech Mahindra using AI to embed sustainability in new product development?

A significant portion of a product's ecological footprint and emissions is determined during its design phase, making sustainability a critical focus. Tech Mahindra's whitepaper with MIT Technology Review Insights, titled Designing Better Products with AI and Sustainability, highlights how AI accelerates time-to-market while reducing waste across the product lifecycle. AI-driven lifecycle assessments during design enable engineers to select optimal materials and designs that uphold performance while minimizing carbon footprints.

How is Tech Mahindra leveraging its investments to advance AI applications in engineering design?

Tech Mahindra's investments focus on embedding AI at both the core and edge to drive enterprise transformation with speed and precision. Through its portfolio company, CTCO, Tech Mahindra delivers robust software product and platform engineering expertise with a nearshore advantage. The co-invested Swifter.io platform, an enterprise-grade Agentic AI application development solution, reduces design-to-deployment time by 50%, significantly accelerating digital transformation for customers.

AI at the edge is showcased across industries like software-defined vehicles (SDV), consumer appliances, warehouse management, manufacturing, and smart devices. By combining machine learning with technologies like computer vision and 5G, Tech Mahindra unlocks new levels of efficiency and intelligence. Dedicated labs and a strong ecosystem of partnerships enable collaborative innovation, allowing clients to explore, experiment, and scale AI-driven possibilities.

What are the biggest challenges in adopting AI for product design and engineering, and how is Tech Mahindra addressing them?

AI adoption in product design and engineering faces challenges related to data, security, privacy, and trust. Tech Mahindra addresses these through scalable, secure, and domain-aligned solutions.

In industrial automation, where systems like PLM, MES, SCADA, and ERP interconnect, the key lies in ensuring high-quality data flow. Tech Mahindra incorporates data readiness and governance into its consulting-led product development roadmaps, laying the foundation for scalable AI deployment.

Public AI models often lack relevance, accuracy, confidentiality, and cybersecurity. To counter this, Tech Mahindra empowers customers to build proprietary AI agents, deployed on-premises and trained on enterprise data, ensuring security and business alignment.

Recognising that AI transformation is a journey, Tech Mahindra designs phased transformations that deliver quick wins with low risk while progressively addressing long-term challenges.

Human-in-the-loop testing ensures end-to-end validation for phygital products, maintaining trust and reliability. Additionally, continuous upskilling, lab-based workbenches, and strategic partnerships ensure the right blend of technical expertise and domain knowledge.

Looking ahead, what trends in AI for product design and engineering do you foresee shaping the industry over the next 3-5 years?

The industry is moving toward autonomous, agentic AI systems capable of planning, reasoning, and acting across entire design workflows. Organizations will increasingly scale AI and GenAI features for enterprise-wide implementations.

Edge-based AI will gain prominence, enabling real-time decision-making and simulations in industries like automotive and manufacturing. Digital twins, digital threads, and generative AI will facilitate closed-loop, continuous product development.

Sustainability will drive adoption, with AI used to design energy-efficient products and reduce waste. Robust governance frameworks will also emerge, ensuring AI systems are ethical, transparent, and globally compliant, defining the next era of cognitive engineering.

What steps is Tech Mahindra taking to upskill its workforce to effectively leverage AI in engineering and design projects?

People are central to AI adoption, and Tech Mahindra's AI proficiency framework defines four expertise levels—from AI White Belt to AI Black Belt—covering foundational to advanced capabilities. The AI White Belt badge is mandatory for all associates. Customized programs address specific industries and domains, such as technical publications, AI for IoT, AI SDLC, and smart device platforms.

Partnerships with academia, hyperscalers, and industry bodies deliver structured AI learning and certifications. Beyond technical training, Tech Mahindra emphasises AI literacy, ethical awareness, and domain-specific expertise, ensuring its workforce is equipped to drive responsible AI-led product engineering at scale.