If you’re not yet familiar with the fundamentals of the EU AI Act and how it builds on the foundation of GDPR, particularly in areas such as transparency, vendor due diligence and data profiling, you’re welcome to read “How to ensure compliance and mitigate risks”.
This time, it’s more than a legal update. With the AI Office and AI Board officially operational since August 2025, the legislation is shifting from policy to practice. I spoke with David Smith, AI Sector Specialist, DPO Centre, to understand how B2B marketers can move beyond compliance as a checkbox and treat it as a source of competitive strength.
David reassures that responsible B2B marketing activities are unlikely to be a target of regulatory enforcement: “for the B2B industry, it should largely be business as usual. The regulation focuses on general-purpose models and high-risk systems, which are areas most marketers don’t touch directly.”
This framing matters. It means that the real work lies in governance, ensuring AI is used and scaled responsibly. B2B marketing teams are already embedding AI modules for account selection, content creation and campaign orchestration, but all this needs to be done with appropriate governance guardrails.
The latest implementation stage of the EU AI legislation is an opportunity to shift from ensuring compliance to gaining confidence. This implies mapping AI use, selecting vendors, training teams and integrating governance in a strategic way to have an impact on business growth.
1. Mapping your AI footprint beyond the legal lens
It’s obviously still important to treat any AI-tool deployment as you would a new data stream, conducting a data-protection impact assessment, checking for sensitive attributes and ensuring transparency. But David advises to build on that foundation and apply a marketing lens:
“Start by mapping where you already use AI and what your roadmap looks like for the next 12 to 18 months. Then identify which parts of the regulatory framework apply to you.”
This implies listing every AI-enabled touchpoint such as CRM-driven lead scoring, predictive account targeting, generative content engines, chatbots and dynamic personalisation. The next step is to ask: “Does this tool use personal or business-user data? Does it profile individuals? Does it create categories that might trigger bias?” David cautions:
“If you’re just targeting businesses, there’s less cause for concern. It’s when you start creating detailed profiles of individuals that regulatory risks appear.”
B2B marketing leaders need to ensure they’re compliant and that teams are trained to use the AI tools responsibly. This shows a shift in which the compliance question now becomes: how many of those tools have been inventoried? How many have had a risk-scoping exercise? And how many have a governance framework that supports scale?
2. Vendor transparency: a new procurement battleground
While before the focus was on vendor selection, and asking relevant questions about how their models work, what data they use and what are the risks, with the AI Act now moving from law to enforcement, transparency becomes a competitive advantage.
This is particularly relevant to B2B vendors advertising safe AI credentials. David stresses that “reputable vendors should be falling over themselves to make this easy for clients. It’s becoming a market differentiator: you’ll see trust centres, detailed documentation and compliance dashboards as standard.”
For marketing operations teams, that means your procurement checklist must evolve. It’s important to ask:
- Does the vendor publish documentation on training data, model behaviour and performance KPIs?
- Does it provide a “trust centre” or compliance portal we can audit?
- Do contracts include clauses around audits, transparency and redress?
An effective AI adoption requires cross-functional collaboration, teams must align to ensure tools are deployed responsibly and data is safeguarded. In other words, vendor procurement is no longer solely a marketing operations task; it must be cross-functional. The compliance framework has to also include vendor governance.
3. Focus on the practical risks
B2B marketers may easily get distracted by “How will the EU AI Act apply to my work?” and lose track of everyday threats. The biggest immediate threats in B2B remain the data-protection fundamentals, not AI risks. The legislation targets threats to rights, freedoms or public safety and these don’t really fall in the B2B marketing world.
David stresses that the real issues are deceptive, manipulative practices or biometric profiling: “Marketers should still worry more about consent management and opt-outs than about the AI Act. Those remain far greater risks.”
For instance, building AI tools in-house is a great way to ensure marketing teams can accelerate innovation while retaining control over data processes, boosting both compliance and operational confidence. This means your risk-mitigation roadmap stays relevant and you may now add internal controls over AI-driven decision-making, checking for bias and ensuring traceability.
4. Voluntary code of practice: A reputation-driven governance
The voluntary AI Code of Practice is no longer just a nice-to-have, but a signal of trust. It provides structure and clarity, showing that you’re acting responsibly. As David mentioned: “If you’re already following best practices, it won’t be burdensome. If not, you’d better have a strong reason why because soon it’ll be the default expectation.”
From a marketing leadership viewpoint, signing up to the code gives you a story: “We operate according to recognised AI ethical standards.” That matters in procurement, especially when selling to enterprise clients who ask for ethical-AI assurances.
Integrating the code of practice can actually become part of your governance narrative, not just for legal compliance but for market trust.
5. Global operations: one playbook to rule them all
GDPR already requires global alignment. With the AI legislation and emerging national supervisory authorities, that principle now takes on urgency. Even with local variations, everything must still align with the AI Act and GDPR.
In practice, this means building a central playbook for AI governance featuring policy, vendor review, risk assessment and training while overlaying local/regional variants only where necessary. This simplifies oversight and avoids fragmentation. Marketing teams become global by default rather than siloed by territory.
6. Future-proofing your AI-governance
Given the clarity on enforcement timelines and vendor behavior, David suggests marketers should build a governance engine rather than ad-hoc fixes:
“Identify your key AI use cases and classify them by risk. Low-risk tasks like generating generic content need little oversight, while profiling or lead-generation tools require stronger controls and due diligence. AI feels like a free-for-all again, like the early SaaS days, yet all corporate rules still apply. Don’t feed sensitive data into unapproved tools.”
Five steps to optimise AI governance:
- Map AI use cases, tag by risk.
- Embed human-in-the-loop checks for higher-risk tools.
- Update vendor contracts to reflect AI transparency and audit rights.
- Train marketing operations and campaign teams on AI tool limits, data-input best practices and IP protection.
- Establish a compliance dashboard (or use existing vendor “trust-centres”) to monitor tool usage, model updates and governance metrics.
Compliance as a growth enabler
For B2B marketers, the real payoff of addressing the AI Act isn’t avoiding fines, it’s turning governance into a differentiator. This is not about reinventing compliance but doing the good things you’re already doing more effectively. A structured governance can transform AI into a strategic asset but training is crucial. Everyone needs to know how to use AI safely and protect both company and client data.
With the EU AI legislation now entering its enforcement phase, the companies that embed governance into marketing operations will set the standard. Treating compliance as a strategic capability, rather than just a regulatory requirement, allows B2B marketers to innovate with confidence, scale AI responsibly and protect both data and reputation.
