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How to Use AI in Corporate Finance: A full guide
AI is quickly becoming part of everyday life in corporate finance. It’s no longer a futuristic concept, but a present-day tool which can “provide outputs that can be extremely accurate, replacing and, in some cases, far superseding human efforts”, say the ICAEW, who also stress the crucial importance of human intelligence (HI) and input too.
When used cautiously and correctly, there’s no doubt that AI can be transformative for jobs and workflows. From speeding up routine tasks to unlocking deeper insights, it’s helping finance teams move faster and make more confident decisions.
Agentic AI systems like QuickBooks’ Accounting Agent demonstrate this in practice — delivering efficiency 24/7 by learning the ins and outs of your business, helping you to save time, make smart decisions, and grow.
In 2025, a report from McKinsey showed the growth of AI tools in corporate finance departments. In their survey of 102 global CFOs, almost half of respondents said they used generative AI for at least five separate use cases that year — up 7% from the year before. What’s more, almost two thirds or respondents said they would be investing further in AI that same year, rising from 25% just two years ago, showing a strong rate of adoption. Following that, Bank of England research also found that 75% of financial services firms were using AI as early as late 2024 — projected to rise by 10% in 25, 26, and 27.
Generative AI is just the beginning. With a new era of automated, agentic decision-making on the horizon, AI could yield greater efficiencies, innovations and insights than ever, if used correctly.
In this guide, we’ll talk about how.
AI in corporate finance – in summary
AI helps automate time-consuming processes like reporting, reconciliation and compliance, freeing up valuable time for other business areas
It enables more accurate forecasting and scenario planning, using real-time data and advanced analytics that support business growth
AI supports a shift from reactive reporting to proactive, boosting strategic decision-making and helping inform sound financial choices
What is AI in corporate finance?
In corporate finance, AI (artificial intelligence) encompasses a range of technologies and purposes — including machine learning (ML), natural language processing (NLP), generative AI and agentic AI.
These powerful tools can be applied and plugged into financial software and processes to automate tasks, analyse rafts of data, predict trends, and produce exceptional results for clients at scale and pace.
How AI might be used in corporate finance
AI can produce excellent results with less human input — here are a few key functions and features that you might use it for.
Forecasting and planning
We all want to spot downturns, upticks and trends early, but sifting through the data is a time-consuming job. AI can make all the difference — processing and interpreting huge datasets and delivering accurate forecasts in real time.
Forecasting. Machine learning tools can learn from the past and present more quickly and efficiently than ever, helping predict anything from revenue to cash flow.
Scenario planning. Whether you’re riding a wave or running a risk, AI can help you predict outcomes and make safer decisions.
Monitoring. AI tools can track everyday transactions in real time, picking up movements and fluctuations before they escalate.
Risk management and fraud detection
Traditionally, risk management has relied on extensive analysis and manual review. With AI, you can monitor data, detect fraud, and assess risks in real time.
AI can monitor and analyse huge datasets to find unusual patterns and flag anomalies to spot fraudulent activity. Think crucial areas like transaction monitoring, credit risk assessment and anti-money laundering compliance.
When it comes to risk to your business — always a “hot button” issue, as Deloitte put it — machine learning and AI and ML tools make anticipating market volatility simpler than ever. This can put you on the front foot, offering a more proactive, preventative approach.
Automated reporting and compliance
Reporting and compliance can be fiddly, time-consuming jobs — but AI can help you take the pressure off.
With the right tools in place, AI can automate much of the heavy lifting with AI categorisation, explanations, and predictions that help ensure your books are accurate. Modern systems like QuickBooks Accounting Agent pull together data, generate reports, and write summaries for time-poor execs and decision makers.
With AI anomaly detection, you can identify and resolve potential discrepancies faster, saving time at month end. AI can help you monitor transactions, and can help you flag anything that might not meet regulatory requirements. That means fewer manual checks, reduced errors, and greater confidence that everything is accurate and up to date. And it’s easy (and widely recommended) to ‘bake in’ human oversight into the workflow throughout.
For finance teams, it’s not just about saving time — it’s about making reporting more reliable and less stressful.
Speed up bank feed processing and transaction categorisation
Your AI bank feed runs smoother with AI categorisation, explanations, and predictions that help ensure accuracy. QuickBooks Accounting Agent categorises transactions, continuously learning from your responses for greater accuracy. This isn’t a one-time setup — the system learns your business rules, vendor patterns, and categorisation preferences, becoming smarter with every transaction it processes.
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Investment analysis and portfolio management
Making investment decisions often comes down to how quickly and accurately you can interpret data – and that’s where AI tools can truly shine. They can analyse swathes of information — from market trends to news sentiment — and surface insights that human eyes might miss. AI can also adapt as new data comes in, helping teams stay responsive in dynamic markets.
For portfolio management, this means a better balance between risk and return, and more confident decision-making. It’s not about replacing human judgment — it’s about giving it a much stronger foundation.
Finance teams are leveraging QuickBooks AI Finance Agent, which analyses performance data and makes suggestions you might have missed — strengthening decision-making even further.
Generative AI for content and insights
Generative AI is changing how corporate finance teams communicate and share insights.
Instead of starting from scratch, you can use AI to draft reports, summarise performance, or pull together key trends from complex datasets. It can even turn unstructured information — like news or internal notes — into clear, actionable insights.
That’s especially helpful when time is tight, or when you need to explain financial information in a simple, accessible way. In short, it helps turn data into something you can use — and share — much faster.
AI agents for process automation
Agentic systems take AI a step further. Instead of just completing individual tasks on a disconnected, prompt-by-prompt basis, they can handle entire workflows autonomously.
Agentic systems like QuickBooks Accounting Agent might take the initiative to process invoices, categorise expenses, or reconcile accounts, without necessarily requiring specific input. They can even move between systems and software — bridging the gap between workflows and teams.
The result? Cohesion, consistency, and collaboration. As these tools continue to evolve, they’re set to become a core part of how finance teams operate daily.
What are the benefits of AI in corporate finance?
AI adoption is growing quickly in the corporate finance world — and the reasons for this are clear.
For finance teams, it’s about working more efficiently, making better decisions, and adding more value for clients.
Benefit | Effect |
Increased efficiency and automation | Routine tasks can be handled automatically, saving time and reducing costs. |
Enhanced accuracy and data quality | AI reduces human error and improves the reliability of financial data. |
Deeper insights and predictive analytics | Better data analysis leads to more informed decisions and stronger forecasts. |
Improved risk management | AI helps identify issues earlier, so they can be addressed before they escalate. |
Strategic focus | With less time spent on admin, teams can focus on planning, growth, and advisory work. |
Challenges and considerations around implementing AI in corporate finance
AI has several clear and persuasive benefits, but with AI’s rate of progress, there are issues users should consider:
Data quality and availability: AI is only as good as the data behind it — clean, structured data is essential to achieve the best results.
Human input: AI can complete work efficiently, but it hallucinates regularly. Human input and oversight are crucial to ensure accuracy and compliance.
Integration with existing systems: Bringing new tools into older systems can take time and planning. AI champions and coordinators can help make this transition smoother.
Ethical considerations and bias: It’s important to use AI responsibly, especially when handling sensitive data.
Cost of implementation: There can be upfront costs, but these are often balanced by long-term efficiency gains.
Human oversight: The best AI systems work for human review — ensuring all automation passes through professional judgement before impacting your financials
How to get started with AI in corporate finance
Getting started with AI doesn’t have to be complicated. The key is to start small, focus on value, and build from there.
Here’s a simple way to approach it:
Assess your current processes: Look for areas that are time-consuming and repetitive. Data entry, reporting and research are three common areas that can be sped up with AI.
Set clear goals: Decide what success looks like — whether that’s saving time, reducing errors or improving insights.
Start with a pilot project: Test AI in one area before rolling it out more widely — this is another area where inter-team AI coordinators can really make a difference.
Invest in your data: Make sure your data is accurate, organised and easy to access.
Build AI confidence: Help your team understand and feel comfortable using new tools.
Choose the right partners: Work with providers who understand finance and offer reliable, scalable solutions.
Discover QuickBooks’ range of AI accounting agents and supercharge your processes.
AI in corporate finance FAQs
What is the primary impact of AI on business finance processes?
At its core, AI helps finance teams work smarter. It automates routine tasks, improves the way data is analysed, and makes it easier to spot trends and opportunities. That means faster processes, fewer errors, and better decision-making overall. Over time, this allows finance teams to move away from manual work and focus more on strategy and growth.
How does generative AI differ from other AI applications in corporate finance?
Most AI tools focus on analysing data or automating tasks. Generative AI goes a step further — it can create content. That includes drafting reports, summarising financial performance, or turning complex data into clear insights. It’s particularly useful when you need to communicate information quickly and clearly, without starting from scratch.
Is AI only for large corporations, or can small businesses use AI for business finance?
AI isn’t just for large enterprises anymore. Thanks to cloud-based tools, it’s becoming much more accessible for small and medium-sized businesses too. From bookkeeping to forecasting, there are now plenty of affordable options that can deliver real value without requiring a huge investment.
In many cases, smaller businesses can benefit just as much — if not more — by saving time and improving visibility over their finances.
What’s the real ROI of implementing AI agents in corporate finance?
The returns are tangible. 45% of customers save 12 hours each month on bookkeeping alone, alongside reduced errors and faster reporting. 71% feel more confident their books are accurate, freeing time for strategic work. As AI agents learn your business, efficiency and value continue to grow over time.
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