AI in action: How enterprises are scaling AI for real business impact

Artificial intelligence (AI) requires a system for industry -related workflows to take advantage of the capacity of businesses. Strong domain skills, solid data foundations and modern AI capabilities will help organizations accelerate business results and improve their competitors.

Enterprise technology leaders discussed these issues and even more, while sharing real -world examples during the recent Virtual event of EXL, “AI in action: Scaleable AI to change.”

“The key to running the real effect is to integrate data and AI into a business operating method,” said Rohit Kapoor, the chairman and CEO of Excel. “It’s not just about enforcement of technology. It is about data, digital solutions and human intelligence to improve decision -making and unlock new opportunities.

Year of Agent AI

Agent AI has the key to unlocking these opportunities. With autonomous, self -organizing AI agents, businesses can create automatic workflows that adopt real -world business complications and increase their human experts to promote performance, accuracy and innovation.

Kevin Achu Purani, president of the Global Partner Eco System with Google Cloud, shared an example of mutual client and how Excel and Google have helped them in customer service agents. Agents understand consumer intentions when they call, make educated decisions through complex arguments and then take action, such as starting a product exchange or ordering an alternative unit.

“We see [2025] As the year of agent experiences for customers, IHH Purani said, where we automatically automatically make business operations automatically.

To achieve this goal, Excel launched its Agent AI platform, Excellette last month. Kapoor said, “It Orchests Human skills and analytics as well as AI models” to help businesses use AI without being less than technical complications. “

The Virtual event also included the Excel Code Harbor Demo, a generating AI -powered code migration device, and Excel’s insurance Large Language Model (LLM), aimed at aimed at aimed at industry challenges around claims and inverting.

Insurance LLM is trained on claims and medical records of 12 years worth of deaths and operates through Excel’s domain skills. Made on NVIDIA’s AI stack, LLM provides 30 % higher accuracy and 30 % lower cost than normal purpose models.

“Insurance LLM claims accumulates and accurately produce more productive and accurate,” said John Fanley, vice president of NVDIA’s Enterprise Software. “It also provides excellent results for both insurance and insurance. Insurance LLM is an excellent example of what we call the Agent AI system.

Ai in the wild

In two event panels, the enterprise AI practitioners are watching this year and how they are shielding. The first conversation focused on the symbols created between data and AI.

“How much data you have to discuss,” said Sid Cocareja, the CTO, with the trust. “Now this is about the standard of figures, as you think about disciplinary landscape, prejudice, confidentiality and moral reservations.”

Randy Huang, Vice President and Chief Data Scientist for the US Business Professional, emphasized the importance of security and governance, as more and more people are using the AI ​​platform for accessing and using sensitive data.

Huang said, “Focus on data is really changing on the basis of how the data is manufactured and how the data is used.”

And Vice President of Anim’s Digital Incobester, Prettha Sikarn, noted that while data can promote AI’s innovation, the opposite is true.

“The really interesting thing with Geni and Modern Technologies is how AI can create your creation, how you change, how you can understand the data, it can accelerate it.” “It’s a really interesting point about how we think about data.”

The second panel focuses on how AI helps to maintain competitive advantage of AI. The NRG Energy AI uses the ongoing scenario modeling, analyzing the weather and predicting its effects on consumer demand and energy prices.

“There are a lot of data points,” said Chief Data and Technology Officer Dick Lian Rachchi, and … to use it to make better predictions is a really good opportunity to use it. “

The head of the artificial intelligence center in BNY, Sarrathk Patatak, discussed the bank’s internal platform, which enables employees to build AI -powered systems, while ensuring security, privacy, justice, moral use, accountability and transparency.

“It democratic access to AI in a responsible manner, so it helps to innovate on a scale,” said Patanak.

And Dr. Ashish Atrija, a professor of medicine at the University of California – Davis Health, spoke about improving access to patients.

“The biggest price of patients who is about to be about to be mainly transmitted to one -to -one care, where you have to stay with a physician and patient at the same place and time, you can treat digital treatment through digital apps, through digital apps, through digital acres of digital treatment.

A fundamental change

Just adopting AI is no longer enough. Since industry leaders emphasized during the EXL program, AI needs to connect with high quality data and deep domain skills for success-while business operations need to be re-considered and corrected.

Kapoor said, “AI is not just a technical change.” This is a fundamental business change. “

To learn more about what agent AI and EXL for your business, see Here.

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