How SilverTech Uses AI in Paid Media and Where We Draw the Line
By: Lindsay Moura | 12/16/25
AI is rewriting many norms, especially in the digital space. Platforms like Google, Meta, and LinkedIn are introducing new AI-driven tools that promise more scale, faster optimizations, and smarter targeting. But with those opportunities come questions around transparency, control, brand safety, and strategic alignment.
At SilverTech, our stance is simple: AI enhances good marketing, but it doesn’t replace it. We embrace AI where it adds efficiency or intelligence, and we place guardrails where it introduces risk, ambiguity, or loss of control.
Much of the focus and talk around AI these days is around SEO and GEO and how to optimize your website to appear in search results. But what isn’t being talked about enough is how AI can, should, and should not be used in your digital advertising.
AI in Paid Media: A Tool, Not a Strategy
AI within advertising channels can help expand audience reach, identify patterns humans may miss, and automate tactical optimizations. But AI models prioritize platform goals (like scale, clicks, and revenue) over business goals.
Our approach starts with strategy, including:
• Defining business KPIs
• Establishing clear audience insights
• Creating conversion-ready websites and experiences
• Layering in AI thoughtfully to extend performance, not dictate it
1. Google’s AI Max: Extending Reach, but with Caution
Recently, Google introduced AI Max, an AI-driven layer that can be activated on existing Search campaigns. When used, it widens reach, particularly through broad matches, while using signals like user intent, behavior, and context to predict the most likely converters.
Where we’re testing: Apply to strongly performing Search campaigns with clearly defined audiences and KPIs, and in non-regulated, compliance-driven industries.
What we’re watching for: Query shifts, performance quality, cost efficiency, and potential unintended reach.
Much like Performance Max in its early days, AI Max shows potential, but we view it as experimental and choose very carefully before implementing and then monitor performance closely before widespread utilization.
2. Google’s Performance Max (PMax): Expanding Visibility Powered by Automation
PMax is one of Google’s most powerful yet still mysterious campaign types. It uses Google’s AI to deliver your ads across Search, Display, YouTube, Gmail, and even Maps, automatically finding the moments people are most likely to engage with you. A new twist is emerging where PMax campaigns may appear in Google’s AI Overviews, depending on relevance and audience signals. This highlights one of the challenges of PMax and the core issue of many AI features within paid media – the placement is dictated by Google’s algorithms, not by advertisers.
According to a recent analysis published with Search Engine Land, AI Overviews are impacting visibility, but ad eligibility is still inconsistent.
Our current approach is cautious:
• Focus on precise audience signals (such as first-party lists and keywords)
• Segment campaigns by strategic intent (e.g., acquisition vs. remarketing)
• Provide creative assets that guide AI decisions
• Monitor brand safety, placements, lead quality, and costs
PMax is powerful, but by no means should be a set it and forget it tool. We use it where it adds value to broader Search or Display strategies, while keeping human control and a focus on meaningful outcomes for our clients at the center.
3. LinkedIn Accelerate: Efficient, but Limited
LinkedIn’s Accelerate campaign type uses AI to automatically create audiences, suggest ad creatives, and optimize toward objectives. It’s simple and fast to market and can enable you to reach untapped and even potentially unknown audiences, but with limited precision and even less detailed reporting.
Opportunities we are exploring: Piloting new audiences, accelerating time-to-market, and supplementing manually built campaigns.
Areas requiring caution: High-intent B2B campaigns, regulated industries, or campaigns needing granular targeting and compliance.
Where AI Fits in Our Larger Advertising Philosophy
AI is great at:
• Identifying new audiences
• Predicting conversion likelihood
• Automating bidding
• Testing creative
• Expanding reach efficiently
Humans are essential for:
• Understanding context, nuance, and brand positioning
• Interpreting results beyond platform-reported metrics and rooted in business impacts
• Ensuring messaging and audience relevance
• Ensuring brand safety and compliance
How We Protect Clients While Using AI
Our media team believes in testing AI, but only within guardrails that protect client performance and brand integrity:
Business Alignment: AI features are enabled only when aligned with measurable business goals, not vanity metrics.
Human Oversight: Every AI-driven expansion, whether targeting, placement, or creative, is reviewed for strategic fit.
Strict Guardrails: Negative keywords, custom audiences, exclusions, and other brand safety settings are continuously maintained.
Transparency: We communicate clearly about what AI is doing, where limitations exist, and what controls exist.
We expect AI will continue to take on more of the tactical workload across platforms, but advertisers who rely too heavily on automation risk reaching irrelevant audiences, lower lead quality, and wasted spend.
While we embrace AI to make campaigns smarter and more efficient, strategy and human oversight remain the drivers of our approach to performance marketing.
For more guidance on how to reduce your risk in an AI-driven landscape and ensure a sound digital marketing and media strategy, contact us for a consultation.
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Marketing