The Reuters news staff had no role in the production of this content. It was created by Reuters Plus, the brand marketing studio of Reuters.
Produced by Reuters Plus for
Rarely in the course of history has a single technological advancement provoked the hope that it will be a universal gateway to future prosperity. GenAI is the next technological leap—but can its real-world impact match the hype?
Balancing AI enthusiasm with practical implementation
World leaders are racing to harness GenAI’s potential. The day after being sworn in as President of the United States in January, Donald Trump announced a $500 billion domestic AI infrastructure investment. At the Paris AI Action Summit a few weeks later, President Emmanuel Macron announced that France was “back in the AI race” with €109 billion of private investment. China is also experiencing an AI boom accelerated by the launch of the low-cost and popular DeepSeek-R1 GenAI model.
GenAI is a technological breakthrough comparable to the “change from flip phone to smartphone,” says Abhay Pradhan, head of analytics technology at LSEG. “This is one of those technologies where the size of change is massive.”
But maybe we shouldn’t be too hasty to crown the new king. Perspective is needed to fully understand whether this most recent iteration of AI is indeed the catalyst for economic growth that it is being hyped up to be, says Sid Sriram, LSEG’s head of AI engineering, who has worked with AI and AI-related technology for more than 20 years. “There is an exaggerated expectation of what generative AI can do, which is not yet fully backed up by the actual capabilities,” he warns. For Sriram, we are witnessing “the third coming” in a technological evolution that began with early statistical techniques 60 years ago and was followed by the advent of machine learning and data mining at the turn of the century. GenAI offers “a large opportunity to apply AI techniques to a broader class of problems than we could in the past, and with much less effort, but it doesn’t work perfectly for all use cases,” he says. “I am excited, but I am also pragmatic.” His colleague Emily Prince, group head of analytics at LSEG, says GenAI will bring “change for generations to come,” but also urges caution in its application. “AI is best when we are precise about the problem statement, and clear about what success looks like,” she says.
Identifying how to change carefully
Despite any unrealistic expectations, signs that GenAI can be a driver of economic growth are already becoming apparent as repetitive tasks are being reduced and the speed of product generation is increasing. Sriram might doubt some of GenAI’s grander claims, but he has seen significant productivity gains at LSEG for some processes, achieved by applying the technology to improve workflows. “The efficiency improvements are making a big difference to our content operators and our ability to provide more high-quality data more quickly to our customers,” he says. Pradhan describes GenAI as an “amazing productivity tool” that has removed “a lot of the drudgery” in LSEG’s code generation processes. Prince heralds a more democratic future where “people generate code without coding.” She also thinks that GenAI’s ability to write a business plan or create a website can “enable and unlock a huge amount of growth and opportunity within society” by simplifying processes for setting up a new business. “You can actually build a business very cheaply.” The technology is accelerating LSEG’s ability to bring new products to market. “The ideation, experimentation and proof-of-concept process becomes much faster,” Pradhan says. For Sriram, speeding up product development is a crucial metric of the value of GenAI. “The velocity at which we can deliver new products and product enhancements has increased,” he says.
Significantly boosting productivity
In a highly regulated industry like financial services, a probabilistic technology such as GenAI will often be unsuitable. “A lot of guardrails need to be put in place,” Prince says. “We need to make sure we insert the right level of control around model risk management in terms of regulations that we and our clients are subject to.” GenAI might help carry the burden of monotonous tasks, Sriram says, but “I don’t yet want a fully automated system managing my retirement portfolio. We are so far away from that.” LSEG always ensures that there is a “human in the loop” to verify its processes. “We don’t just trust what comes out of the model; we verify,” Pradhan says. “There are a lot of techniques we employ to make sure that our data is safe, secure and of high quality, and our usage of AI adheres to our responsible AI framework. This framework is based on a set of principles which aim to enable the safe and responsible use of AI by ensuring accuracy, accountability and resiliency, among other things.” He identifies the technology sector, financial services, healthcare and law as sectors that will most immediately benefit from GenAI as they all have many repetitive administrative tasks that could easily be automated.
Speed is not always the objective
While economies might benefit from the AI rollout, there will be impacts. Prince says that AI skills will become “a big differentiator from a labour market perspective.” Training in the use of AI models, she says, will be “incumbent on organisations to advance themselves, but also to ensure the career progression of their people.” What is clear, says Pradhan, is that “costs will start coming down” as AI models improve. And Prince predicts more economic benefits will come as AI advances are shared from one sector to another. “Increasingly, the things that are driving productivity in this industry are not coming from financial services, but are cross-industry and pollinating across,” she says. “We get a lot of benefit from innovation happening elsewhere.” Sriram, while realistic, is also increasingly upbeat. When he joined LSEG 18 months ago, GenAI was being touted as the solution to every problem. “The lens we now use is: ‘Does it solve the customer problem?’ A year ago, the answer was mostly, ‘No,’” he says. “The answer now is, ‘Yes, you can apply this to an increasing number of customer problems.’ Our approach is to embrace the potential but be pragmatic and not get swept away by the hype.”
The human impact
Disclaimer: The Reuters news staff had no role in the production of this content. It was created by Reuters Plus, the brand marketing studio of Reuters. To work with Reuters Plus, contact us here.
Learn more about LSEG’s data offerings and how it is managing the future of data »
“GenAI is a technological breakthrough comparable to the ‘change from flip phone to smartphone.’”
Abhay Pradhan, head of analytics technology at LSEG
“AI is best when we are precise about the problem statement, and clear about what success looks like.”
Emily Prince, group head of analytics at LSEG
“Our approach is to embrace the potential but be pragmatic and not get swept away by the hype.”
Sid Sriram, head of AI engineering at LSEG
The Reuters news staff had no role in the production of this content. It was created by Reuters Plus, the brand marketing studio of Reuters.
Produced by Reuters Plus for
Disclaimer: The Reuters news staff had no role in the production of this content. It was created by Reuters Plus, the brand marketing studio of Reuters. To work with Reuters Plus, contact us here.
