Key Findings & Highlights:

While automation and machine learning have already been incorporated in extensive numbers of digital use cases, these technologies are now being complemented by and combined with generative AI (GenAI).

GenAI does not necessarily replace narrow AI and ML solutions or RPA technology, as certain functions continue to benefit from specialized, task-specific models or workflows; these models often deliver greater precision and reliability for a lower cost base in comparison to more general reasoning technology.

GenAI is still a relatively new area, with clients unsure about the true capabilities of the technology, vendors still in the process of integrating these technologies into platforms, and regulatory authorities trying to keep up with developments.

Deployments have been led by customer service engagements, in use cases that aim to expand on previous automation efforts, with early deployments in areas such as payroll and recruitment workflows. These processes have tended to have strong existing data pipelines or knowledge databases that the AI can leverage.

In more advanced use cases, vendors are creating agentic processes, reducing the need for human operators by up to 95% by minimizing the need for L1 employees. Organizations have been upskilling their employees as they shift to GenAI-enabled operations; for example, allowing human agents who previously handled just two conversations in customer service engagements to supervise ten conversations at once.

North America is currently the most advanced region for GenAI adoption, albeit still fairly nascent. Organizations in the region have been first to develop proofs of concept and therefore have moved to enterprise-wide deployments, particularly across customer experience, finance, and HR operations. Regulation remains relatively light: there is no federal AI law, and governance is driven largely by sector-specific regulators, a handful of state regulations such as Colorado’s AI Act (CAIA)/California’s Transparency in Frontier AI Act (TFAIA), and voluntary corporate frameworks. This will change in the future, however, as shown by the 2025 AI Action Plan, though these regulations at the federal level will likely be less cautious than the EU AI Act.

Financial services are among the earliest and most aggressive adopters of GenAI for operational transformation. Banks, insurers, and investment firms have been faster to integrate generative models into customer service, document processing, compliance, and fraud monitoring, in part thanks to the industry’s maturity with data readiness.