Three Questions Media Execs Should Be Asking About How AI Is Reshaping Their World

AI is already transforming how content is created, monetized, and distributed, with implications that extend far beyond simple automation. But what is coming next? Industry leaders from Scripps, Graham Media Group, Stringr, Defiant LA and Veritone were asked to predict the future of the media industry at TVNewsCheck’s Programming Everywhere during NAB Show 2025 earlier this month. Based on their insights, here are the critical questions media executives should be addressing right now in order to be ready for the future.

Q: What transformative AI trends will reshape media in the next 12-24 months?

Several major developments stood out from the panel discussion moderated by this columnist:

1.  Real-Time Localization From AI Translation Technologies

Kerry Oslund, VP, AI Strategy & Business Development, The E.W. Scripps Company revealed it is already implementing AI-powered real-time translation and voice cloning and lip syncing. “We’re already starting to move down that path, not so much with lip syncing yet, but the real-time translation and voice cloning technology is already state of the art,” Oslund said. “It’s pretty incredible right now.”

This technology will dramatically expand content reach by breaking language barriers and make global distribution instant and seamless. Imagine broadcasting a live event simultaneously in multiple languages with perfectly matched lip movements and in the same voice as the original speaker.  

• Why It Matters: AI-powered voice cloning and lip-syncing can make content globally accessible.
• Stat to Watch: Already, 42% of broadcast professionals identify automated translation and closed captioning as a top priority for live production workflows (Haivision Broadcast Transformation Report 2025).
• Action Items: Identify one content stream that would benefit from multi-language distribution and begin testing AI translation tools. Then test tools like ElevenLabs (voice cloning), DeepTune and Lingopal (translation and voice cloning) and Deepdub (lip-syncing) for multilingual content.

2. Creating Operational Efficiencies That Help Free Up More Time For Journalism

Michael Newman, director of transformation, Graham Media Group, emphasized AI’s role at helping journalists connect better with their audience. “For Graham Media Group, it’s really about getting more of our people out into our communities [and] leveraging AI to make things like editing, searching for videos, going through transcriptions, translating videos, versioning content — easier,” Newman said. “We’re really trying to reduce that daily busy work.”

The most valuable AI applications won’t replace journalists, but will handle routine tasks — freeing news teams to focus on field reporting, investigations, and community engagement.

• Why It Matters: Media organizations with AI-optimized workflows are reporting operational cost reductions while creating new revenue streams.
• Stat To Watch: AI-enabled workflows in media and entertainment have increased delivery efficiency by up to 40%, reducing costs through automation of labor-intensive tasks like rendering, editing and metadata tagging (Accenture).

3. Data-Driven Personalization

Lindsay Stewart, founder and CEO, Stringr, envisions a future where information is tailored to individual needs. “What we have fondly called news, but really what I think the world wants, is more valid information that pertains to their lives,”: Stewart said. “Imagine a world in which your pipeline data is being served to you in an audio form or a video form.”

Paul Cramer, managing director, media and broadcast, Veritone, framed this as an economic shift. “If you look at the evolution of the economy, we started out with the Industrial Revolution, and then we went to the information revolution. I would argue we’re entering a third revolution, which is the data revolution,” Cramer said. “All these really cool use cases from generative AI to things like personalized and dynamic content, it all starts with data.”

• Key Quote: “Your audience doesn’t want news—they want their news,” Stewart said.
• Stat To Watch: AI-driven personalization generates 83% higher engagement rates compared to traditional content creation methods (Content Marketing Institute).
• Toolkit: Veritone Content Intelligence mines content data for insight analysis. Stringr connects data sources to AI technology that automatically generates hyperlocal animations.

4. Ethical AI Frameworks

Stewart highlighted the importance of using “trusted baseline information” as the foundation for AI-generated content. Media organizations that maintain rigorous standards for data sources will build audience trust in an era of increasing synthetic content.

• Why It Matters: 52% of news consumers in the U.S. and 63% in the U.K. are uncomfortable and distrust fully AI-driven journalism (Reuters Institute for the Study of Journalism 2024).
• Key Quote: “Our latest modules, in association with the Associated Press and Reuters, takes the whole catalog of their articles and their imagery and then allows broadcasters and publishers to come in and say, ‘Hey, I want an AP report that goes back three days that just covers climate, the environment, maybe entertainment,’” Stewart said.

5. Democratized Access To AI Tools

Scripps’ Oslund described his company’s approach of providing AI tools to all employees, not just technical teams. This “ladder down” strategy ensures that innovation can come from anywhere in the organization.

Oslund also described how “vibe coding” allows non-technical staff to create applications using natural language, dramatically reducing development costs while increasing innovation velocity.

Graham’s Newman shared how his group has taken a similar approach with its Spark platform, which has been deployed to every employee in the organization. “Anyone in our organization can actually build these [AI] apps,” he said.

This democratization has led to unexpected innovations from departments that wouldn’t traditionally be involved in technology development. As Newman explained, “It is unbelievably powerful to give our people access to be able to do this.”

• Why This Matters: Organizations that democratize AI access report higher rates of successful AI adoption compared to those that initially restrict access to AI (McKinsey Digital Transformation Survey).

6. Focus On Human-AI Collaboration

The most successful AI implementations maintain a careful balance between automation and human creativity. Our panelists all emphasized that AI should enhance rather than replace human capabilities.

Michael Vamosy, founder and chief creative officer, Defiant LA, shared how his company maintains the human element in its creative process when working with AI. Its approach to the Mike Tyson vs. Jake Paul fight promo illustrates this philosophy perfectly. Rather than generating the entire promo with AI (which often results in the “soulless” quality seen in Coca-Cola’s widely criticized AI-generated holiday ad), Defiant LA started with real humans and real environments.

This human-first approach maintained emotional connection while leveraging AI’s capabilities to enhance the visual experience.  

• Key Quote: “AI won’t replace creatives—but it will expose hacks,” Vamosy said.
• Action Item: Assign human editors to review AI outputs and establish guidelines for maintaining emotional resonance in AI-enhanced content.
• Redline: Never let the tools become the story.

Q: How Will AI Change Revenue Models?

Several new revenue streams and operational models emerged from our discussion.

1. AI Cost Management

Newman shared how Graham Media’s AI costs initially spiked as usage grew. But after implementing token optimization strategies, they were able to reduce expenses. Organizations that understand the economics of different AI models and match capabilities to needs will maintain sustainable AI operations.

• Why It Matters: Early AI adopters who failed to manage costs have seen ROI plummet; those with strong data foundations are seeing 3-5x returns on AI investments.
• Key Quote: “By just changing those models over time, we’ve been able to reduce the cost by… like one-tenth of where it’s at,” Newman said.
• Action Item: Hire an expert to conduct an AI token cost analysis across your organization and identify opportunities to optimize model selection.

2. Dynamic Sponsorships

Stewart demonstrated how Stringr’s AI-generated video content includes built-in sponsorship opportunities that can be automated. Stringr’s platform allows broadcasters to select from a library of content modules (pet adoption, stocks, real estate, news, etc.) and integrates selected sponsor logos, music and AI-voiced messaging into the AI-generated animations.

“What it’s doing is generating content very specific to an audience, like a traffic route, and then it’s automatically refreshing it,” Stewart explained. “It’s also allowing you to have an advertiser’s logo and message read aloud with the report.”

This approach creates new monetization opportunities for content that previously might not have been sponsored. The dynamic nature also means that advertisers can maintain relevance as conditions change.

• Key Quote: “A lot of creative is static… but [Stringr’s GenAI platform] allows you to bring relevance to your brand very quickly,” Stewart said.
• Stat To Watch: Brand spending on sponsored digital content in the U.S. is expected to increase by roughly 14% in 2025, reaching $9.3 billion (Statista).

3. Data Monetization Strategies

Veritone’s Cramer emphasized that “it all starts with data.” Organizations with normalized, harmonized and accurate data will have the foundation for successful AI implementation. Those without this foundation will struggle to generate meaningful insights or content.

During the session, Cramer revealed that media organizations are generating “high seven-figure deals” by licensing their content data for AI training.

• Key Quote: “We have 40 buyers of data that are using it for training… making seven-figure deals,” Cramer said.
• Action Item: Evaluate your content archives for potential licensing opportunities to AI training companies.

Q: What Immediate Steps Should Media Executives Take To Prepare For This Future?

Based on our panelists’ insights, here are some actionable recommendations:

1. Audit Your Data Infrastructure

AI tools require data. But is your organization prepared for this need? Begin by understanding what data you have, its quality and how it’s structured. This includes not just obvious content like articles and videos, but also metadata, audience information, advertising performance metrics and operational data.

Once you understand what you have, assess its quality and accessibility, and if there are gaps in your data that need to be filled.

• Why It Matters: An effective data management value chain leads to “powerful and game-changing benefits” for AI-driven companies, while data-related challenges are among the top barriers to AI initiatives (Deloitte US 2024)
• Key Quote: “In the last decade, we’ve actually ingested over 36 million hours of content on behalf of our clients,” Cramer said. “We create really high-quality metadata through this process, put it into a data lake, and now it’s feeding all of these third-party applications.”
• Action Item: Conduct a data audit across departments to identify high-value data assets that could power future AI initiatives.

2. Create AI Governance Framework

Oslund described Scripps’ four-pillar strategy that includes education/training, database connections, operational efficiencies and growth. Develop a similar comprehensive approach tailored to your organization.

• Why It Matters: Organizations with clear AI strategies are more likely to report significant value from AI implementations.
• Action Item: Schedule a cross-departmental AI strategy session to develop your organization’s AI roadmap for the next 12 months.

Trends That Will Transform Media

The media organizations that thrive won’t just be those that adopt AI, but those that implement it strategically while preserving the human elements that truly connect with audiences.

All panelists agreed that successful AI implementation requires several core elements:

• Starting with human creativity and strategic vision
• Using AI to enhance rather than replace human elements
• Ensuring emotional resonance remains the priority
• Maintaining ethical guardrails through human oversight

But the most important insight from our panel was clear: AI’s greatest value comes not from replacing human creativity, but from amplifying it. The organizations that find success will be those that embrace automation without losing the human touch that connects with audiences.

The data revolution is here. The question isn’t whether to participate — it’s how to lead.

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