The AI Revolution is Transforming Finance Departments at Breakneck Speed. In this article, as a financial leader, CFO, or finance manager, you will receive advice on the most critical aspects to keep in mind as you navigate this new AI era.

Many AI Questions in the Air

Many tasks within finance departments are particularly well-suited for automation. This is because these tasks are often repetitive and time-consuming, involve large amounts of data, and are governed by strict and clear regulations.

Moreover, the financial leader plays a central role in supporting and ensuring responsible and data-driven business decisions within their organization. This is why AI questions about automation often find their way to this department:"

 

What are the primary opportunities and risks? What skills are needed? How do we automate responsibly, for the long term, and sustainably? Where do we begin? What and how do we do it in practice?"

 

Positive Effects of AI

The finance organizations that have already made significant progress in their AI journeys tend to highlight several different points where the positive impact of automation is particularly clear:

Freed-up time and capacity...

...for more value-added work, such as strategy, development, collaboration, training, discussions, support, and analysis.

For example, Svea Bank has been able to create space for its employees to focus more on customer service instead of payments, invoicing, and reminders. Read more about Svea here.

Higher quality...

...in financial data as well as more accurate forecasting and data-driven business decisions.

SEB, one of the largest banks in Sweden, is often highlighted in industry media for its investments in AI to improve its financial forecasts and risk management.

By using advanced algorithms, they can make more accurate forecasts and optimize capital allocation.

Increased security and improved risk management...

...for example, by more easily detecting and preventing fraud, cyberattacks, and credit risks.

Klarna, which proactively uses AI to increase user security by analyzing transaction data and behavioral patterns, is often mentioned in this context.

Better compliance...

...through ongoing control and adaptation where AI is used to ensure compliance with policies, regulations, and laws.

Increased productivity and profitability...

...for example, through faster payments, optimized pricing strategies, more accurate resource allocation, and maximized cost efficiency.

Happier customers and employees

... who receive support and time for tasks they find more rewarding.

Automating finance departments: What specific processes and tasks can be automated?

One of the primary strengths of AI is its capacity to handle and identify patterns in large volumes of data. It often involves automating various processes and tasks that include data entry, reading, loading, interpretation, analysis, and forwarding of large volumes of data between multiple systems.

Here is a list of common examples that are often automated:

• Budgeting
• Forecasting
• Reporting
• Income Statements
• Balance Sheets
• Cash Flow Analysis
• Revenue
• Expenses
• Approval Processes
• Invoices
• Reminders
• Currency Exchange
• Taxation
• Credit Checks
• Costs
• Liabilities
• Invoicing
• Accounting
• Customer and Supplier Ledgers
• Currency Management
• Compliance, including adherence to various laws, regulations, and policies.
• Employee Benefits Programs, such as pension plans and health benefits.
• Email, including receiving, interpreting, and composing.
• Inventory Optimization, including changes, inventory counts, and shrinkage.
• Orders
• Customer Support Chat
• Coding
• Expenses
• Transactions
• Travel Expenses
• Documents
• Archives
• Contracts
• Evaluations and Recommendations, such as portfolio adjustments, insurance solutions, taxes, investments, and profitability.
  These tasks can be automated to enhance efficiency and accuracy within finance departments.

When implementing AI automation in finance, there are several risks and challenges to consider:

Certainly, significant and rapid change always brings risks, concerns, and challenges.

Some of the common concerns often addressed include job displacement, security, and sustainability.

Jobs

The dominant question in both societal debates and many organizations is how AI will impact jobs. Will they be replaced by AI - and if so, which ones?

The fact that the working environment and job roles are constantly evolving - as is the case with the AI transition - is a reality that all businesses need to adapt to. However, studies and future projections, including a recent UN study, suggest that most job roles will generally be complemented and strengthened by AI and automation, rather than replaced.

Human expertise will always be needed to ask the right questions, monitor, and understand the implications of the answers. Just as with other technological shifts, new jobs have emerged as others have disappeared. As IBM has put it in a study:

 

“AI won’t replace people—but people who use AI will replace people who don’t.”

 

A central prerequisite here is that companies, politicians, and even employees themselves take responsibility and maintain initiative. Business leaders need to genuinely understand what the shift entails and actively steer the development in their organization responsibly and transparently.

Policymakers need to keep pace and adapt laws and regulations continuously, while individual individuals and employees need to take responsibility for adapting through ongoing education.

Last but not least, the employees in the organizations affected must have the opportunity to participate early in the change. Full transparency and ongoing communication with an invitation to participate are key factors in reducing internal resistance and thus achieving maximum efficiency.

Data Security

Data security is a particularly important issue in the field of finance, where financial data and even personal information must be protected. Once again, it is important to maintain control and use AI tools within your own systems and environments as much as possible.

However, AI itself does not pose any security risks because the tools are programmed to do what humans instruct them to do. Data security must always be a priority - but not specifically because we are using AI technology.

Correct Data

Even though you often hear that AI "cannot make mistakes," you can never blindly trust that AI provides 100 percent accurate information. AI can only make the best of the available data and the instructions given. Once again, humans will need to retain control over the work.

Sustainability, ethics, and competence

Many also wonder how to implement AI sustainably, ethically, and long-term, and what internal skills are needed. How do you avoid locking yourself into tools, ERPs, and other business systems where most things are continuously replaced with more and more automated functions?

Or, as a company, if you choose to build something yourself where something entirely different may apply in a year, and it doesn't really belong to the core business? And perhaps worst of all: What if some group or individual unintentionally risks being violated or discriminated against?

Here, it is again crucial to take control and ensure that AI adapts to the unique needs and workflows of the organization - rather than the other way around.

To achieve this, it's good to find an AI partner with a holistic perspective and continuously updated and developed expertise across the entire field. It's also an advantage if the provider is not dependent on a specific technology or programming technique but can adapt the solution to what the unique business needs.

Choose a Long-term AI Partner with a Holistic Perspective

When choosing an AI partner, it should be clear what the provider offers upfront, what it will cost, and what is included. And perhaps most importantly, choose an AI provider that understands their mission:

AI and automation are about business development - more than automation, coding, and technical competence.

Do you want to know more and get advice on how you can be part of shaping the future - instead of being controlled by it: Contact Zimply.

In summary

1. AI is revolutionizing finance departments, creating opportunities for CFOs, financial managers, and their teams to engage in more value-added work, accurate forecasting, data-driven decisions, improved security and risk management, better compliance, increased productivity, and profitability.
2. Examples of various processes that can be automated include budgets, forecasts, reports, income statements, balance sheets, cash flow analyses, taxes, costs, and more.
3. Commonly addressed risks in automation include job displacement, data security, and ensuring the accuracy of information.
4. To succeed in transitioning to an AI-driven workflow, responsible initiatives are required from company leaders to retain control over the development of the organization.
5. Choosing a long-term AI partner with a holistic perspective is crucial for success.

 

PSST! Save the date!

25 oktober kl 14.00 sänder Zimply med gäster ett livewebbinarium riktad till CFOer och ekonomichefer för att djupdyka ytterligare i ämnet samt för att svara på frågor kring AI och ekonomifunktioner.

If you can't wait, you can already listen and watch Zimply's Chief Commercial Officer, Sebastian André, who participated in Svea Talks on September 21st to discuss how businesses can prepare for the AI boom.