Artificial intelligence tools lead efficiency and strategic gains – and mainly reshaping professionals in the field of financing.
Artificial intelligence is a revolution in companies financing, enhancing efficiency, prediction and decision -making. With adoption, the financial manager is imagined to expand their role from cost rulers to long -term value drivers because they integrate artificial intelligence in both strategy and operations.
While the benefits are attractive – from improved monetary flow to fraud – cultural transformations, data challenges, and organizational pressures are considered. With the evolution of governance practices and team capabilities rapidly, financing professionals will have to adapt quickly in an environment in which the strategic use of technology that artificial intelligence drives is essential discrimination.
The annual Primrectionue report of the annual director of the financial manager notes that the booming companies in the volatile markets today are those that rethink how capital flow through their operations. Artificial intelligence leads this transformation, which transforms business payments into business by detecting fraud, predictive analyzes, and dynamic dispute.
“It is not a matter of replacing human rule but rather its extension. You must be centered around man.”
Rafael SavalThe former financial manager at WELEDA
At least, companies that use artificial intelligence in the auditing accounts, at least, have $ 3 million in investment (ROI) over a period of five years of improving prediction and the prevention of stronger fraud, according to the report. In retail trade, it gives 60 % of the priority of digital transformation while logistical services-for global trade-adopt artificial intelligence and automation to reduce cash flow pressure, enhance efficiency, and increase the vision of the supply chain through early payment and predictive tools.
However, the fact that artificial intelligence is implemented through the financing function reveals complex operational and cultural challenges. The French network of the General Manager and Al -Wehdat, from artificial intelligence today, which can be frightening for financial specialists.
He says: “As the financial manager, the priority is to understand the material behind the noise,” he says. “In practice, most financial managers are skeptical – especially from Genai and Agentic Ai. Amnesty International is reliable on a broader scale, mainly because it is not deformed. This form of artificial intelligence is already proven useful in detection of fraud, banking reconciliation, and smart critical publishing.”
Pockets of innovation
Alexandros Kulvras, president of the treasury association (HAT) and Vice -President of the European Association of the European Fund, says that the concrete value is increasingly outperforming the skeptics, especially when it comes to predicting cash flow. “In the Americas and Europe, the models driven by artificial intelligence adapt in an actual time based on internal inputs and the total economy, which proves useful for planning for liquidity,” he said.
Amnesty International in classifying transactions and detection of anomalies is another innovation that helps the financing teams to identify the risks early. In some American banks, Copilots is tested from artificial intelligence to help the treasury teams during liquidity stress tests, setting scenarios as needed and effectively included innovation in decision -making.
“These tools not only replace manual work, but also change how professionals interact with data,” says Colvis.
In the United States and Europe, Copilots integrate Amnesty International into their treasury management systems, where they advise optimal financing or investment decisions based on actual time data. In Greece, members of Hat are impatiently adopted with best practices, as some companies experience machine learning to improve payment and discovering fraud patterns.
Whether it is driven by strategic insight or the need to remain at the forefront of the technological curve, the efforts made to include artificial intelligence in financing are accelerating worldwide.
Raphael Savalle, the former financial manager for the manufacture of WELEDA cosmetics, made Amnesty International a strategic priority in the Swiss International Company. “It comes to competitive survival,” he says. “Everyone should adapt; individuals, companies, and the entire profession. People also want to work in companies that adopt the latest technology. You must get a technology train.”
After offering GPT at home for use at the company level, Savalle Brainstymed uses were deeper for the tool with the head of data and digitization on the company. He also launched the stock management initiative.
“For those types of applications, you need two to three years of data,” he says. “The more the granular, the better,” he says.
Genai has transferred the company’s monthly financial reports on more than 20 countries, which cover profits, loss, dues, and budgets. Saval says that what took days now took seconds, achieving 80 % to 90 % of used production in 10 seconds. Next: Including artificial intelligence deeper into the ERP resources planning for predictive analyzes, stockpiles and limited deadline managing behind the scenes.
But while innovation gets the main headlines, it warns, it is important not to neglect the current systems. “You need to change the wheels of the car while driving!” He says. “WELEDA 23 ERP (platforms) today, you cannot realistically aim to apply artificial intelligence across everything once. First, you need to get the foundation correctly. Then you can build new and innovative solutions at the foreground – but at the same time. Only then you can harvest benefits from this new basis.”
Integration challenges
The infrastructure is widely considered one of the largest obstacles that artificial intelligence has received, especially in large organizations where operations extend to multiple departments – participation, logistical services, financing and multiple old systems. Some ERP and Procurement platforms will be valid for decades, and they are often filled with badly and badly, but they are specific to business.
For evangelical, the challenge lies in building bridges between these new systems and technologies.
“This is a dangerous concern not only for companies but also for banks, many of which still work on systems like SAP,” warns. “Integration is much easier for startups that are not ancient infrastructure.”
Colavras says the financing function is a critical turning point in this regard.
“From a technological point of view, the leaders of the financial manager and the leaders of the financial transformation must think normally,” he says. “Instead of great reform, homogeneous reform, the future lies in an integrated structure: to connect artificial intelligence to current systems by ways to provide a fast and flexible investment for expansion.”
Malians also realize that artificial intelligence does not result in a direct investment return; Instead, the real value of long -term gains lies in productivity, participation and the use of the most intelligent resources. Managers (Al -Mazhar) are the budget of Amnesty International with a wider lens, with a lesser focus on fast returns and more on sustainable efficiency and empowerment.
Change the culture of financing
Meanwhile, the role of the financing function is transferred as the roles of automation and reshaping of artificial intelligence, especially for accountants and managers of the average level. Driving increasingly requires a proactive approach to innovation and a profound understanding of how financial technology is reshaped.
“We rethink how we interact with banks, clients and suppliers – everything is evolving, and this type of transformation requires the ability to adapt: not only in the process but in the mentality and leadership,” says Anjili.
Mixed roles such as translators of financial data, digital control units, and treasury analyzes are emerging, and financial experience with scientific knowledge of artificial intelligence and data science. More importantly, the emergence of these new roles is to create wage differences in some companies, where financing managers earn less than some data engineers, which raises driving challenges for financial managers.
Malians must build literacy in data science, support data safety, and deepen their understanding of artificial intelligence algorithms. Close cooperation with data and information technology teams is necessary, as well as a strong understanding of compliance requirements. They also need to ensure transparency in how to address artificial intelligence with sensitive customers, employee and suppliers-keeping people firmly in the decision-making center.
Despite the steps taken by many companies, the adoption of artificial intelligence continues to face resistance, especially on cautious councils of its reputation and risks. Artificial intelligence errors can spread quickly in financing, so strong controls, tracking, and human control are vital.
“It is not a matter of replacing human rule, but its extension,” Saval says. “The human axis should be to explain how you will help artificial intelligence. In any large company, there will be advocates of change and others will be less enthusiastic. It is difficult to persuade a very conservative board member that we may not be artificial, but we need more intelligence.”
