To capitalize on the large potential of synthetic intelligence (AI) enterprises want methods purpose-built for industry-specific workflows. Sturdy area experience, strong information foundations and progressive AI capabilities will assist organizations speed up enterprise outcomes and outperform their opponents.
Enterprise expertise leaders mentioned these points and extra whereas sharing real-world examples throughout EXL’s latest digital occasion, “AI in Motion: Driving the Shift to Scalable AI.”
“The important thing to driving actual affect lies in seamlessly integrating information and AI into the way in which companies work,” mentioned Rohit Kapoor, chairman and CEO, EXL. “It’s not nearly implementing expertise. It’s about orchestrating information, digital options and human intelligence to optimize decision-making and unlock new alternatives.”
The 12 months of agentic AI
Agentic AI holds the important thing to unlocking these alternatives. With autonomous, self-regulating AI brokers, enterprises can create automated workflows that adapt to real-world enterprise complexity and increase their human specialists to spice up effectivity, accuracy and innovation.
Kevin Ichhpurani, president of world companion ecosystem with Google Cloud, shared an instance of a mutual consumer and the way EXL and Google have helped them with customer support brokers. The brokers perceive the patron’s intent once they name, make educated choices via advanced reasoning after which take motion, corresponding to initiating a product change or ordering a alternative unit.
“We see [2025] because the 12 months of delivering agentic experiences for purchasers, the place we automate full end-to-end enterprise processes,” Ichhpurani mentioned.
To attain this aim, EXL final month launched its agentic AI platform, EXLerate.AI. It orchestrates AI fashions alongside human experience and analytics “to assist companies harness AI with out getting slowed down by technical complexities,” Kapoor mentioned.
The digital occasion additionally featured demos of EXL Code Harbor, a generative AI-powered code migration software, and EXL’s Insurance Large Language Model (LLM), a purpose-built resolution to the {industry}’s challenges round claims adjudication and underwriting.
The Insurance coverage LLM is educated on 12 years’ value of casualty insurance coverage claims and medical information and is powered by EXL’s area experience. Constructed on NVIDIA’s AI stack, the LLM delivers 30% larger accuracy and 30% decrease prices than general-purpose fashions.
“Insurance coverage LLM assists declare adjusters to be extra productive and correct in a shorter time interval,” mentioned John Fanelli, vp, enterprise software program, NVIDIA. “It additionally delivers the very best outcomes for each the insurers and the insured. Insurance coverage LLM is a incredible instance of what we name an agentic AI system.”
AI within the wild
In two occasion panels, enterprise AI practitioners shared the traits they’re seeing this 12 months and the way they’re adapting. The primary dialog centered on the evolving symbiosis between information and AI.
“There was a dialogue about how a lot information you’ve,” mentioned Sidd Kuckreja, CTO with TruStage. “Now it’s concerning the high quality of information as you consider the regulatory panorama, bias mitigation, privateness and moral issues.”
Randy Huang, vp and chief information scientist for U.S. enterprise with Prudential, emphasised the significance of safety and governance, as a result of extra individuals are utilizing AI platforms to entry and use delicate information.
“The concentrate on information is admittedly altering based mostly on how the information is generated and the way the information is used,” Huang mentioned.
And Preetha Sekharan, vp of Unum’s digital incubator, famous that whereas information can gasoline AI innovation, the inverse can also be true.
“What is admittedly fascinating with genAI and newer applied sciences is how AI can speed up the way you generate, the way you rework, the way you perceive information,” Sekharan mentioned. “That’s actually a captivating twist in how we take into consideration information.”
The second panel centered on how AI helps enterprises preserve a aggressive benefit. NRG Power makes use of AI to conduct ongoing situation modeling, analyzing climate and forecasting its results on buyer demand and power costs.
“There’s lots of information factors, and … there’s a extremely good alternative to make use of that to do higher prediction,” mentioned Dak Liyanearachchi, chief information and expertise officer.
Sarthak Pattanaik, head of the unreal intelligence hub at BNY, mentioned the financial institution’s inside platform, which permits workers to construct AI-powered methods whereas guaranteeing safety, privateness, equity, moral utilization, accountability, and transparency.
“It democratizes entry to AI in a accountable style, so it helps innovation at scale,” Pattanaik mentioned.
And Dr. Ashish Atreja, professor of drugs at College of California – Davis Well being, spoke about AI enhancing affected person entry to care.
“The largest worth for sufferers that’s going to occur is shifting healthcare basically from one-to-one care, the place you need to be with a doctor and a affected person in the identical house and time, to one-to-many care — how one can automate digital care pathways via digital avatars, via digital apps, via digital therapeutics,” Atreja mentioned.
A elementary transformation
Merely adopting AI is not sufficient. As {industry} leaders emphasised throughout EXL’s occasion, success requires integrating AI with high-quality information and deep area experience — whereas rethinking and optimizing enterprise processes.
“AI isn’t just a technological shift,” Kapoor mentioned. “It’s a elementary enterprise transformation.”
To be taught extra about what agentic AI and EXL can do for what you are promoting, go to here.