Generative artificial intelligence has evolved beyond being just a promising tool; it has become an essential asset. With gen AI’s remarkable ability to comprehend, transform context and generate new content, it has already demonstrated significant value in enhancing business operations.

Companies are successfully executing use cases with gen AI solutions but struggling to scale them into value-based solutions across their enterprise, according to Saurabh Mohanty (pictured, right), partner/principal at PricewaterhouseCoopers International Ltd. The focus should be on the real business value of technology implementation rather than getting caught up in hype and distractions that don’t improve the organization.

“I think companies have successfully been able to execute use cases, and those use cases are showing that there is an odd of possible in terms of what you can do with your generative AI, large language models,” Mohanty said. “Google has amazing models in their Vertex AI model garden, and companies are embedding that into multiple solutions. But what companies are struggling with right now is how to take those use cases and how do you really scale them into value-based solutions that they can drive across their enterprise.”

Mohanty and Scott Petry (left), partner at PwC, spoke with theCUBE analysts Savannah Peterson and Rob Strechay at Google Cloud Next 2024, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed creating real business value through AI solutions and development of an AI factory to centralize and scale AI solutions for clients. (* Disclosure below.)

Scaling gen AI for business success

Consultants advise clients to have a robust governance model in place to balance risk and ROI, and to actively enable the use of technology without being irresponsible, according to Mohanty.

The regulatory environment is changing, and it’s important to consider how deploying solutions will impact customer service and governance, Petry explained. Regulated businesses must be aware of the regulatory risks associated with their actions and should consider responsible and ethical behavior with powerful technology, even before government regulations are in place.

“We’re acutely aware of the regulatory risks associated with the things that we do. We advise our clients in many ways on how to manage their regulatory environment,” Petry said. “The governments basically lag so much on what’s actually happening, what’s actually possible. A certain part of responsible AI or ethical AI is to think about what the right answer is and not wait for the government to make it a regulation. What is a responsible way to behave with this kind of powerful technology?”

Organizations have varying levels of receptiveness to new technology, with a focus on advising on governance, usage, AI factory development and business model reinvention. At the same time, centralizing governance and data strategy is essential before democratizing access to data and tools, according to Mohanty.

“The other thing I’d like to add to that is AI has been there for years. Just because generative AI is now being used by people who don’t have a data science background, it’s just all the hype that got created,” Mohanty said. “I think companies should think about governance, risk, responsibility, regardless of whether it’s a generative AI solution or whether it’s a machine learning solution or whether it’s a deep learning solution.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Google Cloud Next 2024:

(* Disclosure: PricewaterhouseCoopers International Ltd. sponsored this segment of theCUBE. Neither PricewaterhouseCoopers International nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE