Shobit Varshney: I've gone through this whole phase of, Oh my God, this is gonna change this entire world now. So, there's an AI compute explosion, there's a data explosion. IBM has contributed quite heavily in the space on developing algorithms that can harness that power of data and AI. We need to make sure that we are reducing the barriers of collaboration. (upbeat music) Varshney: Hello, I'm Shobhit Varshney. I'm a senior partner and VP in IBM Consulting. I'm accountable for all of our AI business in the US, Canada, and Latin America. It takes years to build trust and takes a moment to lose it, and innovation has to run at the speed of trust. Within IBM, we very much prescribe to having alignment on core values first and then the principles that support them. And then you think about what kinds of orchestration processes and technology and tools that are needed to then go operationalize them.

When we are working with our large clients, we start by understanding their true north. What is their business strategy commitment to their shareholders, right? From there, you break that down into what processes and how workflows happen in the organization. And then you get to this one particular workflow that is high value. For that high-value workflow, you figure out how do you surgically get the right blend of AI automation and generative AI. Those models will keep changing, grounding of that model in your workflow, in your process, in the data that enterprise has, that's what unlocks the value, models over time will start getting more and more commoditized. Then we take that model and then we have to adapt it to enterprise data. We have our own series of models that we've built with IBM research, we call them the Granite Series. Earlier the champions used to be data scientists and vertical stack. Now that AI business is more horizontal,

so the champions have to come in from within each of those lines of businesses. So you need to find people who are excited about adopting AI, but they have to be very conscious about what's the right frame to deploy that AI inside of the processes and workflows that they do every day. They need AI ethics education, they need to have the right set of tools available to them so they can accelerate, and they need to have the right culture of where and when AI will truly augment their workflow. It has to come from within the champion backbone. So you get into this augmentation mindset versus AI being done to you. Now you have given the human all the information that they would otherwise been missing, and now they're able to quickly make decisions, and they're the ones who tell you where they want augmentation and AI versus things that the data science team thinks it's cool, but in the real world, it just crashes and burns 'cause they don't understand the reality.

of how difficult the real world is. But overall, anything that is customer-facing, you'll see a lot more willingness to ship fast to deliver new features, and you'll see companies making those choices. We're trying to reduce the barriers of entry for AI, and it should be democratized across everybody. You should have access to insanely good AI models that are built in the most sophisticated labs in the US, all the way into somebody who's in a village in India who can tap on a feature phone and get access to it, right? I think it's gonna have a very significant impact on our lives. I could not have asked for a better job. What a world we live in, it's just incredible.

Navigate The Path To Innovation With An AI Roadmap | Business Insider

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