How AI Is Reshaping Media Operations: Moving Beyond Basic Automation

Media companies are quickly discovering that AI offers more than just cost-cutting potential. What began as a tool for automating repetitive tasks is now becoming essential to competitive strategy and value creation.

Jay Glavosky, SVP of Analytics at Odyssey and former Vice President of Revenue Operations at the New York Times, has spent over fifteen years in media operations and has witnessed this evolution firsthand.

This blog draws from Mediamint’s conversation with Jay Glavosky, exploring how AI’s role in media operations is evolving beyond automation into a strategic necessity.
 
Watch the full video:
 

 

The Journey: From Cost-Cutting Tool to Strategic Asset

The conversation explores three critical dimensions of AI’s transformation in media operations:

• Why AI’s role is evolving beyond simple automation and becoming a strategic necessity
• How AI agents working alongside your team are reshaping media operations and creating unprecedented competitive advantages
• A vision of the future media landscape where AI enables truly personalized, effective, and ethical advertising

According to industry research, approximately 40% of media companies are publishers using either proprietary or open stacks, with many experiencing complex, siloed workflows that delay revenue actualization. Current tools often create AI features that improve only isolated parts of the workflow rather than addressing the entire process.

“The problem is that we’re still working in silos,” explains Glavosky. “Companies implement AI solutions that solve for one particular department or function without considering the entire ecosystem.”

Part 1: Why AI Is Evolving Beyond Automation

Three Dimensions of Change: Teams, Products, and Workflows

The Limitations of First-Generation AI Implementation

The first wave of AI adoption in media focused primarily on automating routine tasks—scheduling posts, basic content moderation, and simple data analysis. While these applications delivered efficiency gains, they also revealed significant limitations.

“Initially, we were just looking to cut costs and reduce manual effort,” Glavosky notes. “But we quickly realized that the real value isn’t in replacing human work—it’s in transforming how work gets done across the entire organization.”

This realization has driven media companies to seek more sophisticated AI implementations that break down silos and create value across the entire operational chain.

Three Dimensions of Transformation: People, Products, and Process

AI’s evolution is reshaping media operations across three interconnected dimensions that together create strategic value for organizations and their clients.

“I think that there’s an opportunity to transform not only the people and how they work, but also the products and services that you provide your audience and advertisers, as well as the process itself,” Glavosky explains.

Dimension 1: Enabling Human Excellence

First is the human element. You’ll enable your people to focus on more high-value work, which will provide strategic value to your organization and clients.

Dimension 2: Innovating Products and Services

Second is product development: “AI also gives you the capability of developing new products and services, whether that’s improving the user experience through personalization or developing new ad formats or targeting. Both will increase your organization’s appeal in the ad marketplace.”

Dimension 3: Streamlining Process Workflows

The third dimension is process improvement: “And then lastly, and I think the one that comes to mind most often for people, is AI has the opportunity to automate and eliminate repetitive low value tasks which are time consuming and sometimes non-essential processes. I think this will expedite the workflow and allow you to do more and more valuable work,” notes Jay.

Part 2: Agentic AI — The Collaborative Framework Reshaping Media Operations

Strategic Partnership: AI as Collaborative Partner

The most transformative development in media operations is “agentic AI”—systems that function as collaborative partners throughout the workflow rather than just tools performing isolated tasks.

“AI agents will be co-pilots throughout the entire workflow,” Glavosky explains. “I can’t think of a point in which AI agents aren’t additive to your organization’s workflow, whether that’s media planning, ad operations, or reporting and insights.”

This co-pilot approach represents a fundamental shift in how AI delivers value. Rather than simply automating isolated tasks, AI agents work alongside media professionals, enhancing capabilities and enabling more strategic focus.

“If you partner AI with your talented individuals, I think you’ll get the most value,” Glavosky notes. “It’s about amplification, not replacement.”

Breaking Down Organizational Silos

As AI becomes more deeply integrated into media operations, traditional departmental boundaries are dissolving. Glavosky recommends a systematic approach to this organizational transformation.

“Look very deeply at every step of your workflow, the roles and responsibilities around it, and identify places that can be improved or redesigned,” he advises. “There are parts of the workflow that can benefit from agentic AI throughout, allowing for more strategic focus in other areas.”

Role-Specific AI Transformations Across the Media Value Chain

Based on the challenges facing current media operations teams, AI-powered solutions can enhance each role in different ways:

Media Planning: Strategic Focus

Media planners currently analyze inventory performance, update forecasts, and design packages tailored for advertisers. AI-driven media plans and product recommendations can optimize these offerings, allowing planners to focus on strategy and client relationships.

Ad Trafficking: Error Reduction and Acceleration

Ad traffickers configure campaigns, upload creatives, conduct QA testing, and monitor performance. AI-powered QA and compliance tools can automate ad tag checks, reduce errors, and accelerate campaign launches, freeing traffickers to focus on more complex issues.

Campaign Management: Predictive Intelligence

Campaign managers configure campaigns in internal systems, monitor pacing and performance metrics, and troubleshoot execution issues. Predictive campaign analytics can forecast performance, optimize budgets, and drive better outcomes.

Account Management: Data-Backed Client Service

Account managers engage in client communications, review performance data, and propose enhancements. AI insights can help identify opportunities and deliver data-backed recommendations that improve client satisfaction.

Part 3: The Future Media Landscape — Personalized, Effective, Ethical

The Evolution of AI: From Automation to Decision Support

The next phase of AI in media will focus less on simple task automation and more on enhancing decision quality, according to Glavosky.

“I think AI will move from just like task automation where, you know, you just have efficiency by automating things to really enhance your decision and the quality of the decisions you’re making.” he explains.

“Right now we’re in a nascent period of time around adoption, around AI solutions, and we see them as tools,” Glavosky continues. “I think that will transform into solutions that will help you make better quality decisions, will help you prioritize, help you identify what your workload should be, what you should do next, what are the priorities for that day, quarter, and year.”

This evolution from automation to decision support represents a significant maturation in how AI delivers value to media organizations.

The Future: Agent-to-Agent Collaboration

Glavosky also envisions a future where AI systems work together across traditional boundaries.

“It will transform from being modular and role centric to agent-to-agent collaboration,” he predicts.

“While role-centric and modular approaches are crucial now, we can’t keep operating in silos. The agents need to collaborate just like we do with our stakeholders every single day. That will unlock the most value.”

This interconnected approach could transform how media operations function, particularly given the complex, siloed workflows that currently delay revenue actualization for many publishers.

Strategic Implementation: Finding Value in Underinvested Areas

One of Glavosky’s strategic insights is the opportunity to apply AI in underserved areas of media operations.

“Deploy AI in high impact areas,” he recommends. “There are lots of underrepresentative, underinvested areas that have an opportunity to improve substantially and focus on where you’re going to redeploy those sets or resources into more high value work and strategic roles.”

By identifying these overlooked areas and applying AI solutions strategically, media organizations can achieve meaningful improvements in efficiency and effectiveness while differentiating themselves from competitors.

The Path Forward: Top Three Strategies for Media Companies

For media organizations looking to stay ahead in this shifting landscape, Glavosky offers three straightforward recommendations:

1. Embrace AI: Accept the Future

“The first one’s really simple. Embrace it. Accept that this is the future. Don’t fight it,” he advises. “You will be way behind your competition. You will provide less adequate solutions for your clients.”

“I think it’s very interesting that AI is one of the most advanced technologies that have… human mankind has ever built, but also one of the most approachable ones,” Glavosky adds. “We all can go in and play and test with and improve our output just by using a major, you know, LLM and AI solution.”

2. Target high-friction tasks: Quick Wins

“The second would be to identify high friction, repetitive tasks across all of your key roles,” Glavosky says. “That is really important. That’s where I think we are all obviously seeing the first steps of improvement and impact.”

This pragmatic approach allows organizations to achieve quick wins while building momentum for broader transformation. Forrester research indicates media professionals spend roughly a third of their time on tasks that could be automated or enhanced by AI—representing a substantial opportunity for efficiency gains.

3. Focus on high-impact areas

“And then the last one is to deploy AI in high impact areas,” notes Glavosky. “You know, there are lots of underrepresentative, underinvested areas that have an opportunity to improve substantially and focus on where you’re going to redeploy those sets or resources into more high value work and strategic roles.”

The Reuters Institute found that media organizations taking this targeted approach to AI deployment saw 27% better performance indicators than those implementing without clear strategic focus.

The Human Element: Central to Success

Despite the focus on technology, Glavosky consistently emphasizes that human talent remains central to successful AI integration.

“I also think that AI and infusing it into your organization, whether that just be initial testing or really deeply adopting it and putting it through the entire workflow, that it’s really important to partner that with your talented team members,” he explains.

“And so if you partner that AI with those talented individuals, I think you’ll get the most value there,” Glavosky adds.

The Vision: Personalized, Effective, Ethical Advertising

The ultimate promise of AI in media operations is a future where advertising becomes more personalized, effective, and ethical—benefiting both media companies and consumers.

“When AI is properly integrated across the entire workflow, we can deliver advertising experiences that are genuinely useful to consumers,” Glavosky explains. “We move from interruption-based advertising to advertising that feels more like a service—relevant, timely, and valuable.”

This vision represents the culmination of AI’s transformation from cost-cutting tool to strategic asset:

• For consumers: More relevant, less intrusive advertising experiences
• For advertisers: Higher engagement, better ROI, and stronger brand relationships
• For media companies: More valuable inventory, increased revenue, and sustainable business models

The Cost of Waiting

Glavosky’s message to hesitant media companies: the time to act is now.

“I think my last thoughts would be like, you gotta do it. Get on it. If you’re not doing it, you’re not investing, you’re not experimenting, you’re not reading up on it, you are going to be left behind,” he warns.

“And there is an opportunity to accelerate your business and improve the day-to-day working lives of your people and offer unique things to your clients. Who doesn’t want those three things?”

He encourages media companies to adopt a mindset of curiosity and experimentation: “So I think that the most important thing here is be curious and go out and start testing and accept that this is the way of the future. And there’s an opportunity for you to improve your business.”

The media organizations that will thrive are those viewing AI not as just another technology trend but as a core strategic capability that can transform how they deliver value to audiences and advertisers.