Finance has always been close to the data. What is changing is its ability to listen to it. As AI moves from automation to intelligence, the Finance function has an opportunity to move beyond hindsight—using data to surface patterns, challenge assumptions, anticipate risks and shape better decisions.
In an exclusive conversation with The Mainstream, Mr. Sambasivan G, Chief Financial Officer at Tata Play, explores what this shift means for the modern Finance function, from building the right data foundations and scaling AI to balancing technology with human judgment, governance and the capabilities needed for the next era of Finance.
1.The role of the CFO has evolved significantly over the past few years. How has AI influenced the way you approach strategic decision-making, financial planning and enterprise leadership?
The role of the CFO has undergone a profound transformation over the past decade. Traditionally, CFOs were expected to be custodians of financial performance, stewards of capital allocation, and guardians of governance. Experience often compensated for uncertainty. A seasoned CFO knew how markets behaved, how competitors reacted, and how the organisation’s business model responded to external changes. However, in today’s VUCA (Volatile, Uncertain, Complex and Ambiguous) world, experience alone is no longer enough.
The modern CFO is required to make decisions on investments, resource allocation, people, technology, customer behaviour, competition, regulations, cybersecurity, supply chains, and geopolitical developments. The sheer volume of information available today is beyond human capacity to process and analyse manually. Consequently, if there is one capability that can significantly improve the quality of decision-making, it is data. More importantly, it is the ability to convert data into insights, foresight, and action.
This is where Artificial Intelligence becomes indispensable.
I often describe AI in a very simple manner: AI is nothing but “Listening to Data.” Data has always existed within organizations, but AI enables us to hear what the data is trying to tell us. It helps identify patterns, detect anomalies, predict outcomes, and challenge assumptions. For a CFO whose decisions must be grounded in facts rather than intuition, AI is rapidly becoming an essential companion.
This does not imply that every decision must be made by AI. Human judgment remains irreplaceable. Strategy, leadership, ethics, culture, and stakeholder management continue to require human wisdom. The real value emerges when human judgment combines with AI-powered insights. In that sense, AI is not replacing CFOs; it is amplifying their ability to make better decisions.
Historically, CFOs made decisions based on a relatively limited set of variables, such as revenue growth, margins, capital investment, and operating costs. Today, however, a CFO must understand customer sentiment on social media, the impact of global conflicts on supply chains, emerging regulations across multiple geographies, cybersecurity threats, technology disruptions, and changing consumer behavior. AI tools allow finance teams to process and interpret these vast datasets and convert them into actionable intelligence.
More importantly, AI helps avoid bad decisions. Traditionally, Finance was expected to provide hindsight through reports and dashboards. AI enables Finance to provide foresight by flagging risks early, challenging assumptions, simulating multiple scenarios, and highlighting unseen trends. In many ways, AI acts as both an accelerator of decisions and a mitigator of risk.
2. Every organisation is at a different stage of its AI journey. From your experience, where has AI delivered the most meaningful impact within the finance function and how do you measure its success?
I look at Finance AI maturity as a journey through four distinct stages.
While AI has become the latest buzzword, organizations often underestimate the groundwork required before realizing its full potential. AI is not a magic wand. It is a journey that requires discipline, patience, and sustained investment.
Stage 1: Single Version of Truth
Every Finance transformation must begin with a common understanding of data.
Before organizations can automate or deploy AI, they must first establish a centralized and trusted data repository. There has to be agreement on what constitutes the correct source of information. Much like no process can be automated without documentation, no data can be meaningfully analysed until its source, ownership, and authenticity are established.
For many organizations, this foundational stage consumes the majority of the effort but ultimately determines the success of all future AI initiatives.
Stage 2: Automation
The second stage involves digitizing and automating core processes.
ERP systems, treasury platforms, payroll engines, tax compliance tools, procurement solutions, workflow systems, and basic analytics become the building blocks. At this stage, organizations begin introducing robotic process automation (RPA) and reducing manual effort.
A common mistake many organizations make is attempting AI before achieving automation maturity. AI cannot be layered effectively on fragmented, manual processes.
Stage 3: AI Use Cases
Only after strong data foundations and automation capabilities exist can organizations begin scaling AI.
Typical Finance use cases include:
- Revenue forecasting and demand prediction
- Automated reconciliations
- Exception reporting
- Vendor negotiations through AI agents
- Procurement and P2P optimization
- Financial planning and scenario modeling
- Intelligent chatbots
- Fraud detection and risk monitoring
- Data visualization and storytelling
The objective remains simple: move human effort away from repetitive tasks toward value-added activities such as analysis, decision-making, problem-solving, and business partnering.
At this stage, governance becomes critical. Controls such as Continuous Control Monitoring (CCM), Automated Vulnerability Checks (AVC), and periodic model reviews become necessary to ensure AI remains trustworthy and compliant. Ultimately, I believe the success of AI in Finance should not be measured by the number of AI tools deployed. It should be measured by the quality and speed of decisions, the efficiency gained, the reduction in risk and the amount of Finance capacity that can be redirected towards strategic value creation.
That is when AI moves from being a technology initiative to becoming a genuine transformation of the Finance function.
3. Technology investments today are expected to deliver measurable business outcomes. How has your approach to evaluating and procuring technology evolved as a CFO?
A common perception about CFOs is that every decision revolves around traditional financial metrics such as ROI, ROCE, IRR, or Payback Period. While these measures remain relevant, evaluating emerging technologies purely through historical-financial lenses can sometimes be limiting. Many breakthrough technologies have no precedent. Their eventual impact cannot always be estimated using historical data because the future they create is fundamentally different from the past.
Therefore, technology investments today often require what I call a LoF (Leap of Faith) approach. This does not mean abandoning financial discipline. Rather, it means combining financial rigor with strategic conviction.
When evaluating technology investments, CFOs must consider:
- Cultural fit
- Scalability potential
- Vendor adaptability
- Integration capabilities
- Long-term strategic alignment
- Data readiness
- Change management implications
Rather than committing heavily to a single technology platform too early, organisations should experiment broadly, learn quickly, and scale selectively. In a rapidly changing technology landscape, optionality can sometimes be more valuable than certainty.
4. Cybersecurity has become a boardroom priority and a business risk. From a CFO’s perspective, how do you evaluate cybersecurity investments and their contribution to enterprise resilience?
From a CFO’s perspective, cybersecurity has evolved from an IT responsibility into a core business risk.
In the industrial era, physical assets defined enterprise value. Today, trust, data, and digital identities have become equally important assets. When customer identities are compromised, the consequences extend well beyond technology failures. They can lead to financial losses, regulatory penalties, reputational damage, and long-term erosion of customer confidence.
I often compare cybersecurity to insurance.
No organisation purchases insurance expecting a return on investment. The purpose is resilience and protection from unlikely but potentially catastrophic events.
Cybersecurity should be viewed similarly. The objective is not merely to prevent attacks but to ensure that the organisation can continue operating and recover rapidly when incidents occur.
When evaluating cybersecurity investments, I focus on whether they:
- Protect customer trust
- Strengthen fraud prevention
- Improve resilience
- Protect critical data
- Enhance regulatory compliance
- Improve recovery capabilities
Many of the most significant cyber incidents globally have resulted not from sophisticated hacking but from weak identity controls, poor governance, excessive access privileges, and vulnerabilities within partner ecosystems.
Cybersecurity is therefore as much about governance, culture, and processes as it is about technology. Ultimately, cybersecurity is about protecting trust, and trust remains one of the most valuable assets on any organisation’s balance sheet, even if it never explicitly appears there.
5. The relationship between the CFO, CIO and CISO has become increasingly strategic. How has this collaboration evolved, and why is it more important than ever?
One of the biggest organisational challenges today is the gap between business teams and technology teams. Often, business functions struggle to understand technology possibilities, while technology teams struggle to articulate business value. The result is lost opportunities and delayed transformation.
This is where the partnership between the CFO, CIO and CISO becomes crucial.
I often look at their roles through three lenses –
- CIO: Drives innovation and technology transformation.
- CISO: Protects the organisation and builds resilience.
- CFO: Ensures value creation, governance, and prioritization.
The CFO is uniquely positioned to translate technological capabilities into business outcomes and vice versa.
Similarly, the CFO can help business teams appreciate that governance and cybersecurity are not obstacles to growth but guardrails that enable sustainable growth.
Many successful enterprises today are discovering that Enterprise AI initiatives are sometimes better sponsored by the CFO’s office, while the CIO’s office may best drive Finance Digitization programs. The key objective is not ownership but collaboration.
6. As organisations scale AI adoption, governance and trust have become critical considerations. What role do you believe finance should play in ensuring responsible AI adoption, effective governance and sustainable value creation?
As AI adoption accelerates, governance becomes increasingly important.
Organisations often focus heavily on what AI can do while spending insufficient time understanding how it should be governed.
The CFO has a critical role in ensuring
- Data quality
- Transparency of models
- Accountability of decisions
- Ethical deployment
- Regulatory compliance
- Continuous monitoring of outcomes
Responsible AI requires balancing innovation with control. Just as financial controls evolved over decades to protect shareholders, AI governance frameworks must evolve to protect customers, employees and organisations.
7. Looking ahead, what do you believe will distinguish the finance organisations that thrive over the next five years?
Looking ahead, I believe Finance organisations that succeed will distinguish themselves through three strategic priorities, which is –
- Automate More – Use technology to eliminate repetitive work and increase productivity.
- Outsource More – Leverage specialist partners for scale and efficiency while retaining strategic capabilities internally.
- Multiskill More – Develop teams that combine finance expertise with technology, analytics, communication, and leadership skills.
Of these three, the most important is arguably the third.
Technology can be purchased. Talent must be developed. At Tata Play, we strongly believe in building a culture of continuous learning and have actively invested in AI literacy, cross-functional exposure, learning platforms, mentoring, and experimentation.
I often summarise capability development through a simple framework called the 3M Model:
- Meditate – Think deeper, challenge assumptions, learn continuously, and develop foresight.
- Mediate – Communicate effectively, build trust, influence stakeholders, and create alignment.
- Motivate – Develop people, nurture talent, and create future leaders.
Future finance professionals will not be remembered for producing reports. They will be valued for interpreting insights, anticipating risks, influencing decisions, and enabling business outcomes.
8. From AI capabilities and digital talent to operating models and leadership priorities, what should today’s finance leaders focus on to build a future-ready finance function?
The finance organisation of tomorrow will look very different from today’s pyramid structures.
Routine work will increasingly be automated or outsourced. Managers will spend less time supervising transactions and more time orchestrating projects, solving problems, and driving transformation.
In the longer term, finance teams may resemble consulting organizations more than traditional departments. Talent will be assembled dynamically around projects, opportunities, and challenges. Team members will simultaneously contribute to multiple initiatives beyond their functional domains.
Success in such an environment will require agility, collaboration, learning, and adaptability.
Ultimately, while AI will transform Finance, the future will not be defined by technology alone. The organizations that thrive will be those that successfully combine human judgment, technological capability, strong governance, and continuous learning.
In my view, the Finance function has always been the custodian of enterprise value. In the AI era, it is increasingly becoming the custodian of enterprise intelligence. And that is why I firmly believe that AI is the friend of the CFO.
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