As AI agents tackle more critical tasks, ensuring their reliability, safety, and alignment with human values will become crucial: Sreekanth Menon, Global Head of AI/ML, Genpact

Genpact is pushing the boundaries of what’s possible by integrating GenAI into key business processes, enhancing efficiencies, and delivering high-impact solutions for clients. From streamlining customer service for Amazon in Europe to optimizing procurement cycles at Dropbox and improving employee onboarding for Mondelēz, Genpact is using its deep-domain expertise and strong partnerships with tech giants like AWS, Google Cloud, and Microsoft to co-innovate AI-driven solutions.

In this conversation, Sreekanth Menon, Genpact’s global head of AI/ML, shares key insights into these transformative efforts and highlights how it is impacting Genpact

Some edited excerpts:

Which are some of the high impact areas where Genpact is leveraging GenAI extensively? Please give us some examples
Using our new 3+1 execution framework, we are leveraging GenAI to drive impact across stakeholders – employees, clients, shareholders and communities. For clients, we are playing a critical role in driving business transformation with our deep-domain expertise. For example, we are working with Amazon for their Out-of-Warranty device customer service in Europe where we have leveraged AI and Amazon Connect to create an end-to-end solution that integrates AI powered chatbots and enables logistics management, our repair partner network, end-to-end tracking and proactive customer notifications, all with minimal human interactions.

We’re helping leading organizations like Dropbox streamline their procurement operations, cutting the procurement cycle by 50%. Our expertise in F&A space, combined with AI-fuelled automation power of ServiceNow Platform is driving better results, faster time to value, and increased productivity for Dropbox’s procurement and finance operations. Another example is the work we are doing with Mondelēz to address the need for upskilling and shorter ramp times for new employees, leveraging Genpact’s Cora Knowledge Assist platform to enable faster access to knowledge, insights and standardized operating procedures.

We are also collaborating with top-tier partners such as AWS, ServiceNow, Google Cloud, and Microsoft. This collaboration allows us to experiment and co-innovate, thereby building comprehensive, growth-oriented, AI-infused solutions for our clients. Our strategic investments in AI have been consistent. This includes launching AI Innovation Centers in key markets such as London, India, and Bucharest. Lastly, our Generative AI Playground has attracted over 60,000 users. This platform allows users to test and learn how generative AI can solve client problems and unlock value.

What has been the impact of using GenAI in some of the processes, services or solutions? Can you cite some measurable numbers?
GenAI has one of the fastest adoption curves for a new technology in our industry production. Many companies are transitioning from experimentation to scaling GenAI into production, a process we believe we are optimally positioned to facilitate. Our clients have observed a more proactive and strategic approach from Genpact, as we bring transformative ideas to the table. Though it’s still early days, we’re measuring success through inflows, bookings, and revenue, and we’re witnessing increased momentum in GenAI-related revenue and bookings.

Our pipeline is at record levels, indicating a strong position for us moving forward. At the end of the day, clients choose us for five key reasons. Our deep-domain data and AI expertise; comprehensive solutions; accelerating partner ecosystem; client-centric approach, and innovative technology, including our pre-built AI accelerators.

Our GenAI solutions have delivered impact across different verticals ranging from banking to healthcare. For instance, Genpact helped one of the largest investment banks in the Europe with automated infrastructure orchestration, enabled dynamic scaling, and facilitated continuous integration and deployment using GenAI. This helped enhance efficiency and time management by reducing operations time by 42% (from 420 minutes to 180 minutes) and improved productivity by 45% in the development effort. Over the entire year this initial venture saved the client over $30,000.

We have also partnered with a global medical technology company to develop a gen AI application designed to accelerate technical support issue identification and resolution, improving every support interaction with customers. Gen AI powered application can deliver productivity gains of 20-25%, improve dispatch avoidance by 15-20%, and increase instrument up-time by up to 10%. Speeds up onboarding and ramp-up time for new agents to provide effective customer technical support faster. Most importantly, it delivers a logical, repeatable, and consistent customer experience.

How has skilling for employees changed due to GenAI? What are some of the learnings or best practices that you would like to share
The implementation of GenAI has significantly altered employee skilling, shifting the focus towards an AI-first future. Our +1 internal initiative, “Client Zero,” is a testament to this, where we are using GenAI to transform our own operations, thereby establishing Genpact as a model for AI-led transformation. We have introduced an AI assistant for our global IT help desk, which has resulted in a 2x increase in user satisfaction and a 30% decrease in service desk staff. Our future plans include the introduction of Cora AI assistants across various departments.

We have also launched an AI Guru, a GenAI-powered learning coach that provides personalized learning recommendations to our 60,000 global employees. This initiative has boosted productivity and amplified the collective knowledge of our internal experts.

In collaboration with Microsoft, we have modernized our finance function by leveraging Microsoft’s AI tools. This has resulted in improved vendor management automation, with an 85% accuracy rate in response, and doubled supplier satisfaction. The transformation of our customer collections process through AI-powered analytics and automation has streamlined invoice and payment tracking.

We have also implemented a large language model-based digital assistant, which has led to a 53% reduction in support tickets and improved employee experience. Furthermore, our “GenAI Playground,” created using Microsoft’s Azure OpenAI suite, has facilitated over 2 million interactions, enabling employees to innovate and improve 120 unique use cases. This platform has led to significant productivity improvements across our research and training teams, and in software development.

What are some of the key trends for IT services firms in the GenAI space? How do you see it evolving in the future?
We are entering a future where programmers are empowered by tireless assistants, capable of both suggesting code completions and automating entire tasks.  As AI agents tackle more critical tasks, ensuring their reliability, safety, and alignment with human values becomes crucial. We can expect significant efforts to focus on making agents more transparent, and controllable, building trust and enabling responsible deployment. Personalization will drive AI agents to develop customized knowledge bases and interaction styles, becoming more effective personal assistants over time.

The widespread adoption of AI agents will demand new robust Responsible AI practices.  Going forward, the landscape of GenAI will see more enterprise use cases performing crawling & indexing workspaces and creating hyper-personalized digital companions in a human-centric way. There will be a surge in developer tools and application frameworks, such as LLMOps, serving the ecosystem with reusable components to build more advanced AI applications. We will also see AI-first infrastructure companies offering compute at reasonable costs along with on-demand availability and scalability. I believe, GenAI will continue to nudge the business processes to a transformative zenith, catalyzing unprecedented efficiency in both back-end and front-end operations.