By: Alexander Turgeon & special guest, Abhijit Singh
Agentic AI will fundamentally reshape finance and accounting in 2025, surpassing traditional machine learning capabilities, which has long been a cornerstone in the industry, powering fraud detection and complex analytical models. However, recent advancement has elevated AI’s role from assisting in tasks to autonomously managing and improving them. Agentic AI, which can learn, adapt, and perform complex tasks independently, promises to reshape critical areas like fraud detection, compliance, customer interaction, and operational efficiency. This report explores how these trends will redefine finance and accounting, integrating practical use cases and actionable strategies to help organizations leverage its transformative power.
Key AI-Driven Advances Impacting Finance & Accounting in 2025
1. Advanced Proactive and Adaptive Security
The rapid growth of digital payments has led to a surge in cybercrime, with bad actors increasingly leveraging AI for sophisticated fraudulent activities. To counter this, financial institutions are turning to advanced AI systems for fraud detection. By 2025, fraud detection tools powered by agent-based AI and workflows will play a pivotal role in securing high-volume transactions. These systems can autonomously monitor transactions in real-time, leveraging deep learning to identify unusual patterns and dynamically adapt to new threats. Unlike traditional models, Agentic AI evolves alongside cybercriminal tactics, providing a proactive and robust defense mechanism.
The integration of real-time monitoring and pattern recognition enhances the ability to preemptively detect and mitigate fraud, safeguarding both businesses and customers. This shift from reactive to adaptive security ensures that organizations remain ahead of evolving cyber threats.
Actionable Insight: Financial institutions should implement AI solutions that offer continuous adaptation and real-time responses. Prioritize platforms capable of anomaly detection and predictive modeling to tackle security challenges proactively and effectively. This strategic investment not only enhances fraud prevention but also builds customer trust through improved data protection.
2. Transforming Operational Efficiency
Generative AI, initially known for content creation, has evolved into a transformative force in financial workflows. It now automates tasks such as transaction categorization, data processing, and customized reporting, dramatically improving operational efficiency. However, the integration of Agentic AI amplifies these capabilities by autonomously managing more complex processes, including financial close operations and predictive risk modeling. These advanced systems not only streamline workflows but also minimize errors and uncover insights at unprecedented speeds.
Financial institutions are particularly drawn to these innovations for their potential to drive productivity within daily operations. By leveraging AI, banks and finance teams can transition from reactive operations to proactive strategies, enabling faster decision-making and unlocking new opportunities for value creation.
Actionable Insight: Financial institutions should adopt AI platforms to automate and refine complex workflows. Training teams for effective integration and ensuring continuous system feedback will boost adoption, enhance productivity, and maximize ROI. Prioritize solutions that evolve with operational needs, ensuring sustained efficiency and innovation.
3. AI-Powered Accounting Agents for Elevated Personalization and Efficiency
The rise of advanced AI is transforming how accounting and finance software companies deliver personalized experiences. These AI-powered accounting agents autonomously manage routine tasks, significantly improving both external customer interactions and internal operations.
For external clients, AI agents, such as chatbots, handle customer inquiries, reducing the burden on customer service teams and allowing human agents to focus on complex, high-value requests. These systems adapt to user behavior, providing tailored responses and seamless support that enhances the overall customer experience. Internally, AI agents streamline processes by independently searching, interpreting, and analyzing critical information, drastically reducing time spent on manual research, meetings, and documentation. Agentic AI takes these capabilities further by enabling personalized financial planning, regulatory interpretation, and optimization of operational workflows, all without constant human intervention.
Actionable Insight: Identify time-intensive tasks, both customer-facing and internal, and deploy AI agents to automate these processes. Choose platforms that integrate natural language understanding with domain-specific knowledge to deliver tailored insights. This approach frees teams to concentrate on high-impact activities like risk management and strategic planning while enhancing customer satisfaction and operational efficiency.
4. Regulatory Compliance Monitoring
In the finance sector, regulatory compliance is a top priority, requiring constant adaptation to evolving legal standards. In 2025, advancements in Agentic AI and natural language processing will empower AI systems to autonomously interpret complex regulatory texts, identify updates, and ensure organizations remain aligned with the latest requirements. These systems provide continuous monitoring and real-time audit capabilities, significantly reducing the risks of non-compliance while streamlining reporting processes. Agentic AI takes this a step further and enhances compliance by not only detecting regulatory changes but also recommending actionable steps to address them. Its ability to adapt to industry-specific legal challenges ensures that organizations remain agile and prepared in the face of shifting regulations.
Actionable Insight: Invest in AI-driven compliance tools that integrate fraud detection and compliance monitoring into a single solution. Partner with regulatory experts to refine these systems, ensuring they address the unique needs of your organization. Proactive adoption of these technologies minimizes legal risks, supports seamless audits, and helps maintain a competitive edge in a highly regulated industry.
5. Adapting Customer Experience
Artificial intelligence is revolutionizing customer interactions in finance and accounting, offering real-time assistance, hyper-personalization, and intuitive guidance. In 2025, Agentic AI will elevate user experiences by autonomously adapting to individual preferences, delivering tailored financial advice, and streamlining routine operations. These systems allow users to ask specific questions and receive customized insights instantly, ensuring a truly personalized and engaging interaction.
Routine tasks such as data entry and reconciliation will be fully automated, requiring minimal human intervention. This shift enhances efficiency, reduces errors, and frees up time for higher-value activities. Agentic AI goes beyond standard automation by continuously learning from user behavior, ensuring platforms remain relevant, accurate, and aligned with customer needs.
Actionable Insight: Leverage Agentic AI to provide personalized, real-time insights and automate repetitive workflows. Regularly refine systems using user feedback to enhance adaptability and maintain efficiency. Organizations that invest in these capabilities will not only improve operational effectiveness but also build stronger, more loyal customer relationships.
6. Scaling AI Solutions with Robust Data Architectures
As AI becomes integral to finance, ensuring transparency, security, and fairness is critical — but it demands not only robust and scalable data architectures but also rigorous oversight to address biases, privacy concerns, and data security risks. A Bain survey found that over 80% of companies plan to reshape their data structures to leverage AI. For finance and accounting, this means investing in scalable, cloud-based AI infrastructure that supports data-intensive applications like fraud detection and risk management. By 2026, financial organizations that haven’t optimized their data architectures will struggle to compete.
Regular audits will be essential to ensure that AI processes, particularly in sensitive areas like loan approvals and fraud detection, remain unbiased and transparent. The democratization of AI tools increases the risk of data mishandling, particularly when sharing data with third parties under SaaS models. As use cases expand to incorporate diverse data sources, the scrutiny around privacy and accuracy will intensify, making early integration of security measures a non-negotiable priority.
To support these systems, scalable, cloud-based architectures with real-time processing capabilities are imperative. These frameworks must handle the increasing data complexity and ensure security and adaptability, allowing AI systems to make autonomous decisions effectively. Without such infrastructures, organizations risk falling behind in an evolving AI landscape.
Actionable Insight: Establish robust routines for ethical AI audits, addressing biases and embedding security measures early in AI development. Collaborate with AI specialists, IT teams, and data architects to design scalable and secure infrastructures capable of supporting autonomous operations. This dual focus on transparency and scalability will help organizations build customer trust, ensure compliance, and maintain a competitive edge.
7. Promoting Transparency and Security with Scalable and Ethical AI Solutions
As AI becomes integral to finance, ensuring transparency, security, and fairness is critical. Actionable AI demands not only robust and scalable data architectures but also rigorous oversight to address biases, privacy concerns, and data security risks. By 2025, organizations must embed ethical AI practices and scalable infrastructures into their operations to manage the growing complexity of AI-driven applications.
Regular audits will be essential to ensure that AI processes, particularly in sensitive areas like loan approvals and fraud detection, remain unbiased and transparent. The democratization of AI tools increases the risk of data mishandling, particularly when sharing data with third parties under SaaS models. As use cases expand to incorporate diverse data sources, the scrutiny around privacy and accuracy will intensify, making early integration of security measures a non-negotiable priority.
To support these systems, scalable, cloud-based architectures with real-time processing capabilities are imperative. These frameworks must handle the increasing data complexity and ensure security and adaptability, allowing AI systems to make autonomous decisions effectively. Without such infrastructures, organizations risk falling behind in an evolving AI landscape.
Actionable Insight: Establish robust routines for ethical AI audits, addressing biases and embedding security measures early in AI development. Collaborate with AI specialists, IT teams, and data architects to design scalable and secure infrastructures capable of supporting autonomous operations. This dual focus on transparency and scalability will help organizations build customer trust, ensure compliance, and maintain a competitive edge.
8. Prioritizing Practical and Impactful AI Applications
As AI technology continues to evolve, its successful implementation in finance and accounting depends on prioritizing tools that deliver measurable value. By 2025, organizations must take a strategic approach, focusing on AI applications that align directly with their core business objectives. Not every AI tool is worth adopting, separating meaningful solutions from hype will be key to driving efficiency, accuracy, and customer satisfaction.
Agentic AI offers significant potential, but its impact is only realized when deployed in areas that provide tangible benefits. Companies that focus on practical applications, such as improving operational workflows, enhancing decision-making, and delivering personalized customer experiences, will achieve the highest return on investment. By aligning AI innovations with real-world needs, organizations can maximize efficiency and create sustained value.
Actionable Insight: Prioritize AI applications that support specific business goals. Establish clear metrics to evaluate the performance and impact of each implementation, ensuring ongoing alignment with organizational objectives. This disciplined focus will enable companies to unlock AI’s transformative potential while avoiding wasted investments in underperforming solutions.
Looking Forward
The future of finance and accounting is inextricably linked to Agentic AI. By 2025, organizations that adopt strategic, impactful AI solutions will gain a competitive edge, driving innovation, efficiency, and customer satisfaction. Valere is committed to guiding clients through this transformation, helping them unlock AI’s full potential.
Connect with Valere to explore how our Agentic AI solutions can reshape your finance and accounting strategies, ensuring you stay ahead in an evolving landscape.
About the Authors
Abhijit Singh is an accomplished professional in the financial technology space, bringing a wealth of industry experience across diverse areas such as payment cards, accounts payable, and accounting. With a proven track record of driving innovation and efficiency in fintech solutions, Abhijit combines extensive domain expertise with a passion for creating impactful financial products.
Alexander Turgeon is Valere's President. Prior to joining Valere, Alex had worked with organizations such as Digital.gov , USPS, including leading the UX redesigns for Tracking, PO Locator, USPS Click-n-Ship, USPS Connect, and COVIDTests.gov alongside the White House USDS. We has also supported a myriad of B2B, consumer-facing, and large public sector clients, such as the Internal Revenue Service (IRS), and work for the Department of the Treasury (Treasury) in support of the Department of Homeland Security (DHS).