Automated media buying has changed almost every part of how campaigns get planned, priced, and delivered. Programmatic advertising and real-time bidding now move faster than any human could, and machine learning models decide which ad space and ad inventory fit a brand in milliseconds.

Will AI replace media buyers and turn paid advertising automation into the whole job? Not at all, because the parts of this job that actually move a client's business rarely show up in a dashboard.

In this episode of AdTech Heroes, I sat down with Sascha Lock, Executive Director, SVP of Integrated Investment at Hearts & Science, to talk about what automation has genuinely changed in media buying, what it hasn't touched, and why the agencies that win are the ones who treat data-driven tools as a starting point rather than the whole answer.

Key Takeaways

• Automated media buying has made the buying process faster, but it hasn't replaced the relationship-driven work that determines whether a campaign succeeds.
• AI in advertising is following the same path mobile did: it will keep growing until it stops being a separate conversation and simply becomes how digital advertising works.
• Programmatic advertising and first-party data give agencies more signal, but clients still need a human point of view to translate that signal into a decision.
• Real-time bidding has automated pricing, shifting negotiation from "what's the best price" to "what's the best strategic partnership."
• The most valuable habit in media buying right now is filtering. There's more data and more platforms than any one person can track.

Why Automated Media Buying Still Needs a Human at the Center

Ask most people what an "investment" role in media buying actually involves, and they'll picture spreadsheets and numbers moving between columns. Lock pushed back on that idea early in our conversation. His role, he explained, is much more about relationship capital than transaction management.

That distinction matters more as automation takes over the mechanical parts of the buying process. When machine learning and buying platforms handle pricing and placement, the value an agency brings shifts toward judgment: knowing which of the thousands of available options actually fits a client's goals, and being willing to say so.

Lock compared it to any real relationship, built on direct but kind communication and consistency. Automated media buying can optimize an auction. It can't build that trust on its own.

‍ "The actual product isn't everything. You're buying service, and you're buying commitment, and you're buying this mutual strive to do better and to grow together."

Will AI Replace Media Buyers? Not Anytime Soon, Because Context Still Matters

Lock drew a comparison that's hard to argue with. Mobile advertising, he pointed out, used to get its own line item on every media plan. Eventually it stopped being a special category and simply became how advertising works.

He believes artificial intelligence is on the same track. Right now, AI in advertising gets a dedicated conversation on nearly every panel and podcast. Eventually, it will stop being a separate topic and just become the infrastructure underneath everything, the same way connectivity and speed are for the internet today.

That's a useful way to think about whether AI replaces media buyers and paid advertising automation makes the role obsolete. History in this industry tends to be cyclical. Each wave feels revolutionary in the moment, but what people actually need from a partner changes far more slowly than the tools do.

How Programmatic Advertising and First-Party Data Are Reshaping Client Conversations

With hundreds of CTV platforms and thousands of potential partners now available in the US alone, no single person can be an expert on everything. Lock described his role as a connector: someone who listens to every new product release, filters out what's genuinely relevant, and brings a clear point of view to the client.

That filtering depends on data, but the decision itself still depends on people. Clients see the same headlines about programmatic advertising and first-party data that agencies do. What they need isn't more information. It's a trusted read on what that information means for their business, and someone willing to make a recommendation rather than just present options.

From Transactional to Strategic: How Real-Time Bidding Changed Negotiation

Real-time bidding automated a huge part of what negotiation used to mean. Ask a newcomer to define negotiation, Lock said, and they'll usually describe getting the best price. That's still true, and it still matters.

But once pricing and inventory decisions run through an algorithm, the conversation left for humans is a different one. It's less about the number on a line item and more about building something together: better flexibility, stronger strategic terms, and closer collaboration between everyone at the table. 

Some of the most productive moments, Lock noted, still come from putting the right minds from a media partner, a client, and an agency in the same room to work through a problem together.

What a Strong, Data-Driven Buying Process Actually Looks Like

When I asked Lock what a strong modern media partnership requires, he didn't point to a platform. He pointed to three habits: transparency, accountability, and speed.

Transparency means being upfront when something goes wrong, not just when it goes right. Accountability means showing up when you say you will, and explaining clearly when you can't. Speed means pivoting quickly once the data shows something isn't working, rather than over-analyzing a decision that's already clear.

The Two Questions Every Agency Should Be Asking Clients Right Now

Lock narrowed the most important client conversations down to two questions. The first is simple to ask and hard to answer well: what does success actually look like, and what sources of truth will we agree to measure it by?

The second is about risk tolerance. Our guest described a rough 70/20/10 framework many teams use: most investment into what's already proven, a portion into promising opportunities, and a smaller share for bolder tests. That last bucket should expand or shrink with how much risk a client can absorb, and it's worth revisiting often.

Getting clear on goals and risk tolerance matters more than any new platform. It's the foundation everything else in the buying process gets built on.

Toward the end of our conversation, I asked Lock what superpower he'd want in ad tech. His answer was "Mr. Transparency": the ability to see exactly what an algorithm is doing and why, not to fight the technology, but to bring that insight back into planning. It's a fitting note to end on. The tools keep getting faster. What agencies bring to the table is still deciding what that speed should be used for.

You can watch the full conversation with Sascha Lock above.