GenAI Is Redefining Business Paradigms, But Will The Scale Of Change Gobble Up ROI?

With each passing day, artificial intelligence, especially generative AI (GenAI), is driving monumental changes across industries and businesses, emerging as a strategic enabler and turning traditional business models on their heads. At the centre of our ongoing reckoning with GenAI are critical questions like what GenAI can do, its practical applications and how businesses should use those when adopting this transformative technology. To dive deeper into the GenAI territory and explore relevant answers, Inc42 and Google Cloud organised a roundtable titled GenAI Is Redefining Business Paradigms, But Will The Scale Of Change Gobble Up ROI?

The session covered many critical areas, including:

• Practical applications of GenAI
• GenAI as an enabler for products and services
• The ROI challenges associated with GenAI adoption

Moderated by Sameer Dhanrajani, CEO at AIQRATE & 3AI, the session brought together startup leaders from various sectors such as ecommerce, deeptech, agritech, fintech and more. 

Among the key participants were Pranjal Singh, data scientist at Udaan; Yash Dayal, CTO of Wakefit; Exotel’s vice-president of engineering, Abhinandan Kedlaya; Kumar Rajamani, associate director at Cropin; Manas Agarwal, vice-president of engineering at Hasura; Vaibhav Magon, senior director (engineering) at CheQ; Sarath Chandra Kummamuru, senior vice-president (engineering) at Razorpay; Vikas Jethnani, vice-president (engineering) at BetterPlace; Krithika Muthukrishnan, chief data science officer at Scripbox; KarmaLifeAI cofounder Naveen Budda; Syed Mohd Bilal, senior director (machine learning) and head of data intelligence at Perfios; BeepKart CTO Nikhil Vaidya and Google Cloud’s head of customer engineering, Debasis Bhattacharya.

For Whom Generative AI Crafts Solutions & How Well It Is Aligned

During an hour-long discussion, Sarath Chandra Kummamuru of Razorpay came up with a much-needed perspective – how he viewed the evolution of AI/ML and how well GenAI would align with technology-driven business environments. 

“As a top company in the digital payments space, we have already mastered AI-ML to a large extent to run day-to-day operations and protect data. Now, we are taking our ops a notch higher with the help of GenAI for fast and better decision-making and better outputs. At this point, we are looking at GenAI to empower internal operators [developers] and external operations agents. Eventually, it will help all stakeholders, including merchants, mid-market companies and enterprises,” he said.

A hardcore value assessment is due now that the initial hype around GenAI is gradually dying. Therefore, business leaders and decision-makers are doing just that, trying to track the real benefits and the gobs of money the technology can bring in.

“One of our products is a learning management system (LMS) that has moved from content generation at scale to adaptive training,” said Vikas Jethnani of BetterPlace, an HRtech SaaS platform. “For instance, we create real-time, targeted content for Zomato and Swiggy employees, as their performances must improve without undergoing long training sessions. This personalised approach can be a game-changer.”

Funding GenAI Has ROI Challenges: Can New-Age Businesses Cope?

A close look at the GenAI potential reveals three core domains with significant impact: Reshaping customer experiences, innovation in product and service development and transformation of operational workflows. 

Business leaders have little doubt about the value of GenAI applications. However, gaining a solid return on investment (ROI) is still a far cry for two reasons. First, generative AI is still a work in progress, and second, huge capital is needed to implement and run GenAI initiatives.

“In the current situation, a CTO is likely to go for a two-pronged approach,” said Yash Dayal of Wakefit. “One is you can look at some low-hanging fruits where you can quickly see improvements in business metrics and try to do a couple of those use cases. But there’s always some investment alignment you need to do to build that particular tech capability. The moment you go down the path and try to fine-tune a large language model (LLM), you will suddenly see that your tech costs are spiking. So, a strategic investment plan is crucial to manage these costs effectively.”

Abhinandan Kedlaya from Exotel explained how well-defined business metrics and existing frameworks could help decide whether to invest in GenAI capabilities and drive growth.

“Contact centres have well-established metrics for gauging performances and calculating ROIs. GenAI tools like chatbots and WizeBot can also improve efficiency. As most companies have some budget allocation for GenAI, it is easy to make an initial investment and assess its impact. Based on the outcome, a decision can be made,” said Kedlaya. 

Debasis Bhattacharya of Google Cloud also thought companies need to balance costs and benefits.

“In Bengaluru and elsewhere, digital native companies are spending between $1K and $30K a month on GenAI solutions, especially API calls. Some use ready-made APIs, while firms with five to 10 engineers find it cost-effective to fine-tune GenAI models for their data pipelines. However, there is a growing awareness regarding ROI, prompting businesses to reduce costs.”

According to Syed Mohd Bilal of Perfios, aspirations for GenAI adoption will remain high for yet another reason.

“It is widening the scope of work and boosting capabilities. Just type into a ChatGPT interface, sit with an engineer and go through the entire process once. Any product manager can develop a proof of concept (POC) independently in that way. You don’t need a tech person to do that, at least not in the initial phase. So, that entry barrier to trying things has truly been democratised.”

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