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What is agentic AI and why banks are betting on it for frontline sales – Crypto News
Agentic artificial intelligence is emerging as a powerful force in frontline banking, with early adopters already reporting tangible gains in sales productivity and revenue, according to a new report by McKinsey.
The consultancy says the technology could fundamentally change how relationship managers work, easing long-standing pressures caused by poor leads, fragmented systems and heavy administrative demands.
Unlike conventional generative AI, which responds only when prompted, agentic AI systems can interpret goals, break them into tasks and act autonomously across multiple systems. This ability allows them to manage complex workflows that have historically proved difficult to automate in financial services.
Productivity gains within months
McKinsey notes that several global banks are already using agentic AI across prospecting, lead nurturing and account management. In these cases, improvements have been recorded within months rather than years.
Industry data cited in the report suggests that when banks redesign frontline operations end to end around agentic AI, revenues per relationship manager can increase by between 3% and 15%. At the same time, the cost to serve clients can fall by 20% to 40%.
The findings come as banks face growing margin pressure, slower growth and rising cost-to-income ratios. McKinsey argues that agentic AI should be viewed not simply as a productivity tool, but as a new operating model for relationship management.
Tackling long-standing pain points
Frontline bankers have long complained about the quality of leads, complex compliance requirements and disconnected technology platforms. Many spend large portions of their time updating customer relationship management systems or preparing internal reports, leaving less time for direct client engagement. This has contributed to burnout and high staff turnover in sales teams.
Agentic AI aims to rebalance this workload. Intelligent agents can continuously scan markets, analyse both structured and unstructured data, and identify high-potential prospects. They can also automate follow-ups and prioritise opportunities, escalating only the most promising leads to human bankers.
More time for clients, not paperwork
In sales outreach, AI agents are able to personalise communications at scale and nurture thousands of prospects simultaneously. Banks testing these systems report that sales pipelines have expanded by around 30% in some cases, while the number of qualified leads has doubled or even tripled.
AI-powered account intelligence tools have also reduced the time needed to prepare for meetings, while improving the depth and relevance of client discussions. With routine tasks handled by machines, relationship managers can focus on higher-value conversations and complex client needs.
This shift allows bankers to operate more as trusted advisers, concentrating on insight-driven advice, strategic problem-solving and long-term relationship building.
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