🌊AI Revolution - is your department next?

How AI is changing work, department by department

AI, AI, AI, AI…how many times did you hear about AI and how it’s going to change the world?

Well, it got me thinking…can we be more realistic and show you what is the current state of AI solutions out there?

Because when you think about it, it’s easy to say ChatGPT will change the world but can you make a valid business out of it?

That is why we decided to go out there and find companies that are already offering AI solutions (their own or implementing 3rd party solutions) and to find out firsthand what are the challenges.

We will start our “AI tour” with the finance department, and is there a better way to dig into it than having as our guest a company that specializes in AI for finance departments? 🙌

The company name is Nanonets.

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You work in Excel…I mean finance?

When I was a student from time to time we used to have guest lecturers, and I remember one guest in particular; it was a CFO of one of the largest companies in Croatia.

Now, he was talking to us about the company and the importance of the finance department inside the company. Naturally, in the lecture, some students wanted to draw attention to themselves and they asked the question “What is the most important skill we need to have if we want to work in finance”.

The answer?

“Learn Excel well”.

Now that I’m older and have work experience, I completely understand what the CFO means. I estimate that 95% of the work done by the finance departments is based on Excel so it’s a critical skill.

How does AI come into the picture here?

Well…Excel is just a tool, but the data that comes into the tool, people are still typing in manually 👀

We asked Rohan Handa, Product Manager in Nanonets what are use cases for AI in the financial departments 👇

Automated bookkeeping and invoice processing

AI-powered algorithms can automatically extract relevant data from invoices, receipts, and financial documents. By leveraging machine learning and optical character recognition (OCR) technologies, companies can accurately capture and categorize financial data, eliminating the need for manual data entry.

Predictive analytics for financial forecasting

AI algorithms can analyze historical financial data, market trends, and external factors to generate accurate predictions and forecasts. This empowers finance professionals to make informed decisions about budgeting, cash flow management, investment opportunities, and risk mitigation.

Enhanced decision-making with AI-driven insights

By leveraging AI and ML, finance professionals can gain deeper insights into customer behavior, market trends, and financial performance. By mining historical data for patterns and insights, businesses can enable data-driven decision-making, optimize their strategies, identify growth opportunities, and mitigate risks effectively.

Personalized customer experiences

AI and natural language processing can revolutionize the way financial institutions interact with customers. Through chatbots and virtual assistants, businesses can handle several customer inquiries, provide personalized recommendations, and streamline processes such as payments, transfers, queries, and account management.

As you can see from this, current state of AI solutions in finance departments is focused on three things 👇

• automating the data coming into the tool

• utilizing the data inside the tool

• making it easy for the users

But, is everything that simple?

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What are the challenges?

While the integration of AI in the finance function brings significant benefits, it is not without its challenges. Here are some that organizations may encounter when implementing AI in their finance operations 👇

Data quality and accessibility

AI systems heavily rely on high-quality, accurate, and relevant data to deliver meaningful insights and predictions. However, many organizations face challenges in ensuring the quality and accessibility of their financial data. Issues such as operating in data silos, incomplete or inconsistent data, and security concerns can hinder the effectiveness of AI algorithms.

Lack of a skilled workforce

Implementing AI in the finance function requires a workforce with an understanding of both finance and AI technologies. However, there is a shortage of professionals who possess the necessary expertise to leverage AI effectively in finance operations. Organizations may face challenges in hiring, training, and retaining AI talent.

Change management and cultural shift

Implementing AI in the finance function often requires a significant cultural shift within the organization. Resistance to change, fear of job displacement, and lack of awareness about AI's potential benefits can pose challenges. Overcoming these challenges requires effective change management strategies, clear communication, and fostering a culture of innovation and collaboration. Engaging employees in the AI adoption process, providing training and support, and emphasizing the value of AI can help drive successful integration.

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Final thoughts

So, is AI going to change the way we work?

Yes

Will it be instant?

No

From Nanonets experience it seems that integrating AI into existing systems is by no means an easy task, and we not talking here about “ground-braking” AI that changes completely the way we work.

To assess new technologies, it’s good to go into the past and learn from it.

Remember the early days of cryptocurrencies? There were skeptics and believers, debates on its legitimacy, and concerns about its long-term viability. Fast forward to today, and it's clear that blockchain technology and cryptocurrencies have made an impact on finance and supply chain but the overall impact was not as „Crypto prophets“ told us.

Beware of “AI prophets”…