FE Connect
The adoption of artificial intelligence (AI) in business processes is slowly but surely taking place. Yet, there is hesitation to fully embrace AI in the workflow. An IBM survey reveals that 94% of CIOs use AI in line-of-business functions, with over 50% expecting widespread usage by 2025 across IT (71%), supply chain (68%), and product development (67%). However, this enthusiasm isn’t as prevalent when it comes to the finance function in organisations.
CFOs seek ROI
Chief Financial Officers and heads of finance have reservations about large-scale adoption of AI, and its more evolved form, agentic AI. At a recent roundtable discussion organised by IBM and FinancialExpress.com, CFOs said they prioritise accuracy over everything else. They are inherently cautious of new technologies like AI that, even with high rates of successful deployment in other functions, cannot guarantee 100% results in the finance function.
Hemant Kumar Jain, CFO of Reliance General Insurance, highlighted the challenge with technologies like Optical Character Recognition (OCR) in invoicing, for example, stating, “OCR is a challenge, as there is a 95-96% accuracy, but still the rest has to be manually checked.”
This sentiment was echoed by Amit Malpani, CFO of Edelweiss Asset Management, who emphasised, “As a CFO, even if there is 5% inaccuracy, it is an issue.” There is a need for human validation, especially in the finance function. Siddesh Naik, Country Leader, Data & AI, Technology Sales, IBM, acknowledges this, pointing out that “Human element validation is needed. OCR accuracy needs a minimum of 300 dpi.” There is a requirement for a human-in-the-loop, which still implies an added cost and oversight that CFOs are keen to minimise. Only if this can be eliminated can AI deliver value in the finance function.
Beyond accuracy, the return on investment factor in AI remains a significant barrier. Swayam Saurabh, CFO of JSW Steel, said, “AI is used largely in back-office processes, along with robotic process automation and machine learning. It’s only a buzzword so far. It needs to reduce fixed costs, which haven’t happened so far.” This lack of proof of value resonates across the finance heads.
Kapish Jain, President and Group CFO of IIFL Finance, highlighted the core issue, saying, “The problem statement is on reconciliation – what are the costs and how can I use AI to eliminate some of these? There is not enough illustration on proof of value or ROI.” Yogish Udhoji, CFO of Muthoot Housing Finance, admitted, “At the moment, we are only looking at automation, optimising tax and invoicing. We could have changed our invoicing pattern using AI, but we haven’t figured out an AI use case.”
While some companies, such as SBI General Insurance, are using AI in areas like GST compliance, claims, and underwriting, Jitendra Attra, their CFO, confirmed that “when it comes to the core finance function, the company hasn’t implemented any AI at the moment.”
Pavan Jain, CFO of Grasim Industries Limited, sees future potential for AI in automatic updating of regulatory compliance, but widespread adoption for core finance tasks remains contingent on improved accuracy.
To truly unlock the potential of agentic AI and gain CFOs’ trust, companies need to re-evaluate and potentially redesign entire workflow systems to demonstrate not just automation, but verifiable cost reduction and enhanced value, moving beyond just a token adoption to more concrete financial gains.
For deeper insights, explore
AI boosts customer experience and aids retention
However, AI is offering significant gains when it comes to other functions like customer experience. In a competitive business landscape where solutions and services offered by companies often look similar, with limited differentiation and customers facing little friction in switching service providers, delivering a standout customer experience is a key competitive edge.
AI proves to be a game changer in providing an out-of-the-ordinary customer experience. From targeting high-intent customers to automating workflows and customising offerings, AI is steadily redefining how enterprises interact with and serve their customers.
However, harnessing AI successfully requires more than just access to advanced technology. It is about walking the fine line between convenience and privacy, efficiency and empathy, particularly in high-stakes sectors such as asset and wealth management, insurance, securities trading, etc.
We may not see it, but AI is already at work behind the scenes, driving key aspects of customer engagement in businesses. For instance, in wealth and asset management, firms use it to enhance customer interaction and research capabilities.
Insurers are also exploring the use of AI to streamline customer journeys. Girish J Kalra, CMO at Tata AIA Life Insurance, says AI is being used to “reduce cost on creative agencies for marketing-related efforts, understanding customer eligibility for the right insurance policy, issuance of policies to reduce the documentation process for customers, and also to minimise the entire insurance buying process for customers.”
However, scaling AI comes with its own set of challenges. According to Kunal Sanghavi, Chief Strategy and Transformation Officer at HDFC Securities, the challenge is that when there are multiple parties involved in an event, it becomes difficult to ensure the impact and effectiveness of AI.
Sanghavi notes that it is important to have control over various steps involved, which remains a challenge. “For example, regulations play a critical role. In short, it will be a journey to adopt the latest LLM models with the usage by large institutions and enterprises to adopt at scale.”
Personalisation is another critical driver of customer engagement and improving the overall customer experience. However, it requires careful navigation – being too aggressive risks alienating customers and being too cautious can lead to missed opportunities.
“There is a need to balance how much you can intrude into a customer’s space to offer more personalised solutions and build loyalty,” says Santoshi Kittur, CTO, 360 One. “It is about empowering people on the ground to give solutions to customers in the fastest way possible. It is also about the empathy aspect. So, experience is the key differentiator in a scenario where you have competitors doing similar things.”
The effects of AI are not only visible in customer experience but also on the bottom line. One of the measurable outcomes is the reduction in costs related to acquiring new customers and retaining existing ones. In an intensely competitive market, rightly identifying high-conversion leads can yield substantial cost savings.
Also read: AI unleashed: Transforming HR and operations for the next era of business
“Al helps in differentiating between intent and non-intent customers to focus more on the right customers with the right offering and hence, reducing costs,” says Sanghavi.
He maintains that AI also helps in measuring the ROI attached to a customer over a period of time to effectively reduce the cost of acquiring and retaining a customer. In essence, AI helps companies acquire quality customers rather than just a higher quantity.
While companies remain optimistic about AI, the path towards widespread adoption is still unfolding. Compliance with regulations, robust data governance, and ethical handling of customer information continue to be key priorities. For enterprises looking to stand out in customer experience, finding the right blend of intelligent automation and emotional intelligence may be a key advantage. For the finance function, adoption will depend on AI being able to deliver consistent accuracy.