Since last year, generative AI has swiftly evolved from being a buzzword to scripting success stories for businesses. According to a recent survey, implementing generative AI at scale can increase productivity by 30% to 50%, with 95% of global customer service leaders expecting AI bots to handle customer interactions within the next three years.
In the first episode of the six-part webinar series, expert leaders touched upon AI’s potential to achieve operational excellence and improve customer experience. It was led by industry leaders Kiran Kuppili, executive director & head of Institutional Banking Group and Payments, DBS Tech India, and Bala Natarajan, VP of generative AI and analytics at Capgemini, India.
With over 28 years of experience in data analytics, AI/ML, and business process management, Natarajan leads a team of 3,500 professionals. He advises global enterprises on leveraging AI for transformation and developing data monetisation models.
Kiran Kuppili was joined by Natarajan, who also has over 20 years of experience in banking IT across the US, European, and Asian markets. He has driven innovation and efficiency as the lead for a conversational AI platform and continues to leverage emerging technologies to propel the digital transformation of DBS Bank.
This marked the beginning of our webinar series with subject matter experts from various industries ready to inspire professionals and cultivate curiosity in the field of data science and AI.
The Learnings
Generative AI in Customer Service: The session highlighted the transformative impact of generative AI on customer service across various industries, emphasising its role in automating tasks and providing personalised recommendations.
Challenges in Asian Markets: The speakers discussed the challenges of deploying AI models in Asian markets, particularly due to language barriers and the need for improved network speeds.
Voice Boards in Call Centers: There was a mention of the use of voice boards to automate call centre tasks, which allows human agents to focus on more complex customer interactions.
Product Development Cycles: How generative AI can accelerate product development cycles, enhancing productivity and efficiency by assisting human teams and reducing launch times.
Trade Document Calculations: An example shared by speakers illustrated how generative AI aids in trade document calculations within customer service, showcasing its practical applications.
Data Privacy and Hallucination Risks: The importance of addressing data privacy concerns and hallucination risks when integrating generative AI into product development.
Governance and Accuracy in Banking: The governance model in banking ensures the accuracy of generative AI responses, maintaining a 90% correctness threshold.
Co-Pilot Approach: Bala described the co-pilot approach where generative AI bots assist humans in handling customer calls, improving metrics like first call resolution.
At DBS, data and artificial intelligence have been key in driving digital transformation across the bank, generating over $370m of incremental economic benefits in revenue growth or expenses saved last year.
The bank’s success is underpinned by its AI Industrialisation Programme, an organisation-wide initiative aimed at driving the pervasive use of AI and ML across its business, reducing the effort and cost of doing so, and delivering economic results at the same time.
DBS embraces generative AI as a powerful “co-pilot” for its employees, aiming to supercharge their productivity and drive efficiency gains and quality improvements. By leveraging the power of GenAI innovatively, they remove toil from their work, which in turn enhances customer journeys while delivering differentiated customer outcomes.
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