Generative AI (GenAI) has dominated headlines, product launches, and investor calls across industries; finance is no exception. According to a recent Thomas Reuters report, 89% of tax professionals believe GenAI has the potential to improve workflows. Yet only 21% of firms have implemented it enterprise-wide. The enthusiasm is evident, but so is hesitation.

For most CFOs and controllers, the question isn’t if GenAI can help, but how to adopt it without compromising accuracy, compliance, or audit readiness. Early models didn’t inspire much confidence. Data fragmentation, weak governance controls, and limited financial context made it hard to trust outputs. Without a clear return on investment, many finance leaders hit pause.

However, with mounting pressure to modernize and rapidly maturing GenAI capabilities, finance leaders face the critical question of where to apply it for maximum impact.

The Real Roadblocks: Trust, Training, and Tooling

While there’s no shortage of hype around GenAI’s potential, finance professionals are rightly pragmatic. Their work demands precision, auditability, and data integrity. It’s not enough for a tool to be impressive; it must be dependable.

72% of firms offer no GenAI-specific training, and 70% lack responsible use policies. For finance leaders, these are nonstarters. AI applications can become more of a liability than an asset without transparent governance, complete transparency, and domain-specific accuracy.

This is where purpose-built platforms offer an edge. Rather than using generic GenAI tools that rely on vague language models, finance teams need platforms designed around their workflows, from reconciliation and reporting to compliance and strategic planning.

Applying AI Where It Matters Most

Finance teams are adopting a use-case-first mindset to move from curiosity to implementation. Instead of asking what GenAI can do in theory, they’re asking where it can accelerate outcomes in practice. The most immediate wins often come from high-friction, high-volume processes that traditionally consume analyst time.

Some of the most effective GenAI applications in finance today include:

Intercompany reconciliation : High-volume transactions across multiple entities often require hours of spreadsheet wrangling and error chasing. GenAI can automate account assignments, categorize entries, and generate audit-ready documentation. Organizations using these solutions have reported up to 95% reduction in reconciliation time and a complete elimination of manual errors.

: High-volume transactions across multiple entities often require hours of spreadsheet wrangling and error chasing. GenAI can automate account assignments, categorize entries, and generate audit-ready documentation. Organizations using these solutions have reported up to 95% reduction in reconciliation time and a complete elimination of manual errors. Month-end cost assurance : By automatically mapping general ledger data, validating expenses against compliance benchmarks, and producing variance analysis reports, finance teams can cut up to 30 hours monthly from the close process while improving accuracy and compliance confidence.

: By automatically mapping general ledger data, validating expenses against compliance benchmarks, and producing variance analysis reports, finance teams can cut up to 30 hours monthly from the close process while improving accuracy and compliance confidence. Sales tax compliance and discrepancy resolution : Multi-jurisdictional tax calculations are notoriously complex. With GenAI, teams can streamline tax prep, resolve mismatches by region, and reduce compliance risk through automated checks and balanced summaries.

: Multi-jurisdictional tax calculations are notoriously complex. With GenAI, teams can streamline tax prep, resolve mismatches by region, and reduce compliance risk through automated checks and balanced summaries. Real-time KPI tracking: Instead of manually aggregating performance data, finance teams can automate the calculation and reporting of metrics like gross profit margin and net income, giving leadership more insights.

In each of these cases, GenAI isn’t replacing financial judgment. It’s eliminating repetitive, error-prone tasks so teams can focus on strategic thinking instead of spreadsheet firefighting.

From Workflow to Win: A Smarter Platform Approach

What sets successful GenAI deployments apart is the platform. Innovative tools combine agentic AI with no-code analytics automation to help finance teams do more with less, without needing to retrain staff or overhaul existing systems.

Certain AI-powered tools, for example, can remove extra steps in the reconciliation and reporting process. They enable users to prep, blend, and analyze data without coding, offering intuitive, real-time assistance through familiar workflows. This is especially valuable in finance functions where audit traceability, data lineage, and secure access are non-negotiable.

An effective GenAI and automation solution should offer complete transparency through end-to-end documentation, governed access, and standardized workflows aligned with enterprise-grade security requirements rather than operating as a black box. Modular, no-code tools that support data preparation, cleaning, and blending can help finance teams unify information from systems like Excel, Netsuite, and Oracle without disrupting existing processes.

Empowering Analysts, Not Just Engineers

GenAI adoption has stalled in finance because of the outdated assumption that only engineers can work with analytics tools. But in reality, the future of finance is empowering analysts, the 80 million domain experts worldwide who understand the business and know what questions to ask.

Today’s most effective platforms are closing the gap between data expertise and financial domain knowledge. Finance professionals no longer need to rely on technical teams or write SQL to build reconciliations, automate reporting, or resolve discrepancies. With intuitive, no-code interfaces and natural language capabilities, they can directly manage data workflows, reducing delays and enabling finance to respond faster to business needs.

Turning Excitement Into Execution

GenAI isn’t just a buzzword anymore; it’s a productivity tool when applied thoughtfully. Finance teams focusing on concrete applications, transparent governance, and AI-native platforms are already seeing major returns: faster closes, fewer errors, stronger audit readiness, and more time for forward-looking analysis.

The hype around GenAI isn’t the problem. The problem is when the hype isn’t paired with real results. Finance teams don’t need more lofty promises; they need solutions that work today, in the systems they already use, and in the language they already speak.

Finance leaders can finally bridge the gap between potential and progress by focusing on the workflows that matter most and partnering with tools that prioritize trust and transparency.

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Teresa Fortescue is SVP of Marketing at Savant Labs.