A EU funding opportunity to address gender bias in SME GenAI advertising
The European Commission has issued a call through the Citizens, Equality, Rights and Values (CERV) program. Specifically, the CERV-2026-GE call seeks high-impact interventions to combat gender stereotypes in media and advertising.
We have the blueprint. We have the tech. We need a Lead Partner.
We are proposing a 24-month roadmap designed to equip European SMEs with the tools to outpace algorithmic bias. We are seeking an institutional partner to officially lead our consortium and bring this vision to life via a joint EU application.
The future of advertising is being written by algorithms. We're here to make sure they don't delete decades of progress on gender equality.
WHY NOW? THE NUMBERS DON'T LIE
The use of Generative AI has moved past experimentation. It is becoming the primary infrastructure for creating advertising content at scale. For SMEs, that means faster production, lower costs and easier access to creative capabilities that were once out of reach.
But there's a catch.
European SMEs are integrating GenAI tools into their marketing workflows faster than they are building the knowledge to use them responsibly. Without the right guidance, GenAI can easily reproduce harmful, historically regressive stereotypes in copy, visuals, prompts and campaign decisions — at speed and at scale.
While 69% of advertisers are rushing to adopt AI-driven creatives, 71% of SMEs admit they lack the expertise to do so.
European SMEs need digital advertising to stay competitive, but bias is already visible in the GenAI systems shaping language and imagery. Stereotyped outputs can become normalised through these channels, presenting a real challenge that threatens to reverse decades of progress in European gender equality.
Representation
DALL-E 2 generates white men 67% of the time for "CEO" prompts, while LLMs describe women in domestic roles 4× more often than men.
Pay Gaps
GPT-4 assigns women lower salaries 62% of the time in simulations.
Linguistic Bias
73.1% of LLM responses in French default to masculine-generic forms.
Double Standards
Image models generate women in revealing clothing 3× more often, reinforcing objectification in commercial contexts.
Representation
DALL-E 2 generates white men 67% of the time for "CEO" prompts, while LLMs describe women in domestic roles 4× more often than men.
Pay Gaps
GPT-4 assigns women lower salaries 62% of the time in simulations.
Linguistic Bias
73.1% of LLM responses in French default to masculine-generic forms.
Double Standards
Image models generate women in revealing clothing 3× more often, reinforcing objectification in commercial contexts.
Representation
DALL-E 2 generates white men 67% of the time for "CEO" prompts, while LLMs describe women in domestic roles 4× more often than men.
Pay Gaps
GPT-4 assigns women lower salaries 62% of the time in simulations.
Linguistic Bias
73.1% of LLM responses in French default to masculine-generic forms.
Double Standards
Image models generate women in revealing clothing 3× more often, reinforcing objectification in commercial contexts.
Representation
DALL-E 2 generates white men 67% of the time for "CEO" prompts, while LLMs describe women in domestic roles 4× more often than men.
Pay Gaps
GPT-4 assigns women lower salaries 62% of the time in simulations.
Linguistic Bias
73.1% of LLM responses in French default to masculine-generic forms.
Double Standards
Image models generate women in revealing clothing 3× more often, reinforcing objectification in commercial contexts.
Representation
DALL-E 2 generates white men 67% of the time for "CEO" prompts, while LLMs describe women in domestic roles 4× more often than men.
Pay Gaps
GPT-4 assigns women lower salaries 62% of the time in simulations.
Linguistic Bias
73.1% of LLM responses in French default to masculine-generic forms.
Double Standards
Image models generate women in revealing clothing 3× more often, reinforcing objectification in commercial contexts.
Our proposed 24-month programme is a practical, transnational infrastructure for the responsible use of GenAI. It outlines a five-phase journey from Risk Awareness to Market-Wide Implementation: Notice: Multilingual awareness campaign Recognise: Self-diagnosis and benchmarking tools for SMEs Act: A "Stereotype-Safe" prompting playbook and browser plugin, education materials, training sessions. Formalise: Modular "Train-the-Trainer" certification Share: A voluntary pledge and official badge.
SEEKING: A CONSORTIUM LEAD
BC Agency is a Lisbon-based creative and data science firm. We provide technical innovation and creative capabilities, as well as media planning and dissemination, but the CERV program requires a robust consortium led by an organisation with the reach and legitimacy to manage an EU grant of this scale.
What we bring to the table:
- Proprietary Tech: The Bias Scraper (AI ad auditor), niche influencer finder, and AI Self-Check Tool
- Expertise: A majority-female team of creative practitioners, community managers, data scientists, developers, strategists, social and paid media experts
- Strategy: A fully developed project roadmap aligned with EU Priority 4
What we need from you:
- To act as the Lead Applicant for the CERV-2026-GE call.
- To provide the institutional framework and administrative oversight for the 24-month project.
The funding is available. The problem is urgent. The technical solution is ready to go. All that's missing is the leadership to make it official.