The future of financial operations 2026

2026 is nearly here, so let's look at some trends we can expect to affect the work of finance teams and leaders around the world. In 2025, we saw exponential growth of AI, hybrid cloud adoption, and digital transformation. In the next year, we're likely to see AI agents and automation tools take charge of even more tasks, and the role of finance leaders evolving into a more strategic one.

Delegating manual work to AI agents

AI is still reshaping financial operations, and using AI agents has grown rapidly in 2025. In a Deloitte survey conducted among finance leaders, nearly half of the respondents had integrated AI agents into their financial processes. Going forward, CFOs see AI agents as especially helpful in:

• financial planning and analysis - improving forecasting accuracy and real-time scenario analysis
• sales and profitability management - tracking which services are most profitable and identifying sales trends
• working capital optimization - agents could help manage day-to-day cash flow by identifying money tied up in inventory and strategically timing payments
• expense management - flagging unusual expenses and suggesting where to cut costs without hurting the business
• analyzing customers - using agents to scan accounts receivables and identifying possibly lawbreaking clients

Leaving these tasks to AI agents will free up finance teams to focus more on valuable strategic planning and driving growth.

Finance leaders will contribute more to the overall strategy

The role of the CFO seems to be moving from purely finance operations to a strategic one. As the required skills for finance leaders keep increasing, so does their influence on the company's general strategy. To manage their growing scope, CFOs are turning to AI to widen their skill sets and delegate some of their tasks.

Deloitte's survey showed that finance leaders with the power to influence the overall strategy use AI to optimize costs, take more advantage of existing data, and increase productivity. This gives them more time to focus on larger goals with other departments, instead of focusing only on the finance team's function.

In 2026, we expect the same pattern to continue and see finance leaders contributing more to the company's growth. AI will play a huge role in this by taking charge of more routine tasks.

Less manual work thanks to specialized automation tools

Payment and bank reconciliation and data matching are tasks that normally require finance teams to manually cross-reference thousands of transactions. Thanks to specialized solutions that are now available specifically for finance, you can automate these routine tasks with high accuracy.

Finance teams are rapidly adopting workflow automation tools that can eliminate hours of repetitive manual work. Among finance leaders, 49% are using AI to identify cost-reduction opportunities, with many already deploying automation to simplify repetitive processes and eliminate manual verification in transactions. (Deloitte Insights)

Modern automation platforms can be adapted to fit each company's unique workflows, data structures, and business rules, and no longer require finance teams to change their processes to fit inflexible software. Organizations are using automation for fee analytics, customer billing workflows, and revenue reporting, with the technology helping finance teams focus on higher-value work rather than manual data entry and verification.

With a growing number of automation tools, finance teams can expect to delegate most repetitive work in 2026, freeing up time for strategic analysis and decision support.

‍

More collaboration between finance teams and external AI providers

MIT's research showed that 95% of enterprise AI initiatives fail to deliver the expected effects. The study's key finding was that internally built AI solutions fail twice as often as strategic partnerships with external providers (33% vs 66% success rate). This is due to several factors:

• The team builds a tool that works at first, but doesn't improve. This causes users to abandon it because it repeats the same mistakes.
• Building AI for financial workflows requires both ML expertise and deep finance process knowledge, but few internal teams have both
• The company's best engineers get pulled into higher-priority projects and lack the time to develop a well-thought-out product

These findings suggest that companies will soon realize the value of external partners who have enough resources and knowledge to build the necessary AI tools. Instead of putting effort into building something from scratch, companies will rather rely on tools that are proven to work for finance and operations teams.

Preparing for the future of financial operations

Automation, data-driven insights, and hyper-personalization will define the financial operations landscape in 2026. As emerging technologies reshape workflows, skill requirements, and customer expectations, financial institutions must rethink their operating models, workforce strategies, and innovation investments today.

Leading practices to optimize for the data-driven future of financial operations include:

• Identifying automation opportunities across operations
• Implementing AI solutions for predictive insights
• Reskilling workforces on digital and analytics capabilities
• Building partnerships with fintech innovators

By getting ahead of the trends today, finance leaders can ensure their organizations maximize efficiency, reduce risks, and deliver better customer experiences powered by data and technologies like AI.

‍