The role of the Chief Financial Officer is moving beyond reporting historical performance to shaping business strategy. As AI automates routine finance processes, CFOs have more time to analyse customer-level profitability, assess pricing and working capital, and help boards evaluate future opportunities. In this conversation with Tech Achieve Media (TAM), Ankit Sarawagi, Chief Financial Officer at Verloop.io, discusses how finance teams can assess returns on AI investments, why upskilling matters, and which financial metrics AI-native businesses should track as they scale.
TAM: How are data and AI turning today’s CFO into a proactive growth partner who helps shape business strategy?
Ankit Sarawagi: Traditionally, finance teams were expected to analyse historical numbers and report what had already happened. The presentation of those numbers was often left to other teams. That role has changed significantly, and businesses increasingly recognise that CFOs combine a strong understanding of numbers with a broader understanding of the business, which helps them make better decisions. AI is not the only reason for this shift; it was already underway. However, AI has accelerated it by automating routine, back-end work and freeing up time for analysis. Finance teams can now spend more time examining data and assessing what the future may look like, rather than focusing primarily on reporting the past.
TAM: AI investments can be expensive, and many pilots struggle to move beyond the experimentation stage. How can CFOs ensure these investments deliver measurable business outcomes?
Ankit Sarawagi: AI brings significant costs, including cloud-computing expenses and upfront investment. We are also seeing a change in the gross margins of AI businesses. SaaS businesses were often assessed against gross margins of around 80–85%, whereas AI businesses may operate at around 65%, with some below that level. The industry is still exploring the right benchmarks, and expectations will evolve over time. That does not mean businesses should avoid investing. If they do nothing, they risk falling behind as the technology develops. The key is to evaluate the different cost variables carefully and build projections that can be presented to the board. AI can help finance teams analyse these variables in greater detail.
Also read: Why Agentic AI Is Rewriting the Rules of SaaS Economics
The return may not always appear as a higher gross-margin percentage. It may come through revenue growth and new business opportunities. As people begin using more AI-powered tools, consumption can increase too. Even where margins are lower, the business may generate more revenue overall. CFOs need to assess the complete business case rather than relying on one percentage in isolation.
TAM: Which routine finance activities is AI helping automate, and how does that change the work finance teams can focus on?
Ankit Sarawagi: In our finance team, several back-end activities have been automated, including bank and general-ledger reconciliations, customer follow-ups, monitoring days sales outstanding (DSO), vendor payments, and the preparation of board presentations and management information system (MIS) reports.
This has helped us close the books earlier. Earlier, the monthly close could take until around the 10th of the month; now, my team can close by the 4th. That gives us additional working days to analyse the numbers. We can investigate what went wrong, discuss pricing with the team and examine profitability at the individual-customer level. Previously, the team often had little time to do that analysis before presenting the numbers to the board.
TAM: Should companies hire external AI talent or focus on upskilling their existing teams?
Ankit Sarawagi: I believe upskilling is the better starting point. Companies do not need to replace their entire teams. AI is new for everyone, and some employees will naturally take the initiative to learn and explore it sooner than others. Organisations can bring in a consultant to train existing employees or hire one or two specialists where needed. The aim should be to strengthen the current team, not replace it wholesale. At Verloop.io, AI adoption has been encouraged across the organisation for around the past year and a half, supported by training sessions. Our technology team also helps train colleagues. In my view, upskilling is the key.
TAM: What financial metrics should AI-native startups track as they grow, and which metrics are most important?
Ankit Sarawagi: Customer-level gross margin is particularly important. With many businesses exploring agentic AI, pricing each customer appropriately has become a key consideration. Companies need to understand how they price each customer and what margin they generate at that level. Traditional SaaS metrics remain relevant as well, including customer churn and net revenue retention (NRR). Tracking these alongside customer-level revenue, pricing and margins helps businesses understand whether they are growing sustainably.
TAM: What finance infrastructure should AI-native businesses build to support growth and scale?
Ankit Sarawagi: Every organisation is different. Even businesses operating in the same market can have different processes and pricing models. Customer-level metrics, revenue and NRR therefore need to be tracked in a way that reflects the specific business.I believe companies should build the relevant tracking capabilities in-house rather than expect an off-the-shelf tool to meet every requirement. An internally built mechanism gives the team greater control and makes it easier to change metrics as the business evolves. For example, if the team needs to revise its pricing metrics, it can implement the change more quickly in a system it controls. AI is also making development faster than it used to be. Building these capabilities can be valuable even before a company reaches scale.
TAM: How is automation supporting the modern CFO’s role at Verloop.io?
Ankit Sarawagi: As CFO, I now present at board meetings with a stronger focus on future numbers, rather than only reporting historical performance. I examine customer-level pricing and margins and contribute to strategic decisions, including whether the business should pursue an acquisition or acquire another entity. Automation has reduced the time spent on back-end work, allowing me to focus more on these decisions. That additional time supports better analysis and, in turn, better decision-making. CFOs are well placed to take on this role because they understand both the numbers and the business closely.
