Program

Welcoming Chase Davis and Sonali Verma to the Lenfest AI Collaborative and Fellowship

“We’re sharing every step of the journey: ‘Here’s the code. Here’s what we’d do differently. Here are the challenges we ran into and how we overcame them…’ We’re all learning from one another.”

July 14, 2026

News organizations around the world are exploring how artificial intelligence can strengthen their work, but many are learning in isolation, even as other publishers tackle similar challenges and test similar ideas.

The Lenfest AI Collaborative and Fellowship Program was created to help change that. Through the program, news organizations are experimenting with AI to solve real business and operational challenges while sharing what they build, their lessons, and open-source code that others can adapt in their own newsrooms. 

To support those efforts, The Lenfest Institute has welcomed Chase Davis as Technical Lead for the Lenfest AI Fellowship and Sonali Verma as Amplification Lead. Together, they will help capture, document, and share lessons emerging from the fellowship so that news organizations across the industry can learn from one another more quickly, efficiently, and effectively.

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Chase is a journalist, technologist, and newsroom leader who has spent his career working at the intersection of news, data, and emerging technology. He led the Interactive News team at The New York Times, oversaw digital and cultural transformation at The Minnesota Star Tribune, where he participated in the Lenfest AI Fellowship, and has worked as a reporter, data journalist, software engineer, and journalism educator. Chase helps news organizations adopt emerging technologies in ways that strengthen both their journalism and their businesses.

Sonali helps news organizations around the world transform their business models and embrace data-driven decision-making. During her 15 years at The Globe and Mail, Sonali led audience development and digital transformation initiatives that helped journalists use data to better attract and retain subscribers. She later helped develop Sophi, the Canadian newspaper’s high-impact AI and machine-learning platform, before serving as its senior product manager and director of customer success. She has also advised publishers through digital transformation work with organizations, including FT Strategies and the International News Media Association (INMA).

The AI Collaborative and Fellowship is supported by OpenAI, Microsoft, The Lenfest Institute, and other donors. 

We recently spoke with Sonali and Chase about what they’re seeing across the Lenfest Fellowship, the opportunities AI presents for local news, and why sharing both successes and setbacks is essential to helping the news industry move forward.

What interested you about the chance to support the Fellowship’s learning and knowledge-sharing efforts?

Sonali Verma: Everyone in the news business is experimenting with AI right now. What I’ve seen in the projects being built is that there’s a lot of replication. Everyone’s trying to solve the same problems and often approaching them in similar ways.

If we can save the industry some cycles of development, if we can keep people from reinventing the wheel because they can see what others are doing, learn from their mistakes, and move faster, then we’re doing everyone a favor.

That’s what really struck me about this program. You’re not just saying, “Hey, we built a thing.” You’re sharing every step of the journey: “Here’s the code. Here’s what we’d do differently. Here are the challenges we ran into and how we overcame them.” The idea that we’re all learning from one another really appealed to me.

Chase Davis: I actually come to this from a different perspective because I was part of the fellowship while leading a team at The Minnesota Star Tribune. We hired two fellows, so I had the chance to see firsthand not just what this program can do across the industry, but what this kind of engagement can do within an organization. It really is a lever for cultural change and an accelerator for the kinds of changes newsrooms are trying to make.

Journalism has an unfortunate history of having emerging technologies inflicted upon it. We often find ourselves reacting to change instead of helping shape it. What I really appreciate about this fellowship is that it’s one of the few examples I can think of where we’re trying to play offense with a new technology and really trying to empower people to figure out the best way to take advantage of these things in the context of the communities the different newsrooms serve.

For readers who may be unfamiliar with the fellowship, how would you describe the work happening across the Lenfest AI Collaborative, and why does it matter right now?

Chase: So far, we’re working with 11 news organizations across the country that are applying generative AI to practical, hands-on problems related to journalism, revenue, and business sustainability.

Every newsroom gets to decide where they want to focus. Some are building newsroom tools that help monitor public meetings or enrich archives. Others are working on advertising, audience development, subscriptions, and other business challenges.

What’s been really interesting is seeing the breadth of problems across the industry and the different ways these organizations are applying the technology. That tells us a lot about where AI can help local news today.

“The organizations that are doing things right are the ones that aretrying to empower those people whose day-to-day is meaningfully enhanced by generative AI and putting tools in their hands, giving them agency, giving them training, accelerating them, and using them to help propel the technology through the organization.” 

Chase Davis

Sonali: What really appealed to me is the focus on building sustainable news businesses. This isn’t just, “Here’s a cool new technology and you can do cool new things with it.” It’s about solving real problems that help news organizations keep the lights on, build stronger businesses, and continue serving their communities.

That’s a rare opportunity. News organizations around the world are strapped for resources. Here’s a chance where someone gives you a tool and some money and says, “Look, we want to help you solve an important problem so that you can build a sustainable business and you can model that for the rest of local news anywhere in the world.” 

That to me, really matters. That it’s about solving real problems, and it’s about supporting a stronger society, a stronger democracy, not letting the role of the press be undermined as it has been in many countries already.

Many news organizations are still figuring out how to approach AI. What separates organizations that are making meaningful progress from those that are still struggling to move beyond experimentation?

Sonali: It’s not the technology that is the problem. Often it’s the culture. It’s whether people feel empowered, supported, and encouraged to go out and experiment with it and then to scale it.

The organizations making the most progress are thinking about how to bring people along. They’re investing in training, creating ways for people to share feedback, and putting clear AI policies and guidelines in place. That gives people confidence to experiment because they understand what’s acceptable and where the guardrails are.

The other thing they have in common is that they’re solving real problems. They’re looking at audience needs, workflow challenges, subscriber behavior, or other business priorities and asking where AI can actually make a difference. Once people understand that AI tools close gaps and solve real problems, it’s much easier to build support across the organization.

Chase: Since generative AI has come around, people talk about there being this jagged frontier to this technology. Among other things, what that suggests and what that means is that AI capabilities can be stronger or weaker at doing certain things, and also generative AI specifically can do more or less to help people with their jobs, depending on what their jobs are. 

So this technology doesn’t apply evenly across the board in terms of what it can do for people. It really depends on what your vantage point is as to how much advantage you can take of this technology. So you might have people in your organization whose jobs are really enhanced by this, and they can do many things that they couldn’t do before, do those things faster, do those things better, etc. And you also might have folks for whom those benefits aren’t immediately as clear, just based on what they do and what they value. 

The organizations that are doing things right are the ones that are trying to empower those people whose day-to-day is meaningfully enhanced by generative AI and putting tools in their hands, giving them agency, giving them training, accelerating them, and using them to help propel the technology through the organization. 

Sometimes, where things don’t go quite as well is when we look at AI as this monolith, and when we try to legislate that everyone in our organization must use it in a certain way. Those approaches are often well-intentioned because you don’t want people to fall behind. But because AI affects different roles in different ways, that one-size-fits-all approach tends to be less effective.

One of the goals of the Lenfest Collaborative is to share lessons beyond the participating organizations. What do you hope other newsrooms take away from this work?

Sonali: I hope they come away with practical ideas they can use themselves.

Sometimes it’s seeing another newsroom’s project and thinking, “That’s a great idea.” Sometimes it’s hearing someone say, “I wish I’d known this before I started.” That kind of candor helps other organizations leapfrog challenges instead of repeating them.

Whether it’s how to hire an AI fellow, how to prioritize projects, or simply learning how someone else approached a problem, those are practical takeaways that any newsroom can apply.

If a local newsroom is feeling overwhelmed or uncertain about AI right now, what advice would you give them?

Chase: The first thing I’d say is that AI is not an “it.”

We’ve started talking about AI as one giant thing, and I think that makes it feel bigger and scarier than it really is. There are lots of different AI technologies with different strengths, different weaknesses, and different uses.

The closer your conversations get to practical examples and real use cases, the less intimidating it becomes. Learn about the technology, understand where it’s useful, understand where it isn’t, and have conversations about those specific applications instead of treating AI like one big abstract idea.

Looking ahead, where do you see the greatest opportunities for AI to strengthen local news?

Chase: I’ve always thought the business of journalism is relatively simple. You have to produce distinctive journalism that matters, and then you have to get the maximum number of people to care about it.

On the first side [of producing journalism] there’s ways that we can use these tools to do stories we couldn’t before, which is awesome, and to be able to research things and have a broader perspective on our communities. But at the end of the day, the judgment of actually creating journalism is the distinctive value that we provide on that first side of the equation. 

On the second side, with reaching people, there are so many opportunities to use generative AI to identify the parts of stories that are most relevant to people’s lives and make sure they see them. It can help create and enrich the data we already use to understand our audiences, develop new strategies, and better evaluate how we’re spending our time as journalists.

There are a lot of opportunities to help more people discover and connect with our journalism, and that’s where generative AI can be incredibly useful. A lot of that work isn’t flashy. It’s very in the weeds. It’s about creating metadata, analyzing it, and improving all of these systems that feel very mechanical, but can add up to expanding the audience for our work in meaningful ways.

“Now we have the technology, and it’s no longer prohibitively expensive to create a highly personalized product for an audience segment. In the past, that simply wasn’t possible for most news organizations. We really have an opportunity to understand why people come to us and meet their needs more effectively.”

Sonali Verma

Sonali: Right now, most news organizations are using AI to do what they’ve always done, just faster or more efficiently. Where I think the real opportunity lies is in growth.

What can you do that you’ve never done before? What can you produce that really addresses a need that your audience has?

Information is abundant today. Why would someone come to your publication instead of an AI answer engine? What do you offer that they don’t? How do you reinforce trust? How do you help audiences understand the reporting, expertise, and human judgment behind your journalism?

Now we have the technology, and it’s no longer prohibitively expensive to create a highly personalized product for an audience segment. In the past, that simply wasn’t possible for most news organizations. We really have an opportunity to understand why people come to us and meet their needs more effectively.