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- Why many brands hold back on AI for influencer programs
- How brands exploit AI to profile customers and scale campaigns
- Creators are adopting AI tools to find deals and streamline workflow
- CTV adoption lags behind social and retail channels
- Platforms, tools and technical limits shaping AI for streaming ads
Marketers are testing AI across ad channels, but its adoption is uneven. While social and retail media are moving fast, influencer campaigns and connected-TV remain more cautious. New survey data and industry experiments reveal why brands are selective and how tools are starting to reshape creative workflows.
Why many brands hold back on AI for influencer programs
Only a minority of marketers have welcomed AI into influencer work. A recent industry survey found that just 25% of marketers report using AI when running creator campaigns.
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Trust and authenticity are core reasons for the hesitation. Research from the World Federation of Advertisers shows most brands wary of virtual influencers cite consumer skepticism.
- Virtual influencers are fully generated avatars controlled by teams behind the scenes.
- These AI-driven personas can look and sound lifelike, but many brands fear audiences will reject them.
- Viral examples, like a Wimbledon-themed post from a virtual creator, highlight the creative potential — and the reputational risk.
Among the subset who do use AI for influencer work, the main applications break down into clear tasks.
- 75% use AI to analyze campaign and audience data.
- 63% use AI tools to generate creative content.
- 56% deploy AI for outreach and matching with creators.
How brands exploit AI to profile customers and scale campaigns
Some companies are blending first-party data with generative models to reshape targeting and messaging.
For example, a mid-size skincare brand partnered with an AI analytics firm to feed CRM and e-commerce signals into large language models. The outcome was a set of refined customer segments that now guide product copy and campaign targeting.
Agencies and platforms are also bringing AI into talent discovery. One influencer agency uses models that match campaign briefs to creator profiles. The system simulates likely engagement based on historic performance to estimate return on ad spend.
- AI can rapidly sort thousands of creators against campaign goals.
- Modelled predictions help advertisers decide which creators to scale.
- Automation becomes essential as brands work with larger pools of micro- and mid-tier creators.
Creators are adopting AI tools to find deals and streamline workflow
Influencers themselves are increasingly using automation to manage content and business asks. Industry reports say roughly 80% of creators integrate AI somewhere in their content process.
New creator platforms aim to be autonomous assistants. One commerce app released an “agentic” feature that scans a creator’s inboxes and DMs to flag brand offers and estimate commercial value. The tool can identify whether a message comes from a brand, gauge the potential budget, and surface opportunities.
- Automated DM triage to spot sponsorships.
- Content generation and idea prompts to speed production.
- Revenue discovery tools to highlight monetizable interactions.
Platform founders say many creators feel overwhelmed by volume and miss a large share of inbound opportunities. AI aims to reduce that friction and increase conversion of outreach into paid work.
CTV adoption lags behind social and retail channels
When it comes to streaming and connected-TV, AI use is still limited. In the same survey, a large majority — 82% of marketers — said they do not apply AI in their CTV campaigns.
By contrast, nearly half of marketers reported AI use in social media, and over two in five said the same for retail media.
- Social media: ~49% using AI.
- Retail media: ~42% using AI.
- CTV: only ~18% report active AI use.
One executive notes this gap stems from the historical nature of TV. Traditional TV was built for broad reach, not granular data-led targeting. Streaming is changing that, but the shift is gradual.
Where AI does appear in CTV, it is primarily focused on targeting and creative support. Among marketers who use AI on streaming:
- 69% apply it to analyze audience and performance data.
- 54% use it to generate creative assets.
- 54% use it to automate media buying and placements.
Platforms, tools and technical limits shaping AI for streaming ads
Large ad platforms are rolling out AI suites that combine creative generation with media optimization. For instance, one retailer’s ad product offers AI-driven planning across premium streaming inventory and tools for video and audio creative.
Other streaming ad sellers partner with creative AI vendors to help smaller brands enter CTV. Those integrations make it cheaper to produce spot-quality ads without a full production budget.
Industry leaders warn about structural hurdles. Fragmented identity graphs, siloed measurement systems, and varying device ecosystems complicate AI-driven targeting in TV ad stacks.
- Ad tech firms say integration ease varies by where AI sits in the stack.
- Interruptive formats still suffer from fractured identity resolution.
- Siloed metrics make cross-channel attribution difficult.
At the cutting edge, research teams introduced a tool that can remove or alter objects in video, detect relationships between items on screen, and apply scene edits. Such capabilities point to more powerful video editing and personalization tools ahead.
Despite the innovation, many advertisers remain cautious. Creative for the living room is treated as premium. Brands worry that subtle visual or tonal flaws from automated production could damage a campaign’s impact.
