AI enables engineering teams to develop new products, automate processes, and mitigate risks. A recent conversation with Wipro Engineering Edge, Rupesh Kumbhare, General Manager of Wipro Engineering Edge, reveals how AI will impact engineering teams today and in the future.

Q: Over the past 12 months, AI and GenAI have been discussed in all industries, and their use is accelerating quickly. What are you witnessing in the Engineering space?         

Rupesh: From our client interactions, we have witnessed that product development, operations, business, and technology teams are under intense pressure not only to understand AI but also to build business cases and start to use it in their everyday processes, concept developments, and product design stages. Many of our clients already have impressive plans to overhaul their engineering and R&D processes through the power of AI. Others have just begun.

Across all enterprises and industries, disruptive change is coming. AI is unavoidable. If integrated strategically, it will be an impressive force for good, enabling unprecedented efficiencies, driving enhanced engineering capabilities, and ushering in new innovative ways of doing business. From AI co-pilots to AI agents, intelligent automation can work alongside humans to unlock new levels of productivity and innovation.

Rupesh W. Kumbhare

 General Manager, Wipro Engineering Edge

Like Cloud before it, AI and GenAI present a new paradigm for product engineering teams to redefine what to do and how to do it.

The trend of software (re)defining everything continues and is now accelerated by incorporating AI and Generative AI technologies. Like Cloud before it, AI and GenAI present a new paradigm for product engineering teams to redefine what to do and how to do it — one that requires a transformation of the approach toward the process and the outcome orientation of product development. 

The opportunity is immense if managed well. McKinsey estimates place the global value creation potential of Cloud technologies at $3Tn by 2030. Generative AI, on the other hand, has the potential to generate roughly the same magnitude annually!

So, how do businesses capture this opportunity?

Successful product development will increasingly be a function of processes bringing together people, partners, and platforms to build defined, differentiated, and disruptive products and services. Engineering Service Providers (ESPs) like Wipro have a unique role in helping businesses navigate this journey.

Q: Based on what you have seen in the market so far and the current forecasts around AI technologies, where do you see Engineering organizations using AI to unlock the most business value?

Rupesh: AI in Engineering is already prevalent across many industries. AI and deep learning have the potential to revolutionize engineering processes, enabling enhanced ideation, product drafting, virtual design, and simulations. By optimizing test cases, engineers can reduce physical build and testing time. In product development R&D, AI can improve productivity by an estimated 10 to 15 percent. 

For example, industries like life sciences and chemicals are leveraging AI for faster development of drugs and materials. Healthcare providers use AI and Engineering skills to automate processes that enhance patient outcomesManufacturers are re-evaluating their supply chains, conducting predictive data analysis, and utilizing engineers to improve maintenance, health & safety, and resilience, resulting in products made safely, efficiently, and cost-effectively. Customer service businesses are utilizing AI to assist Engineers in uncovering insights about customer behavior and buying patterns to help improve the products they bring to market.

More and more examples are starting to come to market in terms of AI usage in Engineering. However, at Wipro, we advise clients to take a cautious evolution toward extracting/evaluating business value from AI. Organizations should not dive into using AI tools without a strategic evaluation of those tools. 

They should first examine their value chain and ask: “Where can the use of AI make the most significant impact?” It may be in the concept design stage, the R&D process transformation, or the product launch phase.

Where Engineering teams can see the potential for AI, they should be looking at more than just the tooling deployment costs and business benefits. They also need to make sure operating costs such as cloud usage, additional technology infrastructure, and the up/cross-skilling of people are included in the business case to identify if AI will have the impact they desire.

But let’s be clear: The impact of AI solutions combined with engineering skills will be felt everywhere — not just in Silicon Valley or technology companies, but in every kind of organization you can imagine. This innovation potential will span sectors and combine with other technologies — including 5G, IoT (Internet of Things), and digital twins — to usher in new ways of doing business.

Q: Do you have any recent examples or case studies from Wipro where you have successfully deployed and used AI technologies to help with projects in the Engineering space?    

Rupesh: AI has been prevalent in Engineering for some time now.  For example, we have Pipe Sleuth, an AI-powered pipe condition assessment solution for metropolitan wastewater networks. It uses advanced image processing and deep neural network algorithms (AI) to identify, grade, and score pipe anomalies.

 Rupesh W. Kumbhare

General Manager, Wipro Engineering Edge

AI has been prevalent in Engineering for some time now.

Of course, I’d like to discuss our collaboration with automotive giant Marelli. Marelli leveraged Wipro's expertise to develop a cabin digital twin, a significant milestone in the transition to software-defined vehicles (SDVs). Wipro partnered with Marelli to realize the possibilities of a digital twin, connecting with AI and ML technologies to help Marelli create an intelligent, automated solution on the cloud to test, validate, and update SDV features. Now, they can work with OEMs to transform and deploy conventional automotive apps leveraging cloud-native technologies (apps-on-automotive as containerized microservices) deployed and controlled from the cloud.

This technology enables OEMs to introduce connected vehicle services quickly, simplify simulations, and reduce prototyping costs. In addition, Marelli's solution facilitates over-the-air software updates for faster response to customer demands.

Q: Innovation is a broadly used term. How do you see AI enabling innovation in Engineering today and in the future?

Rupesh: AI can deliver new capabilities and efficiencies across nearly every engineering stage, from original concept to operations. At Wipro we are taking an ‘AI-first’ approach’ and embedding AI in all our offerings. We are upskilling our talent pool to apply AI in their work, projects, accounts, and solutions. Companies embracing AI tools and engineering skills have a unique opportunity to accelerate innovation. Contrary to popular belief, AI will not eliminate jobs but redefine them, allowing for more human creativity. By leveraging AI, organizations can optimize their engineering talent, shifting focus from mundane tasks to critical challenges requiring human ingenuity. For example, In Manufacturing, we are witnessing companies using ‘cobots’ (collaboration robots) to undertake specific repetitive tasks enabling skilled engineering staff to free up their time to concentrate on more complex functions which can provide an innovative edge to an organization. Wipro engineering teams, too, are actively exploring new possibilities through proof of concepts, leading to ground-breaking platforms like Wipro Cloud Car, Wipro 5G Def-i, and Wipro Industry DOT, catering to multiple industries.

Q: Amongst all the hype and potential of AI we should remember that there are risks associated with AI. How can Engineering teams understand the key risks associated with AI and how can they plan to mitigate the risks?

Rupesh: Like any technology, AI tools need to be tried and tested so risks can be identified, managed, and mitigated. Before deploying AI tools, Engineering teams need to ask themselves: If I use this AI tool, could it damage the company’s reputation in any way? Will it affect an organization's market position? Could it result in prosecution if the technology is not used correctly?

In summary, it’s not as simple as analyzing an AI tool and seeing if it is an organizational fit. Data, security, diversity, governance, ethics, and compliance questions and assessments concerning using AI tools in engineering must be undertaken.

If a risk exists, then Engineering teams need to ensure they take responsibility. They need to establish safeguards and controls to mitigate the risk, have the right management and culture for managing the potential risk, and ensure they have the right contingency plans in place for decision-making processes, aligning motives, bias, inefficiency of training data, transparency in funding, explainability, safeguards, ethics, and regulation. Despite the challenges, enterprises can use the correct training data, keep humans in the loop, and implement thorough change management processes to extract the benefits of AI.

Q: Finally, we need to discuss the impact on people. What do you think are the work and productivity implications for Engineering teams?

Rupesh: AI and technological changes are coming, whether organizations are ready or not. It challenges all enterprises to re-examine what is possible and embrace new working methods that make the most of the new capabilities. That’s why Wipro Engineering Edge integrates AI with the Cloud and infuses it into every aspect of our business.

 Rupesh W. Kumbhare

General Manager, Wipro Engineering Edge

AI and technological changes are coming, whether organizations are ready or not.

Across the technology ecosystem, as AI becomes more adept at capabilities like code generation, engineers must shift their focus (reskilling) and upgrade their skills (upskilling) to use AI to improve their roles. Fortunately, the creativity and expertise of engineers will continue to be essential in allowing enterprises to leverage the power of their technology stacks more effectively. At Wipro, our $1bn+ investments and company initiatives such as ai360, internal hackathons with Intel, and hyperscalers are already providing our engineering talent with opportunities to explore how engineers and AI will collaborate to drive value in this new opportunity-rich era.

To learn more about Wipro Engineering services and how we use AI to enable our clients to realize their technology and business ambitions, please visit our engineering page and email us at