Finance teams are trapped in a relentless cycle. Recurring demands like month-end closes, quarterly re-forecasting, and annual budgeting create bottlenecks that leave little time for process improvement.
Meanwhile, disconnected systems and siloed data lock teams into tedious manual workflows.
That means high-value professionals are pulling levers instead of driving strategy, with forecasting often reduced to guesswork and reporting constantly delayed.
AI and automation offer powerful solutions to break this cycle, reducing manual touchpoints and freeing up teams to focus on analysis and strategy.
But many teams get stuck on the starting line. Which processes should you automate first? How do you prove ROI to skeptical stakeholders? And how can you avoid overwhelming your team?
To get the answers to these questions, we spoke with Burt Y. Chao, Chief Financial Officer at Nintex, who has deep experience implementing process improvement, automation, and AI across core workflows.
From forecasting to invoice processing to audit prep, he shares his view of the finance processes where automation delivers the most value — and how your team can follow suit without needing to hire a dedicated data scientist.
1. Automating onboarding to attract and retain top talent
Financial talent is getting harder to find and even harder to keep. Approximately 75% of the CPA workforce will retire in the next 15 years, according to the American Institute of Certified Public Accountants (AICPA). Nearly 334,000 accountants left the profession between 2019 and 2021 alone, according to Bureau of Labor Statistics data.
The Bureau of Labor Statistics also predicts increasing demand for professionals in Financial Planning and Analysis (FP&A), with six percent projected change in job offerings between 2024 and 2034 for financial analysts, financial and investment analysts, and financial risk specialists — that’s faster than average for all occupations.
And the pipeline for incoming talent isn’t looking much better: Accounting degree completions dropped 7.7% in 2022, hitting their lowest point since 2007.
As seasoned professionals retire, finance leaders are left competing for a shrinking pool of qualified talent. At the same time, younger employees entering the field want more than repetitive tasks. They want roles that feel meaningful and strategic.
“If you think about the workforce that’s coming up, they don’t want simple task orientation,” says Chao “They don’t want to come in and repeat tasks every single day. They want to feel like they’re driving value through innovation.”
For finance leaders, this means using automation to improve the employee experience from day one. Automating onboarding and role changes, like promotions and department moves, is a solid way to improve the employee experience. By creating a smoother, faster, and more welcoming journey, you can show new hires that you value them and give them reasons to stay.
How to get started
Begin by mapping your current employee onboarding and change processes. Document every manual step — from account setup to software provisioning to approvals — and identify where delays or handoffs occur.
Next, create a standardized intake form with Nintex that collects necessary information like department, job title, access needs, manager, and location. Use this form to trigger approval workflows and tasks like account creation and team notifications.
Focus on creating automations like these for just one role or department at first. Then, once teams see how much faster and smoother the process becomes, you’ll likely get more buy-in and new ideas for implementation.
2. Breaking down data silos to improve forecast accuracy
Finance teams are swimming in data, but much of it is stuck in disconnected systems. Sales metrics live in your customer relationship management (CRM) platform. Financials are buried in your enterprise resource planning (ERP) platform and financial planning tools. Operational data is scattered across several different departmental tools.
When it’s time to forecast, teams often spend more time compiling spreadsheets than analyzing trends or shaping strategy.
“The connectivity between data sources and the quality of that data is always a challenge,” says Chao. “There’s a real opportunity here, depending on your process automation maturity, to drive insights through AI.”
AI shines when connecting the dots across systems. For example, when you use AI to connect sales pipeline data with historical collection patterns and seasonal trends, you get far more accurate revenue forecasts. AI can even help identify leading indicators of churn — like a sudden drop in customer engagement — giving business leaders time to intervene.
This isn’t about replacing judgment with algorithms. Rather, it’s about empowering finance professionals with better, faster insights, so they can make confident business decisions.
How to get started
Identify where your data lives. What systems feed into your main reports? Where do employees have to stitch information together manually?
Choose one high-impact area where data integration could move the needle. For many teams, month-end close is a great place to start: It’s time-sensitive, cross-functional, and often plagued by extra manual work.
From there, build simple connections between systems and automate routine reporting with a tool like Nintex. Once that’s working smoothly, you can layer in AI-powered analytics to boost your forecasting models and surface new insights.
3. Empowering finance teams with smarter resource allocation
When it comes to optimizing internal resources — especially technology — finance teams can feel like they’re cycling uphill.
“Finance teams often have to fight for resources and tend to rely on IT — particularly business applications or infrastructure teams,” Chao explains. “These aren’t your typical research and development (R&D) engineers: They’re engineers embedded in business systems who can unlock real value for leaders across the business.”
AI, automation, and low-code, no-code tools like Nintex can change this dynamic. With the right platform, finance teams can build their own solutions to automate reporting, manage workflows, or flag issues in real time. This means less time waiting on development cycles and more time driving business results.
But success depends on having the right foundation. “No-code and low-code tools are only exciting when they’re built on a solid foundation and supported by IT,” Chao says. Without IT’s guidance, your automations can create unnecessary risk or crumble altogether.
By collaborating to establish governance frameworks and approved platforms, both teams win. Finance gains autonomy over routine processes, while IT maintains oversight of enterprise architecture and security standards.
How to get started
Identify pain points where finance heavily depends on IT support or manual processes. Report generation, budget approvals, and compliance documentation are a few common ones.
Engage IT early to establish a joint framework. Define which low-code tools to approve, who owns governance, and how to scale solutions that work across the organization.
Then, pick one high-value task to pilot, such as automating recurring reports. Aim to demonstrate quick wins while building collaborative relationships that will make future initiatives successful.
4. Using AI to drive scalable growth
Finance leaders feel increasing pressure to increase output without proportionally increasing cost. While most CFOs can see the clear value AI and automation offer across process-heavy functions, many get stuck translating that vision into action.
Still, CFOs are well-positioned to lead the charge.
“The effort to scale and create operating leverage shouldn’t be limited to finance,” says Chao. “It’s something CFOs can champion by helping other leaders understand how AI can drive scale.”
This positions the CFO as a strategic and operational leader who guides other departments toward scalable, efficient workflows — whether it’s helping sales automate pipeline reporting or assisting HR with streamlined onboarding.
Leading by example also means preparing the organization for what’s next. As businesses expand into new markets, AI and automation tools absorb complexity without requiring increases in headcount. This becomes especially critical during rapid growth, mergers and acquisitions, or hiring freezes.
Finance teams that invest in automation early and often can maintain accuracy, compliance, and speed without adding resources.
How to get started
Look for high-volume, repetitive processes where scale is currently an issue — or soon will be. Invoice approvals, budget tracking, and compliance documentation are often good candidates.
Home in on patterns in your current operations. Where does headcount scale faster than output? Which workflows create bottlenecks as volume increases? Prioritize areas where automation could offer immediate relief without major disruption.
Automate where it matters most
To succeed with AI and automation, don’t try to transform everything overnight. Instead, start with your biggest pain points — the processes that consume too much time, create too many errors, or struggle to keep up with business growth — and grow your efforts from there.
From onboarding to forecasting to compliance, even small wins can drive big impact.
Remember: Automation doesn’t have to be perfect to offer value in your finance workflows. Instead, aim for meaningful progress that frees your team to spend more of its time on strategy instead of busy work.
Whether you’re just getting started or scaling existing efforts, Nintex can help. See what’s possible — request a demo.