Chapter 1: What insights does Priyanka Vergadia share about AI's capabilities?
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You're listening to TED Talks Daily, where we bring you new ideas to spark your curiosity every day. I'm your host, Elise Hu. Don't compete with AI, work with it. At least, that's what technologist Priyanka Vergadia says. In her talk, she takes a look at the collective fear that AI is coming for our jobs.
While sharing what AI is really good at, she also digs into what it misses and why building stronger collaborations between humans and AI is our best bet for a future that allows us to stay, as she puts it, irreplaceably human.
Well, 71% of Americans believe that AI will cause massive job losses. Algorithms are getting smarter, faster, more capable every single day. My work puts me at the heart of this anxiety, where I bring AI applications to market for big tech companies, and I help customers and businesses really take the potential of this technology further for their businesses.
And through it all, I've seen brilliant professionals second-guess themselves as AI gets smarter. But let me tell you this one fundamental truth about AI. AI is excelling at identifying patterns. It understands data. We humans excel at understanding what these patterns actually mean in this beautifully chaotic world of human behavior.
And even as these models and algorithms get stronger over time, this will stay true. Why? Because we understand things that cannot be quantified. context, intent, unspoken emotions, cultural nuances. This depth of understanding comes from lived experiences that AI cannot replicate.
So today I'll share with you three stories from my experience to prove this point, that AI understands data and we understand experiences. And the key here is to not compete with AI, but to work with it while staying irreplaceably human. So how do we do that? Well, I was recently at a conference and met Sarah, a product manager.
Her team has built an AI-powered analytics dashboard that's telling them very clearly that 80% of their users are only using basic features and 20% are using advanced features here and there. Now, Sarah looks at this data and she's like, OK, logically, it makes sense. But she's questioning it. And this is the part I really love. She didn't just trust the algorithm as is.
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Chapter 2: How can humans and AI collaborate effectively?
He dug a little further and identifies that the customer is going through a restructuring. And Three teams thought that they owned the decision to make this purchase. If Marcus didn't get into this human element of the deal, the deal would never happen. AI identified the activities. Marcus measured meaning in those activities. So the lesson to learn from this story is
you need to read the room, not just the dashboard. Understand those micro-expressions, the social cues in the room, the what are people saying, how are they nodding. We've all been in meetings where somebody says, that's interesting. Are they politely dismissive or genuinely curious? Well, our emotional radar knows that. AI doesn't.
I was with a friend recently, her name is Priya, and she works to use social media as a platform to help brands grow their revenue. Her AI tool is telling her to post fashion hack videos, those videos where you get a lot of fashion tips out for one of the brands. And she did that, and they saw great engagement, lots of follower growth.
But when talking to the team, they identified that none of that follower growth and engagement on social media was leading to sales or revenue. They were building the wrong audience. They were attracting bargain hunters that was exactly opposite of the person who would pay $200 to buy an ethically made jacket. This was what this brand makes. Now, AI was optimizing for followers and engagement.
Priya knew that they were making the wrong audience, so she flips the switch. She stops taking AI-recommended content, instead starts building content that is showing sustainable cost of building these fashion items. She started showing stories of artisans that were making these clothes. Now, AI in this case was optimizing for activity and engagement. TRIA optimized for building a community.
And they started seeing the sales skyrocket. So the lesson that we learn here is always pause and ask, what is the story behind this data? And only we can do that. So if you see all these examples, there's one thing very common. The future doesn't belong to humans or AI. It belongs to humans that work closely with AI while staying irreplaceably human.
Our ability to read the room, our ability to look at emotions, That is irreplaceable. Our ability to empathize with people, that's irreplaceable. So the next time you're feeling anxious about AI taking your job, remember that AI can identify patterns. Only we and you can identify the human behind it. Thank you.
That was Priyanka Vergadia at TED Next in 2025. If you're curious about TED's curation, find out more at TED.com slash curation guidelines. And that's it for today. TED Talks Daily is part of the TED Audio Collective. This talk was fact-checked by the TED Research Team and produced and edited by our team, Martha Estefanos, Oliver Friedman, Brian Green, Lucy Little, and Tansika Sangmarnivong.
This episode was mixed by Christopher Fasey-Bogan. Additional support from Emma Taubner and Daniela Balarezo. I'm Elise Hugh. I'll be back tomorrow with a fresh idea for your feed. Thanks for listening.
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