Reimagining financial decision-making, work and value in the age of AI

The finance function is at an important crossroads, with tradition and innovation colliding as the era of artificial intelligence introduces new opportunities to innovate, evolve and transform.

While many finance teams still use traditional approaches to advise their organizations on finance strategy, recent research shows that a shift is happening: 63% of finance leaders now actively use AI solutions at their organizations.

With all this transformation underway, the future of finance could look very different. In fact,  80.5% of finance and accounting professionals believe AI-powered tools will become mainstream in finance and accounting by the year 2030. But what might mainstream finance AI actually look like — and more importantly, what can leaders do today to get there?

Work itself will change

Automation continues to dominate CFO agendas today, with 50% of CFOs ranking digital transformation of finance as a key priority for 2026 — a trend likely to shape how the finance function evolves through the  remainder of the decade. 

Agentic AI in particular presents a transformative opportunity for finance, with finance leaders recognizing agentic AI's potential to automate data entry, deliver real-time insights, and enhance areas such as sales and profitability management (48%) and working-capital optimization (46%).

Today, finance teams devote the majority of their time to manual self-service reporting, static dashboarding and ad hoc analysis, often repeated weekly, monthly or annually. The balance of their time may be spent reviewing or interpreting results. As agentic AI becomes more capable, this ratio could change dramatically: AI tools could reduce time spent on routine activities and review cycles, freeing capacity for more forward-looking, strategic work.

To enable this transformation, finance leaders can do more than simply implement new technology. They can champion AI adoption by creating a culture of continuous learning and experimentation, focused on empowering professionals and building AI literacy and skills. This shift also requires reimagining and redefining roles and workflows to emphasize human-driven judgment enabled with agentic capabilities. Change management will be critical for setting expectations and resolving challenges. This is all in addition to developing and refining AI solutions, tracking progress along the way and celebrating when AI leads to higher-value and more impactful work.

If finance leaders can get the approach right, finance professionals could spend less time on manual, repetitive tasks and more on synthesizing insights, solving complex problems and driving strategic decisions and value. By 2030, the finance function could evolve into a strategic capability hub, with AI as the co-pilot enabling faster, more informed actions — always anchored by human curiosity, judgment, and creativity.

Decision-making will get smarter and more strategic

AI agents are poised to deliver two transformative outcomes for finance leaders: unlocking advanced forms of decision-making and expanding the function's ability to offer strategic support across the organization.

Currently, many finance teams still rely on conventional analytical methods when faced with critical decisions around funding, investments and forecasting. However, the landscape is evolving. By 2030, finance functions could leverage AI not just as a set of tools, but as intelligent, agile, data-driven partners capable of real-time analytics, continuous scenario modeling, and harnessing vast, previously inaccessible datasets. All of this helps drive sharper, faster decisions that meaningfully contribute to enterprise strategy.

Finance leaders have already begun this transition, with 57% of surveyed leaders saying they play a leading role in shaping enterprise strategy today. As AI amplifies analytical depth and bandwidth, financial professionals will be able to devote even more time and expertise to high-value, strategic decision-making that drives growth and differentiation for their organizations.

To capitalize on this shift, finance leaders can expand their roles from monitoring the outcomes of existing strategies to actively shaping and convening enterprise-wide conversations. This means becoming a pivotal hub for a broader spectrum of business intelligence, confidently integrating financial and non-financial data — such as operational metrics or workforce analytics — to optimize execution and drive smarter decision-making.

Achieving this vision will require finance leaders to break down data silos and forge new connections between traditionally separate data sources. For example, linking employee talent survey results with overall business performance data can reveal powerful correlations and augment decisions. If information such as talent data remains isolated within human resources, the organization may risk missing key drivers of success. As AI unlocks new frontiers for the future of finance — both with regard to financial and non-financial data integration — finance will increasingly fuel smarter strategies and become an even more critical enterprise enabler. 

Process redesign can unlock measurable AI impact

AI's benefits to financial workstreams, decision-making and strategic support may be unfortunately limited if AI is not used to its full potential. 

While many finance leaders are experimenting with AI, only a minority are seeing clear, measurable value from their investments: Just 21% report tangible results, and only 14% have fully integrated AI agents into their finance functions. This highlights a significant gap between piloting new technologies and achieving sustained, enterprise-wide adoption.

This disconnect arises when AI — particularly large language models and agentic tools — is deployed in a piecemeal fashion, applied to isolated tasks instead of being woven into the very fabric of end-to-end finance processes. When AI is bolted onto existing workflows without a broader process redesign, efficiency gains are limited, and downtime or rework can persist across the organization. The result is unrealized value left on the table. 

To move beyond one-off use cases and realize true value, finance leaders will need to consider adopting a more strategic, iterative approach: Start by identifying areas where technology can elevate human work, and then thoughtfully integrate both engineers and finance professionals, refining how they collaborate and support each other throughout the process lifecycle.

In the future of finance, the success of AI tools won't depend on scattered individual initiatives, but on establishing a standardized, embedded approach across teams. For instance, some organizations may benefit from setting up a "center of excellence" where AI agents function together as an extension of the finance team, while other organizations may bring in specialized engineers to infuse targeted capabilities into specific finance workflows. 

Whatever the model, the key is to move toward an enterprise-wide AI strategy.

As finance leaders look toward the end of the decade, the opportunity ahead is not simply about adopting new technologies but about reimagining how finance creates value for the enterprise. AI can provide the means to elevate decision-making, transform how work gets done, and redesign experiences — but only if leaders rethink how finance functions in relation to the broader organization.

Finance leaders who embrace this moment may have an easier time unlocking the full potential of finance and, in doing so, position the function not only to respond to change, but to lead through it.