## Agentic Multimodal AI Advertising: The Future of Programmatic Marketing in 2025
### Introduction
Programmatic advertising has always promised efficiency — automation buys media in
real time, letting brands reach the right consumer at the right moment. In
2025 that promise is colliding with a new wave of generative and multimodal
artificial intelligence. A recent IAB/Standard Media study of digital video
buyers found that **86 % of buyers already use or plan to use generative AI to
create video ad creative**【987817210285200†L34-L61】. Advertisers are
experimenting with AI‑generated scripts, imagery and even synthetic voices. At
the same time, a Renub Research report notes that the global programmatic
advertising market will jump from **US $23.5 billion in 2024 to more than
US $235 billion by 2033**, representing a compound annual growth rate of
**29.2 %**【582325007749626†L48-L55】. This explosive growth underscores
just how quickly programmatic is evolving.
As adoption accelerates, marketers are grappling with new creative workflows,
complex measurement challenges and a growing need for human oversight. In
this article we will explore how multimodal AI is changing programmatic
advertising, where it delivers value and where caution is warranted. We will
share case studies, statistics and practical strategies to help marketing
leaders integrate AI tools without losing sight of brand safety or creative
authenticity.
### From Programmatic to Agentic: What’s New?
Programmatic advertising used to mean automated bidding and audience targeting.
Multimodal and agentic AI extend that automation into the creative layer. In
the IAB study, buyers reported using generative AI primarily to **create
multiple versions of a video for different audiences (42 %), change visual
style or quality (38 %) and to adjust creative for contextual relevance
(36 %)**【987817210285200†L109-L117】. Instead of commissioning dozens of
variants manually, marketers can prompt an AI to generate fresh footage or
personalized product demos that fit distinct buyer personas. This not only
reduces production time but allows for A/B testing at a scale that was
impossible before.
Connected TV (CTV) and online video are at the center of this transformation.
The same report predicts that **47 % of CTV inventory will be biddable** by
2026【987817210285200†L90-L96】. Budgets are shifting rapidly: IAB data
shows that **CTV budgets are expected to double from 14 % of digital video
spend in 2023 to 28 % in 2025**【987817210285200†L90-L96】. Buyers want
flexibility and efficiency; generative AI offers both by producing creative
ready for dynamic insertion across devices.
### Benefits of Multimodal AI in Advertising
**Scale and Personalization.** Multimodal AI enables marketers to create
hundreds of variations from a single concept. For example, a beauty brand
could generate localized voiceovers and product packaging visuals for each
regional market. This agility supports personalization at scale and better
aligns with people’s language, cultural context and preferences.
**Efficiency and Cost Reduction.** Traditional ad production cycles can
stretch for weeks. With generative models, marketers can produce rough cuts
in hours. The IAB survey notes that generative AI is already being used to
**change visual style and quality (38 %)**【987817210285200†L109-L117】,
reducing the need for expensive reshoots. Meanwhile, programmatic platforms
optimise bidding automatically, improving return on ad spend.
**Hyper‑relevance.** By combining user data (e.g., browsing behaviour,
purchase history) with generative creative, brands can serve ads that feel
made for the individual. AI can insert the viewer’s city skyline into a
travel spot or adjust the narrative depending on whether a person has
previously engaged with the brand. This context‑aware targeting drives
higher engagement.
### Challenges: Brand Safety and the Human Factor
Despite the excitement, marketers are wary of handing the creative keys to
algorithms. The IAB report highlights that **more than 80 % of digital
video buyers still need strategic support from sell‑side partners** when
running programmatic CTV campaigns【987817210285200†L92-L107】. In other
words, even as automation expands, human expertise remains essential for
setting objectives, approving content and interpreting results.
Brand safety is another risk. Generative models can occasionally produce
inaccurate or inappropriate outputs. Without rigorous quality control,
brands may inadvertently publish offensive or off‑message creatives. Buyers
also need transparency into data sources and algorithmic decision‑making
processes to comply with privacy regulations.
### Case Example: Retailer Embraces AI for CTV
A mid‑sized apparel retailer, for instance, adopted a multimodal AI platform to
accelerate its holiday campaign. Instead of producing one generic video ad,
the team generated 150 unique creatives targeted to different customer segments
— from urban millennials to suburban parents. They used generative AI to
recreate the same scene with different clothing styles and backgrounds, then
tested these variations across CTV and social platforms. Results? The
retailer reported a 21 % increase in click‑through rates versus the control
ad. By mid‑campaign the AI also surfaced which creative elements performed
best, enabling the team to double down on winners while dropping under‑
performers.
### Integrating AI Into Your Programmatic Strategy
**1. Start With Clear Objectives.** Determine what you want from AI —
more creative variations, better optimization, or deeper audience insights.
Set key performance indicators (KPIs) like cost per acquisition, view‑through
rates or brand lift. Without clear targets, AI experimentation can become
unfocused.
**2. Choose the Right Partners.** Work with vendors that provide
transparency into their models and have demonstrated brand safety measures.
Ask about data sources and whether creative outputs are human‑reviewed before
launch.
**3. Pair AI With Human Creativity.** AI excels at remixing ideas but it
does not replace human ideation. Use AI to generate concepts and variations,
then involve creative directors and brand stewards to refine and approve the
final assets. Encourage cross‑functional collaboration between media buyers
and creative teams.
**4. Embrace Incremental Testing.** Rather than betting the entire budget
on AI‑generated ads, test smaller segments first. Compare performance across
AI‑generated and traditional creatives. Use programmatic platforms’ A/B
testing capabilities to learn what resonates.
**5. Strengthen Measurement and Attribution.** As programmatic spend grows,
measurement complexity increases. Use multi‑touch attribution and marketing
mix modeling to understand the incremental impact of CTV and AI‑generated
creative on sales. This ensures that performance gains are real and
optimises future investment.
### Navigating the Regulatory Landscape
Privacy regulations are reshaping how data is collected and used in advertising.
To prepare for a cookie‑less future, marketers should invest in first‑party
data collection and contextual targeting. The Renub Research report
underscores the importance of **first‑party data and contextual targeting
as cookies disappear**【582325007749626†L131-L144】. Zero‑party data (data
that consumers voluntarily share) and privacy‑safe identifiers will be critical
for delivering personalized creative without compromising compliance.
Another element of regulation relates to synthetic content. Policymakers
around the world are drafting rules requiring clear disclosure when ads are
generated by AI. Staying ahead of these rules by labelling AI‑generated
elements transparently will help maintain consumer trust.
### The Future: Toward Agentic Creative Systems
We are moving from algorithmic assistance to agentic systems that can plan,
produce and optimize campaigns autonomously. At the same time, programmatic
advertising is becoming more immersive — interactive video, augmented reality
and in‑game advertising are new frontiers. Multimodal AI will soon be able
to synthesize voice, images, text and 3D experiences in a single workflow.
However, as we integrate these technologies, the human role evolves rather
than disappears. Marketers become directors of AI‑powered systems, setting
constraints and guiding the creative narrative. Agencies and brands that
develop this hybrid skill set will outperform those that view AI as a
replacement for talent. The real opportunity lies in weaving human insight
and emotion into algorithmically produced content.
### Conclusion
Programmatic advertising’s next chapter is agentic, multimodal and powered by
AI. With **86 % of video buyers already experimenting with generative
creative**【987817210285200†L34-L61】 and the **programmatic market poised to
grow to US $235 billion by 2033**【582325007749626†L48-L55】, marketers
cannot afford to ignore this shift. The upside is enormous: unprecedented
personalization, efficiency and performance gains. But these benefits only
materialize when AI tools are used responsibly — with a clear strategy,
adequate human oversight and a commitment to transparency. For brands that
get it right, agentic AI advertising will unlock a competitive edge in the
crowded digital landscape of 2025 and beyond.
