How FS firms can transform use cases and accelerate impact with AI
In brief
- Agentic AI goes beyond generative chat: It employs agents that plan, act, and adapt across banking and insurance throughout the cloud modernization lifecycle
- Most financial services (FS) firms stall at pilots: Why? Because they’re worried about the ramifications of agent behaviors, they haven’t experienced it themselves and need someone who has guided others to implement at scale. Agentic AI reimagines business flows by enabling systems to make autonomous decisions, adapt in real time, and optimize outcomes across complex processes. A proven approach and platform accelerate time to value by aligning AI capabilities with clear business goals, reducing friction from experimentation to deployment.
- Governance is non-negotiable: explainability, human-in-the-loop, logging, and security must all be built in from day one to satisfy regulators and auditors. Every agent interaction should be made visible to avoid black box behavior.
Why agentic AI? And why now?
Financial services organizations are under pressure. Costs are up – so is inflation. Regulators are watching. Customers expect speed and personalization. Agentic solutions can think, take decisions, and pick the right path to execute, which brings sophisticated automation to human intensive legacy processes.
Generative AI (GenAI) helps with assistive work – like answering questions and drafting copy – but it’s limited. Agentic AI is the new frontier, offering agents that can plan, act, and adapt in real time. Take claims triage, fraud checks, and loan onboarding as few examples. The payoff is cycle-time reduction, higher straight-through processing, and consistent decision-making in a cost-effective manner. While generative AI enhances individual tasks, agentic AI drives end-to-end value by integrating reasoning, memory, and control into enterprise-scale processes. Most financial services organizations recognize this need. The question is: how? Learn and build everything in-house, or accelerate with a baseline platform and proven partner? Scaling is hard. And the reality on the ground is clear: when it comes to AI adoption, only 26% of companies have the capabilities to move beyond proof of concept and create value at scale.1 The rest stall in pilots. Meanwhile, AI is broadly used. As many as 78% of organizations report using AI in at least one function.2 And yet, end-to-end redesign still lags.
Why so many stalls? Several reasons:
- Classic project risk plays a role. Only 12% of business transformation projects are successful.3
- Newer analyses of large IT programs show that only 31% meet their “success” criteria.4 Big programs fail far more often and suffer overruns.
- Agentic AI is a complex, multi-dependency program: governance, data, models, controls, and organizational change all at once.
Building bespoke “inside the perimeter” programs can work, but many…
Read More: Reimagining financial services with agentic AI
