The Future of Finance Operations: Agentic AI and Evolving Service Models

It goes without saying that artificial intelligence (AI) and automation are changing financial operations.  

But how so, and how fast?  

Agentic AI is on its way to making financial systems autonomous, meaning they will be able to perceive, reason and act with very limited and, in some cases, no human interaction.  The technology can also substantially reduce errors and omissions in transactions recording, reducing time spent finding and fixing inaccurate or incomplete information. 

 Sure, we are just in the embryonic stages, but financial services enterprises are working fast to identify the specific business processes that will gain the most value.  

Unlike today’s generative AI (which requires human prompts) or very scripted robotic process automation (RPA), agentic AI operates continuously and adaptively, effectively functioning as a digital worker. This will no doubt have a dramatic impact on business process outsourcing (BPO) as we know it and, while the potential is undeniable, many CFOs remain cautious. Integrating agentic AI requires more than technology; it demands a shift in mindset, governance and trust in autonomous decision-making systems. 

The Power of Agentic AI in Business Processes 

CFOs should note that agentic AI is not science fiction; it is already starting to take over the simple and transactional tasks that are traditionally outsourced. In finance ops, agentic AI can automatically pull data from systems, analyze it and carry out tasks such as reconciling accounts, validating invoices and adjusting budgets. We are already seeing agentic AI applied to procurement and supply chain.  

BPO service providers are investing heavily in AI capabilities with the intention of transforming their traditional offshore service delivery models to agentic digital employee models. Major financial institutions such as Citibank and tech firms like Salesforce are already experimenting with AI agents that autonomously handle customer service interactions, financial processes, including more complex processes like budgeting, and even compliance and regulatory processes specific to different industries. 

AI Trends Changing Finance Departments 

The rise of agentic AI is one of three trends transforming finance departments: 

• AI-driven automation and intelligent agents: Finance tasks from invoice processing to forecasting are increasingly automated. GenAI and machine learning technology help analyze data, but agentic AI “copilots” autonomously execute processes. These agents can handle unstructured data and exceptions that allow it to learn to adapt workflows rather than rigidly following scripts.

• Continuous close and predictive accounting: The traditional month- or quarter-end close is shifting to a continuous, real-time process. Transactions are recorded and reconciled as they occur, reducing bottlenecks and enabling a "soft close" at any time. With AI, CFOs can gain real-time visibility into cash flow and performance, turning the close into an ongoing, streamlined function rather than a rushed period-end task. 

• Digital twins for finance: Digital twins – virtual models of financial systems – are gaining traction. A digital financial twin integrates data from an enterprise’s ERP system and other systems to simulate financial outcomes. It precisely attributes costs and revenues to products, customers and processes, and can run “what if” scenarios. AI is helping finance departments to use digital twins to predict revenue and profits before they occur and monitor key indicators interactively. In practice, this means a CFO could tweak inputs (like prices or volumes) and see the projected impact on profit and cash in real time. 

Agentic AI in Action: Realistic Scenarios 

The broad promise of AI is a reduction in manual work. Here are some scenarios: 

A large manufacturing company used an AI agent to manage its month-end close process. Interacting with existing systems, the agent autonomously gathered trial balances from multiple ERPs, ran matching rules and even proposed adjusting entries that allowed the finance team to review only the summarized recommendations, cutting the close cycle by roughly 50%.  

A global retail CFO experimented with an AI negotiation assistant for procure-to-pay: the agent analyzed historical payment data, current cash forecasts and supplier credit terms, then engaged with vendors’ digital portals to secure extended payment schedules consistent with policy, the same organization is also using the technology to prioritize early payments, capturing discounts offered by vendors. The ROI on early payments is a multiple of what companies can earn on their cash. P2P systems also make it easier to analyze outlays and identify duplicate payments and contractual issues such as not getting the volume discount. 

In another example, a financial services firm tested an agent that continuously monitors foreign exchange markets and cash positions, autonomously rebalancing currency swaps to hedge risk in real time. In each case, the AI handled the mechanics while the finance team focused on exceptions, strategy and oversight. 

These examples illustrate how CFOs are becoming more comfortable with outsourcing cognitive labor to AI. AI agents can do more than follow rules and checklists – they can understand and apply context, like tax laws and your company’s history. CFOs are envisioning finance staff partnering with AI: humans set goals and guardrails while agents execute routine analysis and planning. 

Impact of BPO 4.0 on Financial Functions 

As internal enterprise finance departments undergo various levels of transformation, the agentic-AI revolution also has profound implications for finance BPOs and consultancies. Traditional outsourcing has thrived on scaled human labor for financial administrative tasks. But if AI agents can perform these tasks 24/7, the traditional human labor cost arbitrage model significantly erodes.  

Already, routine back-office functions like claims processing, reconciliations and simple customer service are being automated end to end by AI, reducing costs for end clients of up to 60%. The new human-first model for BPO is giving way to an AI-first model.  

Figure 1: The Continued Rise of the BPO Industry  

Does this mean that we will see the end of BPO?  

No, far from it, but there will very likely be winners and losers in the service provider community.  

BPO firms that focus solely on human-driven outsourcing may find themselves displaced, but most BPO providers are adapting rather than retreating. Almost all are embedding AI into their offerings and adapting their pricing structures. Instead of simply delivering low-cost labor, they aim to be AI-first, which will take the shape of BPO deals that bundle AI and human labor and are focused on outcomes.  

CFOs can expect to see very different pricing as a result of this shift, and we should expect some degree of turbulence over the next few years as pricing structures evolve. Providers that transform into AI-savvy advisors – managing data governance, model training and ethical oversight – will have a significant role in the future finance transformation ecosystem, so there is a lot of opportunity as well as risk in the industry. 

Preparing for the New Finance Frontier 

For CFOs and finance executives, the agenda is clear. The coming years will see finance operations become smarter, faster and more autonomous, and service providers will be integral to this transformation. To succeed, finance leaders must invest in data quality and AI literacy. This includes establishing governance guardrails for AI usage – ensuring data accuracy, bias controls, security and explainability – as the World Economic Forum and others stress. Executive teams will need to clarify accountability when AI agents act. Teams will need to know: Who signs off on decisions made by an agent? How should I escalate unexpected outcomes?  

At the same time, CFOs should carefully manage the change that is happening in their teams. Staff will be working alongside digital agents, so roles will shift. Many routine accounting and finance jobs may evolve into roles that oversee AI, analyze exceptions flagged by AI and provide strategic insight. Finance departments should proactively upskill in data analytics, AI oversight and cross-functional collaboration for those already in the industry. 

Accounting will become a more attractive career to a wider group of people because there will be much less dull repetitive work. The role of the FP&A group will evolve to facilitate true integrated business planning with faster cycles to promote organizational agility. Treasury departments will be more productive because fewer people will be necessary. Tax departments will have a greater impact by cutting tax expenditures while reducing risk of non-compliance. 

Ultimately, agentic AI and related innovations are tools that can amplify the finance function. When used effectively, they promise to free finance teams from repetitive tasks, deliver near-real-time insight and enable proactive decision-making.  

Key Takeaways for CFOs 

The future of finance operations lies in intelligent, integrated systems, not siloed human processes. Agentic AI sits at the heart of that future, but success will require thoughtful adoption. CFOs who experiment now, build partnerships with tech-forward providers and invest in strong governance will position their organizations for the next wave of finance innovation. 

• Agentic AI is here. Finance teams must evolve from task execution to supervising autonomous digital coworkers that drive speed, accuracy and insight. 

• Outsourcing is changing. Traditional BPO models are being disrupted by AI-first service providers – expect new pricing, expectations and partnerships. 

• Real-time finance is the future. Embrace continuous close, predictive analytics and digital twins to move from reactive to proactive decision-making. 

• Building future finance. The most successful CFOs will not just deploy agentic AI, they will redesign their finance functions around it, positioning themselves as architects of AI-enabled enterprise value creation. 

• Don’t do it alone. Your particular challenges may be unique to you but unlikely to be unique overall. Don’t be afraid to ask for external support. 

ISG helps enterprises navigate the current state of AI and get ready for the future of AI – where to invest, upskill and support their employees. Contact us to find out how we can help you.