Jan 19, 2026
Why has ad creative volume increased in recent years?
Marketing hasn’t gotten easier, it’s gotten faster and more fragmented. Retailers, brands, marketplaces, and agencies now operate in a world of:
dozens of channels
hundreds of formats
thousands of variants
continuous localization + personalization
Campaigns are no longer “launched”, they’re maintained and iterated across paid social, retail media networks (RMNs), display networks, product display pages (PDP), connected TV (CTV), and digital out-of-home (DOOH). High-frequency advertising demands high-frequency creative without sacrificing quality. And that’s where the system breaks.
Most creative workflows still depend on:
manual resizing
repetitive copy swaps
legal and compliance cycles
product and market localization
platform formatting
multi-stakeholder approvals
These are not storytelling tasks. They’re operational tasks. And until now, they’ve required people to push pixels, update copy, click software, and export assets over and over again.
What is the benefit of getting creative assets at scale?
Once creative production becomes automated, three performance levers open up:
Experimentation velocity - You can run more tests, faster, without buying more capacity.
Personalization at scale - You can tailor to channels, SKUs, segments, markets, and seasons.
Cost efficiency - Headcount no longer scales linearly with creative volume.
Creative stops being the constraint on media. It becomes the multiplier.
Why is Generative AI not helpful for creating ad assets?
The first wave of Generative AI was thrilling but incomplete and inadequate for driving sales. It produced novel content (images, videos, copy) but it did not produce production-ready ad assets.
Brands need:
accuracy of SKUs, claims, dates, CTAs
compliance
visual and tonal brand integrity
channel formatting
Raw GenAI models don’t understand those constraints. They hallucinate. They lack guardrails. They produce content, not campaigns. They create assets, not outcomes.
Which leads to the next leap.
How does Agentic AI work in advertising?
Agentic AI combines Generative AI and traditional software. Where Generative AI responded to prompts, Agentic AI responds to briefs and objectives, executing multi-step workflows traditionally handled by humans.
In creative production, that means AI Agents can:
→ Ingest content + SKUs + brand rules
→ Generate master assets + variants
→ Resize for dozens of formats
→ Localize for markets + languages
→ Apply compliance + brand checks
→ Export production-ready assets
The difference is profound: GenAI outputs assets. Agentic AI outputs campaigns.
What role do humans play in the process?
Enterprise advertising carries reputational, legal, and brand risk. That’s why the future isn’t autonomous replacement but rather a hybrid orchestration. In Rocketium’s model, humans are still central but used differently:
They don’t operate the software
They supervise the Agents
They govern the brand
They make creative decisions
They tune for business outcomes
Machines handle throughput. Humans handle judgment. This is exactly how high-leverage industries adopt automation; not by eliminating expertise, but by eliminating drudgery.
Why is this the end of traditional SaaS?
For 20 years, SaaS scaled by letting humans operate software instead of agencies or back offices. But that model contains a hidden cost: every new tool implies new human labor to operate and integrate it.
As Rocketium’s CEO, Satej Sirur, recently noted in reference to Marc Benioff, the next era will not be defined by new SaaS applications. It will be defined by AI Agents that leverage software instead of humans. In this model:
People don’t click software to complete tasks.
AI Agents click software on behalf of people.
This unlocks the step change SaaS never delivered:
workflow without operators
execution without tickets
throughput without headcount
automation without training
interfaces without traditional “users”
Traditional SaaS digitized tasks. Agentic systems will automate them.
How do creative operations look in the future?
The shift underway looks like this:
Yesterday: People → use SaaS → create assets
Today: People + AI → create assets faster
Tomorrow: AI Agents → use software → create assets. People → direct strategy + supervise
This is not incremental evolution, it’s a new production paradigm.
Rocketium’s AI Studio operationalizes this hybrid model for brands, retailers, marketplaces, and agencies by combining:
Agentic AI for scaling and execution
Experts-in-the-loop for tuning and QA
CreativeOps software for collaboration and approvals
The result: brands can go from brief + key visual → on-brand assets for every channel in minutes, not weeks.
And critically: without sacrificing brand safety, output quality, or creative integrity.
Agentic AI turns creative from a manual workflow into an automated growth engine. The brands that adopt it will win on speed, personalization, and cost - the dominant levers of modern advertising.
