Sneha brings over decades of experience in finance, accounting, compliance, and analysis within the automotive industry. She has a proven track record of driving strategic growth, improving operational efficiency, and positioning finance as a key business partner for organizational success.
In a thought-provoking interaction with Women Entrepreneurs Review Magazine, Sneha shares her insights on the evolving role of finance leaders in navigating technological innovation, balancing digital investments, and integrating AI-driven decision-making while upholding ethical standards. Her perspectives on these critical challenges are explored in the article below.
With rapid technological innovation outpacing regulatory frameworks, how should finance leaders assess which emerging technologies to adopt, especially when the risk of obsolescence looms over digital investments?
It need to be accessed both for human and technological way, there can’t be a one-way solution. There should be a robust compliance and legal team to monitor the changes in regulations and can interpret them thoroughly; they should ensure that technological solutions align with the latest legal and regulatory standards. Your team should regularly engage with regulators to get an idea of potential change.
From the perspective of technology, focus should be on modular scalable approach so that updates can be done in parts without overhauling the entire system as per the requirements. The development should be done in Agile way so that necessary adjustments can be made.
Few essential steps to keep a check like understanding the business problem this particular technology will solve, how this new technology will drive revenue, enhance efficiency, reduce cost or mitigate risk. Means a clear business case with ROI
Second step would be to check the risk assessment framework like maturity of the technology, its viability, scalability, security and regulatory compliances.
Third would be the phased approach to adoption, Test the technology with the real world data before making the huge investment.
The last would-be flexibility and scalability, adopting a solution that allow for easier upgrades and replacements.
Additionally, finance leaders should look at the broader industry landscape, considering how competitors and partners are adopting similar technologies and whether those technologies are gaining widespread acceptance.
How do you build a case for tech investments that don’t show immediate ROI but have long-term strategic value for competitive edge?
Actually, it needs a structure approach with the in depth understanding of the business. When you invest in any digital technology then it should be a strategic fit to your organizational goals, future growth and long-term value. The benefit should explain the competitive edge in terms of speed, agility; enhance customer experience or any other depending on your business requirements. Above all AI and digital always provide/help in data driven decision making, it not only help in predicting the market trend and customer behavior but also help in financial and compliance monitoring.
So, the purpose of introducing any digital transformation shouldn’t be just adding one more software but it should demonstrate the financial benefits and long-term success by focusing on strategic alignment, competitive advantages, operational efficiencies, and the ability to innovate in a rapidly evolving market. It’s crucial to communicate how technology aligns with the company’s long-term strategy. Building a case for tech investments your ability to show a new perspective from short-term financial metrics to a broader, future-oriented view of the company’s growth and competitive advantage. The key is to frame these investments as essential enablers of future profitability, rather than as costs to be written off in the present. The challenge lies in articulating that long-term value in a way that resonates with stakeholders.
Digital transformation is not a one-time project, but an ongoing journey that requires a strategic, patient and adaptable approach.
Sometimes you have to adopt the approach of introduction in phased manner, by starting with small scale pilot that allows testing and learning, and you can demonstrate value incrementally. So, it depends on you that how you showcase the strategic role of these technologies in enhancing brand value, customer loyalty, and market positioning can make a compelling case.
As finance integrates automated decision-making tools, where do you see the balance between machine-driven insights and human intuition, particularly to navigate volatile markets or black swan events?
Machines can interpret the vast data, identify the patterns and provide actionable insight but how to apply those results especially in complex economic environments is the ability of the human. Sometimes the decision is taken based on moral and ethical values also, communication with stakeholders is equally important. The key to success is recognizing that AI and machine driven insights should complement, not replace human intuition – Especially in uncertain or volatile situations.
Digitisation or AI tools certainly excels at processing vast amounts of data and identifying patterns that might be invisible to the human eye. However, in times of unprecedented challenges or highly volatile markets, these tools often lack the nuance and contextual understanding that human intuition and experience can provide. This is where finance leaders need to strike a balance.
Machine driven insights are valuable for making data backed decisions based on available information but human intuition – fueled with experience, industry knowledge, and a sense of broader economics and geopolitical landscape – is crucial when dealing with anomalies that don’t fit historical patterns. In such situation it is important to use human ability to interpret the broader implications of the situation.
As AI becomes integral to financial operations, what responsibility do CFOs have in ensuring ethical standards are maintained in algorithm-driven decision-making processes, especially in areas like credit assessments, resource allocation, or performance evaluations?
You can’t replace human touch from the decision making, keeping the moral and ethical values is the priority of not only any CFO but for the complete organization, you can’t go away with it and think only for growth and profitability. For example, in profit maximization, AI can be employed to identify cost-saving opportunities, but decisions should be balanced with ethical considerations such as fair wages, employee welfare, and sustainable practices.
So the first and foremost responsibility of the CFO is to ensure that AI model is based on unbiased representative data. Algorithms are only as good as the data they are trained on, and if the data reflects historical biases or incomplete information, the decisions they generate can perpetuate those biases. CFOs must ensure that the data used to train these models is thoroughly vetted, cleaned, and regularly updated to avoid reinforcing biases.
Transparency is another key; CFO’s role is to ensure that the logic behind AI-driven decisions is clear and explainable. CFOs should advocate for models that not only deliver accurate results but also provide transparency into how those results are arrived at.
Moreover, CFOs should be proactive in establishing ethical frameworks and governance structures around AI use. This involves setting up clear guidelines for how AI should be used, regularly auditing AI models for fairness and compliance, and ensuring there are mechanisms in place for human oversight.
Finally the culture in the organization should be such that support the responsibility and ethics. This includes training teams to spot potential biases, encouraging open discussions about ethical concerns, and ensuring that there is a system for employees to report any discrepancies or ethical issues they may observe in AI decision-making processes.
