From convergence to transformation: the impact of the AI ​​generation on business speed

Generative artificial intelligence is proving to be a game changer and complements other technologies to give businesses faster, more optimal results, according to Scott likesglobal leader in AI technology and innovation at PricewaterhouseCoopers USA.

“We talked about this convergence,” said Likens (pictured). “We’re studying what’s called the Essential Eight, the emerging technologies that we think are essential, but it’s in their convergence that the real power comes in. The AI ​​generation is going to help us generate much more in the simulated world. Think about multimodal concepts of 3D image generation, generative AI will advance the metaverse in ways we’ve never seen. Thinking about how we use this to accelerate time to market, I think it’s a no-brainer.

Likens spoke with industry analyst CUBE Dave Vellante has Supercloud 4, in an exclusive broadcast on theCUBE, SiliconANGLE Media’s live streaming studio. They discussed how the AI ​​generation is improving other technologies and what the future holds for this cutting-edge technology.

The AI ​​generation is a good vehicle for transformation

With the AI ​​generation starting the ball of technological innovation, the acceptance rate is remarkable based on the transformations presented. Accordingly, according to Likens, this should be made as practical as possible in business.

“Generation AI has given us a very good tool to get leaders to say: ‘The world is changing, let’s accept it, let’s invest in it,’” he stressed. “To be part of a company like PWC, we have to support a very broad range of industries. That’s really what excites me: how can we then apply this in practice.

Given the limited nature of the regulated sector, decisions may not evolve as quickly as expected. However, AI generation can eliminate this problem thanks to the presence of fundamental models, according to Likens.

“I love pharmaceutical life sciences, my ability to bring essential medicines to market and help people who need them…I think we are limited,” he said. “I think of all the sectors we work with, banking and insurance, which have to deal with enormous amounts of information. For me, it’s all about speed, and generative AI has shown us a way to do it differently.

For Generation AI to move out of the experimentation phase and into the activation phase, it must operate in a secure environment, according to Likens. It is also essential to think about the specific problems and use cases that the AI ​​generation should handle.

“First of all, get yourself a secure environment,” he said. “We’ve moved from education to experimentation, but now I think we need to move to enablement…and then think about what models of things the AI ​​generation solves well. I will give you an example, a summary of documents. It’s a huge model. We obviously work in finance, but with all our clients, there is a summary of the documents.

The need for AI agents

As automation drives the value proposition, AI agents will prove useful as there will be more focus on skills rather than processes. As a result, Likens says, human-led generative models will become the norm.

“Large language models alone will not allow us to automate,” he explained. “Now we need to think about this next wave and this next model. This is where you see things like AI agents that will help chain tasks together and break the process into smaller pieces. We want humans to take the lead, but then using AI or automation, agents will actually speed up certain processes and add quality along the way.

As data is the backbone of businesses, it is also at the epicenter of the AI ​​generation transformation. On the other hand, the AI ​​generation and AI in general have the ability to take the interaction between humans and data to unprecedented levels, Likens emphasized.

“I think we’re in a time where we’re going to see a different model of interacting with our data as humans, being able to talk to our data,” he said. “You’re starting to see that emerge now. These generative models or AI in general can look at structured and unstructured data in a different way. With this AI actually guiding us through the data as a human, I feel like the structuring of the data is for us, not the machine.

Here’s the full video interview, part of SiliconANGLE and theCUBE’s coverage on Supercloud 4:

Photo: SiliconANGLE