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Highlights
- Agentic finance is a layered framework that supports strategic, tactical, and operational activities using both assist and autonomous capabilities.
- Task-specific solutions can help organisations achieve results faster, reduce risks, and build long-term efficiency.
- TCS offers a structured approach, supported by a wide range of use cases, that helps organisations identify priorities, design solutions, and scale agentic capabilities across finance functions.
On this page
Introduction
An agentic finance organisation introduces a structured approach to enhancing traditional roles through the use of assistive and autonomous capabilities.
As finance functions evolve, the focus is increasingly on improving efficiency, accuracy, and responsiveness across processes and operations. Integrating AI into finance is becoming an important part of this shift, helping organisations reduce reliance on manual effort, shorten cycle times, and improve the quality of output. At the same time, AI supports better access to insights and enables stronger collaboration between finance and business teams, while maintaining governance and control.
This approach can be understood as a layered model spanning strategic, tactical, and operational activities. Assistive capabilities support tasks such as analysis, recommendations, and documentation, with human oversight, whereas autonomous capabilities are applied to routine, rule-based, multi-step workflows, and are designed to learn and operate within defined boundaries, with escalation mechanisms in place when required. Different finance roles benefit from varying levels of support, depending on the nature of their responsibilities—ranging from strategic, tactical, to operational.
When applied consistently, this model can lead to measurable improvements, including reduced manual effort, shorter processing cycles time, improved accuracy and better visibility into financial performance. It also supports greater standardisation and compliance. Over time, this enables finance teams to shift their focus toward oversight, planning, and business engagement, while routine execution becomes more streamlined.
Why task level design matters
Finance activities can be better supported when solutions are aligned to the specific nature of tasks—strategic, tactical, and operational.
A key consideration in adopting this model is designing agents at the level of individual tasks rather than broad processes. Each task has its own requirements, risks, and outcomes, and aligning solutions at this level improves relevance and effectiveness. Designing at the task level provides several advantages:
- Clear alignment with business needs: Tailored agents to reflect a client’s specific finance processes, data models, and KPIs, delivering measurable ROI from day one.
- Improved control mechanism: Approvals, guardrails, audit trails that match regulatory and internal control requirements can be built directly into workflows.
- Seamless integration with existing systems: Task-focused designs are easier to connect with existing platforms and data sources.
- Faster realisation of value: Prioritising high-impact tasks enable early improvements in efficiency and accuracy.
- Adaptability: Individual tasks can be refined or updated without affecting the entire process landscape. Tailored agents can be iterated quickly to reflect changes to business model and learn from the client’s outcomes.
A structured deployment approach
TCS recommends a phased approach to help organisations introduce changes in a structured and manageable way.
A practical framework begins with developing a clear understanding of the current finance organisation and typically includes three-steps:
Map the finance organisation: Identify roles across functions and geographies, and process areas. This helps establish a clear view of how work is distributed and where inefficiencies exist.
Classify tasks: Break down each role into specific tasks and categorise them as strategic, tactical, or operational. This step enables prioritisation based on complexity, impact, and feasibility.
Design and deploy solutions: Develop task-specific solutions with defined objectives, performance measures, and control mechanisms. Deployment can begin with selected high-impact areas and expand over time.
This staged approach allows organisations to test “Assist versus Autonomous” concepts, measure outcomes, and scale progressively while enforcing standards and driving business value. It also minimises disruption to business by aligning changes with existing organisational structures and workflows.
An illustrative example: Accounts Payable
Accounts Payable (AP) demonstrates how structured, task-level support can improve efficiency and consistency.
In a typical Accounts Payable function, AI agents can be distributed across multiple roles. Managers can leverage various agents to oversee policy adherence, handle escalations, and analytically manage performance. Team leads use agents models to co-ordinate workflows, manage exceptions, and ensure timely payment processing, while specialists can rely on agents to focus on invoice processing, reconciliations, and responding to vendor queries.
Applying a structured, task-focused agentic model helps streamline these activities. Routine processes such as invoice handling and data entry become more consistent, while exception management and approvals follow clearly defined workflows. Vendor interactions can also be handled more efficiently through standardised responses and processes.
This shift enables a move away from manual, exception-driven operations toward more predictable and auditable workflows. As a result, organisations can reduce processing times, improve accuracy, and allow finance professionals to focus more on vendor relationships, analysis, and value-added activities.
Key considerations for adoption
A structured and phased approach supports effective adoption and long-term impact.
Adopting the agentic finance model requires a combination of clear planning, defined priorities, and ongoing monitoring. By mapping roles and tasks, and aligning solutions with specific activities, organisations can create a practical roadmap for implementation. A phased approach for both assist and autonomous agentic models—starting with targeted use cases and expanding gradually—helps manage complexity and build confidence within teams.
A predefined set of use cases across finance areas such as planning, accounts payable and receivable, treasury, and tax can serve as a starting point. These use cases can be adapted to reflect specific organisational needs, with appropriate controls and performance measures built in for distinct roles ranging from junior analysts to senior leaders and executives.
Over time, this approach can help improve efficiency, strengthen controls, and support a more strategic role for finance. By combining structured implementation with continuous refinement, organisations can develop a finance function that is more responsive, accurate, and aligned with business priorities.