“With [generative and agentic] AI, you have access to more real-time data than any person can handle, and because you can process that you can discover new things and solve problems that are too complicated for one person to solve on their own. It’s like the discovery of a new drug or the creation of a new type of building material.”
That’s what Anil Jain —Global Managing Director, Strategic Consumer Industries at Google Cloud — told Telecompetitor in an interview last week.
Jain said the rise of generative AI (gen AI) and the sudden accessibility of AI tools in the last two years has resulted in a profound shift in consumer expectations and companies’ capabilities. “Gen AI has been worked on for years. But it has accelerated so dramatically that every organization is thinking, top to bottom, about ‘how will this affect me?’”
He also talked about the rise of agentic AI and “AI-native networks.” Where AI processes information, agentic AI is further empowered to act on that information and analysis. Jain likened agentic AI to human reasoning and decision-making.
“Between information and action is reasoning,” he said, “Not just ‘If I see A, do B,’ but here’s a complex set of data, and given this and some other things I can learn, my assessment of the opportunity is X. And based on what I know the KPIs for the business are, I’m going to make this decision, and then I’m empowered to go and execute all of this.”
With agentic AI, Jain said, “I have agents — that are AI programs — able to take this data, reason, and execute tasks on my behalf.” Human operators then monitor the decisions made and the actions taken by AI agents. Google is working on this technology now, with Google AgentSpace currently under development.
Jain described AI-native networks similarly to agentic AI: “AI-native networks are an evolution where what we’re looking at is the ability to have AI infused across the entire network, to see what signals are coming in, understanding of all those signals, learning patterns and making predictions, then automating how to address issues that might arise.”
“Some people call it network optimization,” he said. “AI-native or AI-driven is about leveraging AI in every aspect of how I run the network and interact with consumers, all of which is providing a better customer experience while lowering costs.”
Jain described agentic AI as having several benefits for companies:
- Increasing efficiency. With the ability to make decisions and carry them out, Jain said the efficiency benefits of agentic AI are enormous. “The cost optimization of reduced time to resolution [is huge]. You haven’t taken up anyone’s time, and in the case of problem resolution maybe you’ve reduced the time in which customers might have noticed an issue.”
- Improving customer experience. AI processes large amounts of information far faster than a human can, leading to faster resolution of customer issues. “Complex layers of billing, coverage information, services, and upsell information form a multifaceted, multilayered complexity that creates friction in creating a positive customer experience,” said Jain. “AI capabilities handle all of that.”
- Driving new revenue. Combining AI with customer data — “in a safe and secure manner, because telecommunications providers are beholden to their community to protect their data” — allows for upsell opportunities. “You can empower your AI agent to say, ‘I see your family’s usage, and I’m going to proactively offer you some things to make your experience better or upsell you.’”
- Preventing customer churn. By monitoring customer usage, providers can use AI to spot potential issues before they arise. This might mean training agentic AI to learn what problems lead to customer churn and to proactively offer something like a discount or faster speeds, Jain said. Agentic AI can also notify customers when a potential network issue has been identified and resolved, which helps customers feel more loyal because they know their provider is watching out for them.
Jain summed up the promise of agentic AI by describing the impact on individual employees: “Imagine having a super-powered AI agent on your shoulder in whatever you’re doing, allowing every individual to do more with their time — or better with their time — because they have an AI agent able to synthesize vast amounts of data and connect to their workflows and applications and pull it all together.
“This changes the nature of what’s possible for that person to do in executing their job,” said Jain. “Watch this space—there’s a lot more coming in this area.”
