Artificial Intelligence (AI) isn't just redefining information gathering and decision-making; it's fundamentally reshaping how companies operate and compete. While cutting-edge technologies represent an investment, corporations increasingly view them as a strategic imperative, dedicating substantial resources to their acquisition and implementation. The true competitive advantage, today and in the future, lies not in owning these technological advancements, but in the intelligence and depth with which they are applied.
The financial sector is at the epicenter of this revolution. Across the entire financial landscape, AI has taken on a leading role, transforming everything from back-office operations to complex capital market activities. In the latter, for example, models once conceived in the 1990s to draw charts and predict the future behavior of stocks, debt securities, and foreign currencies have gained unprecedented robustness. Powered by machine learning and deep learning algorithms, these models are now far more responsive and predictive, incorporating continuous learning that enables advanced real-time data analysis, including sentiment analysis and the use of alternative data.
A 2021 OECD (Organization for Economic Co-operation and Development) publication already pointed to the transition from traditional datasets to Big Data as a foundation for gaining insights into investment processes. Today, this foundation is the starting point for AI in finance to extract hidden correlations and forecast trends with previously unimaginable granularity and speed.
Meanwhile, in corporate activities, the use of AI in finance has also gained increasing traction through hyper automation, which goes far beyond simply replacing manual tasks. In addition to automating reconciliations and accounting closings, AI in finance now processes invoices, manages expenses, audits large-scale data, and automates the generation of complex reports. This not only reduces operating costs but also frees the workforce for higher-value strategic activities, converting manual time into productivity.
In operational financial planning processes, and especially in strategic planning, the applicability of AI is being directly integrated into Enterprise Performance Management (EPM) tools. Companies are using advanced predictive analytics, data science, and machine learning to empower finance professionals to be deeply data-driven. This directly impacts the business, uncovering opportunities that a human eye would not perceive and identifying hidden patterns and correlations. AI also allows for the simulation of complex and dynamic scenarios in risk environments,after 2020, for example, it has become standard to include the simulation of disruptive global events, such as pandemics or geopolitical crises, in strategic planning.
The increase in corporate profitability, driven by AI, manifests itself in various ways: from the significant reduction of back-office costs and the speed in obtaining actionable insights to the ability to simulate and optimize risk scenarios with unprecedented precision.
Scenarios, in fact, are decisive in this equation. However, I want to point out another variable of extreme relevance for achieving the desired results: customer experience, whose level of demand grows proportionally with technological advancements. A 2022 Harvard Business Review article, written by David C. Edelman and Mark Abraham have already addressed the construction of "intelligent experience mechanisms," highlighting personalization as central to corporate strategies. In this context, "competitive advantage will be based on the ability to capture, analyze, and utilize personalized customer data at scale and on how a company uses AI to understand, shape, personalize, and optimize the customer journey," culminating in the hyper-personalization of attention and financial offerings.
We therefore perceive the need for a very well-architected connection between all ends of this digital ecosystem to achieve the desired objectives. This comes with the conviction that the differentiator does not reside exactly in the available resources but, but in how they are chosen, applied, and adapted to the particularities of each corporate culture, each macroeconomic scenario, and the different consumer profiles, always based on principles of responsible and ethical AI.
Indeed, all these are pieces that must fit together to complete the great puzzle of digital transformation. No component can be forced in or incompatible with the others.
Adapting to new realities is not merely a whim of those who want to grow vertiginously or lead market segments. These adaptations, today, are more a matter of minimum survival. In a digital and globalized world where business borders have been practically extinguished, it is essential to unify methods of analysis and dissemination of company information, financial or not, and in this aspect, Artificial Intelligence transcends barriers that were once impossible, facilitating the democratization of data and interdepartmental collaboration.
Actionable insights in real time, derived from consistent and quickly obtained or constituted data, represent an invaluable competitive advantage. Companies that insist on manual, low-value-added work run serious risks of losing customers and investors, jeopardizing the perenniality of their operations.
The technology is on the table. However, I reiterate that, to make good use of them, the ingredients of strategic analysis must not be missing. This involves a lot of planning, considering thatife necessary to harmonize people and tools to extract the best possible cost benefits from investments in both technological resources and staff training and reskilling. As Kate Kellogg, a professor at MIT Sloan points out, Generative AI, for example, must be introduced in the right way so that highly qualified professionals feel engaged with the process, amplifying their productivity and creativity, not replacing them.
We are dealing with concepts that require continuous learning. As some barriers are overcome, new challenges arise and the need to develop more knowledge and courses of action. There is, therefore, a basic and primordial premise in this trajectory: the recognition that it will never be complete. It will always be necessary to reinvent oneself and demonstrate agility and resilience. It is, in short, a change of mindset, of thought and culture, both professional and organizational.
This willingness and openness to what changes constantly do not need to be engendered in state-of-the-art software. The genesis of a good plan can even be manually sketched on a piece of paper, if this plan is actually executed afterwards. And there, yes, strategically employing the available technological resources that Artificial Intelligence offers us.
At Avvale, we understand that AI in finances not just a trend, but an essential tool for survival and growth in today's financial landscape. It redefines decision-making, automates complex processes, and generates actionable insights that were previously unimaginable. We believe it's time to leave behind low-value manual tasks and embrace an era of hyperautomation and predictive analytics, consolidating the path of Sustainability and the Circular Economy in companies and industries.