What the Evolution of AI Is Exposing in Paid Media

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Here’s why marketing leaders must shift from AI adoption to orchestration and fulfilling the demand that AI earns its keep.

AI adoption is no longer the challenge in the marketing world. The landscape has now arrived at the point of diminishing returns. More tools don’t equal more value.  As marketing leaders have standardized AI across tech stacks, media channels and creative workflows, the cracks have also started to appear: campaign fragmentation, over reactive teams and metrics that don’t support revenue.

The AI revolution isn’t about the latest or greatest tool anymore. It’s about what it’s amplifying for better or worse. Here’s what AI is exposing in paid media today, and how leading brands are closing the gap between performance and accountability.

TL;DR – AI Is Reshaping in Paid Media

  • AI is now an expected budget line item. And its performance is non-negotiable. Your CFO and stakeholders don’t necessarily care about the latest AI tool you’re leveraging for marketing efforts. Instead, they’re focused on the performance it’s driving. If AI tools are not eliminating waste, improving productivity, driving efficiency or supporting revenue, it‘s now a legitimate distraction toward larger business initiatives.

  • Most marketing and media teams are stuck in adoption mode. GenAI is still buzzing across the industry; consequently, marketing teams are using it with bullish enthusiasm but with considerable potential risk. Most organizations are not implementing shared KPIs, creative quality assurance, media integration or accountability. As a result, many are in a tech stack slump, feeding the potential for misalignment, missed opportunities and competitive setbacks.

  • AI is exposing the disconnection between creative and media. While creative assets are being produced faster than ever with the help of AI, so is the waste. Between soulless GenAI creative and lack of human oversight, only creative informed by real-time media signals can mitigate the risk.

  • Buyer discovery is now driven by GenAI, LLMs and platform summaries. From ChatGPT and Gemini to G2, including transitional search platforms now summarizing content,  AI has undeniably transformed the customer journey regarding how and where buyers discover solutions. They’re reaching decisions faster than ever, with fewer clicks. If your brand isn’t structured for GenAI and LLM visibility, you’re not ranking in today’s shrinking shortlist.

  • Broad match is revealing AI strategy readiness. No longer a simple keyword tactic, broad match is a predictive engine powered by AI. However, a lack of strategic human oversight can amplify not just reach but campaign fragmentation, disconnected conversion goals, and poor data input. 

Proving AI Drives Business Outcomes

In leading today’s marketing organization, AI has become a staple in the tech stack, especially across paid media.

However, there’s a growing demand to understand how technology, including AI, drives real business impact. Statistics show that marketing leadership is intensely focused on making AI earn its keep. 

According to G2’s 2025 Buyer Behavior Report:

  • 49.5% of enterprise buyers switched vendors last year for better AI functionality
  • 88% of power users are willing to pay a premium price tag for AI, but only if it drives value
Source: G2 2025 Buyer Behavior Report
Source: G2 2025 Buyer Behavior Report

AI is no longer a shiny object. Its functionality is expected, and like any marketing efforts, ROI determination is paramount. That means the marketing landscape is now beyond adoption metrics and turning to business-level KPIs, such as funnel velocity, revenue lift, operational efficiency and CAC reduction.

Without a strategy, AI investments can quickly become overhead instead of a business outcome driver. 

For instance, when creative and media teams run their experiments solely with AI, performance falls through the cracks. Brought-on AI tools quickly multiply, including their cost, instead of clear ROI. Costs can creep through overlapping subscriptions, duplicate efforts, fragmented data, premium upgrades and time spent.

Then, CMOs are called back to the C-suite to justify the budget against business outcomes. Decisive execution surrounding AI implementation is paramount. If not, it becomes an elusive cost and sometimes a liability.

AI deployment statistics:

  • Deploying generative AI models costs businesses on average $5 million to $20 million (Gartner)
  • 30% GenAI projects will be abandoned after proof of concept by 2025 (Gartner)
  • 74% of companies struggle to achieve and scale value with AI Adoption (Boston Consulting Group)

What this looks like in paid media:

  • Creative teams are scaling content with Gen AI, but skipping QA
  • Media teams are launching AI-managed campaigns without performance signals or quality data inputs
  • Automating workflows without insight ownership, leaving findings on the table


What’s at stake:
 

Disconnected AI tools without strategy, oversight and clarity mean a faster, more efficient mess.

Mishaps compound quickly in this tech-assisted world, putting brand credibility, performance and budget at risk. Don’t make AI a quicker way to fail.

AI Has Changed Buyer Discovery and Purchase Decisions

Search engines and sales teams’ output no longer dominate buyer discovery. In case you missed it, this process is now happening in AI frameworks and systems: LLM, review sites and AI content summaries across traditional search.

According to the G2 2025 Report:

  • Software review websites and AI search now rival or exceed Google for initial discovery.
  • Enterprise buyers see review content as more trustworthy than actual vendor websites


Now, more than ever, if your content isn’t structured for LLMs or indexed properly in GenAI tools like ChatGPT, Gemini or Perplexity, you’re not visible to buyers. Showing up in search results isn’t the prime objective anymore. It’s also about showing up in
answers to prompts.

For marketing leaders, this changes the playbook:

  • Traditional SEO no longer secures early-stage visibility
  • Ungated PDFs won’t get crawled
  • Blog content without schema or source links won’t get surfaced


Brands must build structured content ecosystems that include:

  • Schema-enabled landing pages to support structured snippets
  • Frequent evaluations of site strategies on platforms like G2 and Trustpilot, which are often sourced by LLMs
  • Internal linking processes with well-cited sources to ensure content is LLM-readable and discoverable


If you’re not visible in AI-generated summaries, it’s a lost opportunity to strengthen your likelihood of being in the consideration set.

Before you write off AI-powered discovery as just an SEO concern, you must understand it’s a visibility issue that directly impacts paid media performance. From brand searches to top-of-funnel searches, your paid media campaigns only work optimally if customers can discover you across the places they trust: GenAI platforms, review sites and AI-powered search results.

Leverage this checklist below to assess whether your content, creative, and media foundation are aligned with today’s evolving buyer and search discovery landscape. Use it to identify and close gaps quickly.

What AI-Powered Broad Match Is Exposing in Search Advertising

The rise of GenAI and AI-powered buyer discovery has transformed traditional search advertising. In fact, Google Marketing Live’s updates revealed how AI is driving keyword-less optimization. 

Once largely deemed ineffective for being too general, Google’s broad match has become a predictive engine fueled by real-time signals, behavioral intent and audience targeting. With the buyer discovery shift toward LLMs like ChatGPT, Gemini and Perplexity, many markets are wondering:

Is Google Search still relevant today?

The answer is yes. Search isn’t dead. The strategy is evolving.

Broad match still plays a critical role in bottom-of-funnel capture, assisting brands in capturing high-intent customers.  If marketers aren’t properly managing AI inputs, broad match doesn’t just expand reach, it can expose these common blind spots:

  • Disconnected conversion goals
  • Missing first-party data signals
  • Poor negative keyword strategy
  • Fragmented campaigns
  • Creative misalignment


Broad match is the litmus test of AI readiness, not just targeting, in a post-keyword landscape. It indicates how well your brand can interpret, align and act on intent signals across fragmented buyer journeys and before your competitors win the zero-click, AI-generated  answer.

Marketer leaders aren’t ditching search just yet. They’re actually doubling down on high-intent keywords, better creative and AI optimized performance structures. 

Search is still very much the moment of truth where buyer intent meets decision. Broad match with the rise of AI just shows if you’re built to convert it. 

Marketing Teams Are Still in AI "Adoption Mode"

Closed Loop has seen the following too many times across multiple B2B brands:

  • Creative teams experiment with GenAI to scale variations, but skip QA
  • Teams use AI to summarize content, but those insights aren’t fed back into performance planning
  • Media teams automate bidding, but ignore data signals like offline conversions.

And what’s the common denominator? Teams are efficiently  “doing AI” in silos.

Here’s a framework that illustrates a paid media team’s AI posture in phases:

Right now, most brands are floating between adoption and alignment. And it’s understandable with the relative age of the AI era. This purgatory feels like progress, but lacks structure, accountability and direct business outcome alignment. 

"Using AI for campaign optimization is more than just hitting a switch. It takes a deep understanding of data and how AI performs to get optimal results."

Inside the Top Paid Media AI Strategies

At Closed Loop, we don’t chase AI trends or the gold rush. For years, we’ve been integrating AI where it earns its keep — multiplying strategic effort, improving media performance and creating capacity.

Here’s what mature paid media teams are doing with AI:

1. Forecasting before spending

Instead of reallocating budget reactively, our paid media experts use predictive modeling to simulate outcomes across funnel stages and business units before launch.

2. Implementing creative to scale without sacrificing control

We use GenAI tools like Firefly, Canva, Adobe and Claude to draft scripts, generate visual enhancements and build modular creative packages.

But that output never goes live without:

  • QA checkpoints
  • Funnel-stage alignment
  • Creative insights tied to media signals

3. Real-time optimization

We monitor campaign performance in real-time and use AI to adjust:

  • Budget by funnel performance
  • Creative by audience engagement
  • Campaign structure based on signal strength


Iteration at this granular level helps our partners stay agile without losing sight of long-term performance goals.

Curious about our AI tech stack? Check it out below:

With our proprietary data solution Forager, Closed Loop also connects creative, media and performance signals in real-time, ensuring AI-powered insights from tools and platforms are actionable and driving business outcomes. Forager enables us to monitor creative impact at the asset level, correlate performance trends across campaigns and align media investments with funnel progression.

The Takeaway: AI Isn’t a Strategy. It’s a Multiplier.

It’s not about adding another shiny AI tool in today’s marketing landscape. You need strategic orchestration that drives AI investment.

AI can drive efficiency and business outcomes. However, it’s only achievable if brands and marketing leaders integrate it within the proper processes and systems it needs to thrive. AI efficiency calls for alignment across teams, media and creative and clear KPIs.

The real test of AI isn’t what it creates or optimizes. It’s what it returns to the bottom line.

What’s Next for Marketing Leaders After AI Adoption

  1. Audit your AI tech stack by output, not usage
    Think about which tools are driving and delivering measurable impact to your business. Which tools are nice but don’t have much of a business effect? Remember, adoption is expected in this climate. It’s time to be obsessed with attribution and C-suite-ready results.

  2. Structure your funnel for buyer discovery today
    It’s time to update your content and site architecture for LLM visibility. You’re already falling behind in this competitive market if you’re not appearing in the GenAI search.

  3. Align your marketing teams under shared KPIs
    AI’s full potential is achieved when media, creative, and data work toward the same metrics tied to direct business outcomes. Remember, marketing is moving beyond vanity metrics.

  4. Don’t let the strategy slip with your automation
    AI is here to eliminate inefficiencies, not human instincts. More productivity and speed are gifts to marketing leaders. But they only provide real value with strategy and good intentions.

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