I recently attended the Genpact AI conference, where the Genpact employees I spoke to were energized by the changes AI is bringing and are focused on helping clients operationalize emerging technologies at scale. The company is investing in tools to provide greater ongoing feedback from employees: an HR executive described how they use an employee feedback system combined with a benefit awards system (like an airline's rewards program) to monitor employee satisfaction and identify ways to remedy shortcomings.      

In this blog, I look at Genpact’s approach to scaling AI across the enterprise.

Scaling AI across the enterprise

Genpact’s AI focus is on the “AI of Now”. It believes that for AI to have an impact, it needs to be scaled operationally across the enterprise. Unlike many competitors, Genpact did not demonstrate futuristic AI functionality but instead focused on how it helps drive adoption across enterprises, presenting examples of operational deployment of AI to six clients. To grow its client base, Genpact wants to do more work with Tier Two enterprises, which typically have a more significant portion of their operations delivered with legacy platforms and manual processes.

To drive operational adoption of AI across an enterprise, Genpact believes there are three things required:

• Domain expertise: understanding industry-specific processes and data from working with those processes. Genpact has identified which processes and data it will work with for AI projects   
• Technology ecosystem and expertise: building an ecosystem of product vendors is necessary to access emerging AI functionality. Executing successful implementations requires the tools, integrators, and technology knowledge that most clients do not have    
• Dynamic talent: building an effective workforce to deliver these services requires training and creating cross-functional data, AI, and domain experts’ teams.

Practical AI applications

To build its AI services, Genpact surveyed what CFOs want from their technology investments, and found their top requirements to be:

• Actionable insights
• Reliable forecasts
• Talent that can implement and run AI effectively.

Based on this research, Genpact has embedded AI into its F&A offerings to enable CFOs to improve capital allocation and produce more reliable sales and profit forecasts with on-demand revenue and cost forecasts, fast decision-making with what-if analyses, and the ability to drive change in the trajectory of their business. Using these tools, enterprise clients can:

• Drive growth through AI-driven insights and data-backed decision-making
• Improve revenue forecasting, working capital optimization and planning
• Improve operational efficiency with AI-driven automation. 

Genpact can develop better AI-based insights than any single client because it draws on a large pool of data from clients across multiple industries. Genpact’s business supporting F&A draws on its experience doing 500 quarterly book closes for 35k legal entities annually. The data and domain experience from this sizeable annual transaction pool enable robust predictive analysis and the ability to apply AI using keystroke-level process knowledge, thus enabling it to deliver outcomes to its clients. Similarly, Genpact has applied its considerable operational transaction experience to address supply chain and bank fraud challenges for clients.  

New AI tools

At the conference, Genpact announced three proprietary tools for its AI ecosystem:

• Genpact CFO Actions Hub: the four key themes the hub will address are responsible AI, fine-tuning LLMs, the agent-computer interface, and how to retrieve & generate data that enables CFOs to transform data into cohesive narratives and enable forward-looking actions like scenario planning and forecasting. It uses LLMs and Genpact’s domain knowledge on a foundation of responsible AI to drive relevance with CFOs
• Genpact Agentic AP Solutions:  the launch of four AI-based AP solutions, already live, with four AI-based AR and four AI-based accounts solutions coming soon  
• Genpact Finance AI Academy: a set of training courses for employees and clients to improve their domain/technology expertise for the use of AI in finance.

In addition, Genpact’s GenAI solution, Scout, was on the conference app. It summarized each presentation soon after it had been delivered. This was a significant aid to this conference attendee because of the speed at which the summaries were sent out after each session. Presentation slides were also available on the app soon after each session.

Conclusions

Genpact’s AI strategy is to drive operational adoption of AI within enterprises to deliver business value. Operational adoption requires both client and Genpact employees to become familiar with AI technology and how it works in practice. Success in AI deployment means work practices will change, eventually making historical operations architectures irrelevant. Successful change management will need employee buy-in, and Genpact is building continuous feedback mechanisms to keep employees on board.