Enterprise leaders have concluded their phase of testing generative AI’s capabilities, according to Genpact’s President and CEO, Balkrishan “BK” Kalra. During Newsweek’s AI Impact Forum webinar, he explained that companies now focus on scaling use cases rather than conducting experiments. Scaling AI involves addressing unresolved issues from the proof of concept stages, making data usable, standardizing processes across business units, and ensuring employee fluency with AI tools.
Kalra stated that the success of scale use cases should be evaluated based on business performance, answering whether enterprises can grow faster, operate more efficiently, or increase cash flow. Achieving these goals becomes complex when AI expands beyond controlled tests to everyday operations.
Research by Genpact and HFS Research, involving a survey of 2,002 executives across 16 industries, found that only 6 percent of organizations qualified as effective debt re-mediators. Kalra discussed the challenges senior management should consider, emphasizing the importance of tackling technology, data, process, and talent debts before advancing agentic operations.
Kalra highlighted technology debt as the visible issue with deeper underlying problems like data, process, and talent debts, which hinder AI application. He pointed out that AI agents need access to relevant data and enterprise-specific information to function effectively and accommodate varying business processes globally.
Kalra stressed the necessity of integrating IT and governance early in AI discussions. He suggested including the CIO or a CDO at the start to facilitate buy-in and understanding. Security and a responsible AI framework also require attention as AI takes on significant tasks in finance and supply chain operations.
In agentic operations, processes increasingly shift from human-processed and validated to machine-processed and human-validated. However, people remain accountable for exceptions and overall results. Workforce readiness is crucial. Genpact provides staff with access to AI tools to understand their potential, emphasizing the importance of training alongside daily responsibilities.
Tinaikar added that training should not be a privilege but a necessity. Genpact’s skills development focuses on AI builders with technical expertise and business domain knowledge, and AI practitioners with expertise in fields like finance and banking, who develop AI and data skills.
Kalra acknowledged that as AI evolves, tasks and roles will change. Tinaikar cited the smartphone era to illustrate that technological innovations often create new ecosystems and opportunities rather than replace existing technologies. Kalra agreed, noting that advancements lead to new business models and roles.
Kalra cautioned workers that job security might depend on AI proficiency, as more capable models allow for increased automation. Successful scaling relies on usable data, reliable processes, security measures, and adaptable employees.
“Aspirations are high,” Kalra concluded, “but readiness is low.”
The next AI Impact Forum webinar is scheduled for October 22. Dr. Ranjit Tinaikar will discuss enterprise technology and AI with Firdaus Bhathena from S&P Global. Registration is open and free for interested participants.