Unlock large-scale growth with cloud-powered AI agents
- Cloud and AI agents boost efficiency and personalization, but adoption remains nascent.
- Cloud-powered AI agents unlock value by automating tasks and enabling real-time, personalized CX.
- To maximize impact, financial institutions must redesign processes and align cloud-AI strategies with compliance.
AI is rapidly becoming a cornerstone of almost every industry. Today, it’s everywhere – discussed, adopted, and integrated across sectors. Now, we’re entering the era of agentic AI. Here’s what it means for financial services.
According to Capgemini’s latest World Cloud Report – Financial Services 2026, 87% of financial institutions have implemented some form of AI, but only 10% are using AI agents at scale. This gap represents a major opportunity for banks, insurers, and market operators to move beyond basic automation and embrace the AI-driven revolution.
Meanwhile, cloud platforms have evolved from simple infrastructure providers into powerful innovation engines. Today, they enable AI-driven transformation across the entire value chain, delivering speed, resilience, and compliance in a highly regulated environment. Together, cloud and AI promise faster time-to-market, hyper-personalized experiences, and greater operational agility. However, according to the report, success requires more than technology. It demands a cultural change, robust governance, and a clear roadmap.
Adapt: Embracing AI evolution and cloud’s changing role
AI has traveled an impressive path, from early machine learning models to generative AI and now agentic AI. These intelligent agents go beyond responding to prompts, and now autonomously manage workflows, make decisions, and learn continuously. For financial services, this means moving past traditional tools like robotic process automation toward systems that can handle complex tasks like underwriting, fraud detection, and customer onboarding with minimal human intervention.
According to the report, 75% of banks and 70% of insurers already deploy AI agents for customer service. Other top use cases include fraud detection, loan processing, and claims handling. Yet, despite these advances, only one tenth of firms have scaled AI agents’ enterprise-wide, signaling untapped potential.
Cloud is the enabler of this evolution. Hybrid and multi-cloud strategies are gaining traction, with 26% of financial institutions migrating more than half of their workloads to hybrid environments. The reasons include scalability (87% of respondents), legacy modernization (86% of respondents), and compliance (32% of respondents).
Forge: Creating business value with cloud-powered AI agents
By utilizing the scalability and flexibility of cloud platforms, firms can gain efficiency, optimize operations, innovative topline growth and deliver superior CX.
These agents automate manual tasks such as underwriting and credit scoring, reducing errors and accelerating turnaround times. With orchestration capabilities and unified large language model layers, they enable seamless coordination across workflows and drive real-time decision-making.
Building on these efficiency gains, AI agents also help institutions evolve toward autonomous operating models. Tasks once dependent on human oversight, like risk scoring and policy servicing, are increasingly performed by AI, freeing employees to focus on more strategic initiatives. This shift is supported by smaller, task-specific models that improve speed, explainability, and compliance while reducing compute costs.
Customer experience is another key dimension. Intelligent agents deliver hyper-personalized interactions, proactive query resolution, and faster service, helping banks and insurers boost acquisition, engagement, and retention.
Orchestrate: Building a cloud-native, AI-centric future
The orchestration phase is where strategy meets execution. Financial institutions are mapping business processes to identify where cloud-based AI agents can deliver the greatest optimization. Capgemini’s latest report divides these into 4 categories:
- Quick wins – high-value and easy to adopt
- Open for evaluation – strategic but more complex
- Need for education – simple to adopt but offer limited value
- Investigate – low in both priority and ease of adoption.
Quick wins like credit underwriting and CRM-integrated sales stand out as ideal starting points for rapid returns.
Orchestration goes far beyond technology deployment. It demands strong governance and compliance frameworks. With 96% of executives citing regulatory complexity as a major barrier, institutions must embed explainability, fairness, and accountability into AI systems from the start.
At the same time, numerous behavioral challenges still remain. In fact, 92% of leaders report skill gaps and cultural resistance. Overcoming these requires enterprise-wide AI literacy programs, clear communication of benefits, and collaborative development models.
Closing thoughts
AI agents are poised to redefine financial services, unlocking speed and innovation. Firms should start with a clear buy-or-build strategy that weighs solutions, internal capabilities, compliance, scalability, and privacy, supported by resilient cloud infrastructure.
Leaders must drive an AI-first culture by securing stakeholder buy-in, prioritizing high-value use cases, and enforcing safeguards like human oversight and transparency. Training teams and democratizing access to tools accelerates adoption and creativity.
Embedding these initiatives into digital transformation and cloud strategies enables specialized agents, autonomous operations, and multi-agent collaboration. Combined with a solid cloud strategy to cut costs and remove geographic limits, this approach positions financial institutions to lead the next era of agility, personalization, and growth, where those who act boldly will set the pace for the industry.
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