Content+Data+AI: Newsweek’s Fresh Recipe for Success

Arham: I was looking up Newsweek and their initiatives on AI, and they had this huge tagline which said ‘CONTENT + DATA + AI.’ I want you to open up that and just talk about this journey.

Bharat: It’s just the start of that journey. I’ll probably talk in more generic terms about where the media industry is headed, specifically the legacy media industry like Newsweek, Time, and others. For the longest time, brands like Newsweek, Time, and The New York Times have been, and still are, the hallmark of journalism.

But content is so ubiquitous now that it’s really hard to figure out what’s factual and what’s not, what’s objective and what’s not, what we trust and what we don’t. Every media company says trust is their biggest value, but then, trusted by whom?

Beyond that, you have a deluge of content from small, medium, and large companies, from bloggers to YouTubers, that has penetrated the market. It’s truly difficult to search and find objective and factual content from even a few of these legacy brands. You have to be very intentional about it.

Bharat: So, I think this is a real opportunity for us. If I had to reach out to a few people and say, “Hey, check out this article or video,” that’s typically how the conversation goes. I call them, “Have you seen it?” And then they’ll go look it up. If I had to do that for millions of people, it’s impossible.

That’s where I feel like AI and AI agents can help. They could play the role of unearthing content that’s useful in people’s lives, but coming from a source that’s journalistic, objective, and trusted by them or people like them. This content could be brought to them in a fashion where it gets through the clutter and reaches them.

I see a lot of opportunity with AI for us, and even in Newsweek, where we can reach out to millions of people with our content in a fashion they like, in a medium they like, and personalizing it for their needs.

On the other hand, we can also make our staff more intelligent and efficient to generate better content, more content, and meet the needed scale and quality for content production. So, there are a number of opportunities there, but we’re starting with small steps. How does somebody actually find the content we produce? Then we’ll get into how to personalize it next. We’re also learning about the best models out there that we should be using and how to build an infrastructure that can personalize it.

For us, it’s a learning journey. None of my colleagues, and even most of our media companies, didn’t grow up in the research world. They didn’t grow up in AI or do AI research as their job. They did content research, they did basic engineering. So, that’s why we want to partner with the likes of Google and Zazmic to bring that expertise into our company and short-circuit that expertise needed for us.