Key features of generative AI co-pilot that unlock untapped workforce potential: Generative AI introduces the co-pilot era, enhancing workforce efficiency by seamlessly collaborating with human operators and offering insights, recommendations, and adaptive assistance. The bank employees we surveyed identified the following critical co-pilot elements that could increase their productivity.
As banking agents struggle with daily tasks, customer engagement dips: Only 9% of a bank’s customer onboarding team time is allocated to customer interaction, and a substantial portion of that time concerns addressing process-related questions. Contact centre employees dedicate 82% of their time with customers to operational and support tasks, instead of focusing more productively on customer needs and sales.
Most banks lack readiness for generative AI-led intelligent banking: Banks face several impediments in adopting enterprise-wide AI due to legacy systems and incompatible processes. Most banks are unprepared for intelligent banking driven by generative AI, lacking business, technology, and data readiness.
Banks are lagging in developing KPIs to gauge generative AI performance: Assessing the impact of generative AI is crucial for banks across numerous aspects of strategy and performance. Understanding impact helps evaluate AI systems and ensures they align with the bank’s objectives and benchmarks. Despite its importance, many banks are lagging in implementing effective KPIs for monitoring generative AI impact.
Details
Date: Tuesday 4th June
Time: 12.00 pm – 2.00 pm
Venue: Bentley Restaurant + Bar, Sydney CBD