Generative AI adoption is spiking and starting to generate value at an accelerated pace.
According to McKinsey, about 80% of organizations have reported they believe their organizations will be transformed significantly over the next 36 months from generative AI.
An example of generative AI that can be commonly understood is the technology of computer vision image recognition that can disrupt even interactions with teenage children, said Partha Chatterjee, digital transformation and technology strategy leader with Shell.
Chatterjee recently tagged his teenage daughter in a photo on social media and said that when he tried to undo it, it was too late. Even if he had been a bit quicker to hit the button at his daughter’s request, AI had already stored her image.
"That’s disruption, and it has happened in technology, is happening in AI, is going to happen in Gen AI and many more technologies to come," Chatterjee said.
Speaking in September at the 2024 Digitalization in Oil and Gas Conference in Houston, Chatterjee shared tips on evaluating AI vendors to strategize advancement in technology and optimize data capture in AI models for strategic insights.
He said generative AI is a type of AI that is capable of generating text images and having conversations with people, in ways that mimic human intelligence.
The Natural Language Processing piece involves processing languages using different models to help people understand conversations and give context to things being generated, Chatterjee said.
"ChatGPT fell from the sky, something which was supposed to be just hidden, something for the nerds, just became all-pervasive," he said. "It’s built on those language models. It’s a chatbot developed by OpenAI and it simulates human-like interaction and simulates conversation.
Generative AI: A disruptive technology predicted to generate trillions
Partha Chatterjee, digital transformation and technology strategy leader with Shell, speaking during the 2024 Digitalization in Oil and Gas Conference in Houston.
"It understands. It trains on modern data and then it can help you make decisions. You can converse and tweak decisions, and then you get better at it, just like humans learning stuff. And they will get the hang of it. So, when you say, I want to take a left in London, it knows that left is different from can I get a lift from you?"
Using market data can help employees sort the differences in data, Chatterjee said. Sales data can be merged with inventory data, supply data and sales data, providing a forecast for supply and demand.
Creating a data catalog can then help employees ask questions, like what the power load was at a facility in a specific location during hot weather, he said. Different quantitative data can help drive decisions, price, demand, supply and inventory, Chatterjee said, which can be merged with market sentiments.
The data generated can then be analyzed and paired with quantum models to drive better decisions. Generative AI can also run queries and code, which is expected to be routine in the next few years, Chatterjee said.
"It’s happening all over the industry, the gap between business and IT is really, really disappearing because a lot of these tools — DNA, AI, data science and machine learning tools — are empowering businesses so that they become better coders," he said.
"They become better developers and can actually serve their own needs."
Chatterjee said AI is a powerful tool, but one that must be used judiciously. It will improve over time and will remain essential for businesses to solve harder problems to meet the needs of the company.
"The technology will get disrupted, but you have to work with the technology and then take it to everyone. And that’s the world we would like to see," he said.
