AI adoption in B2B marketing is accelerating but compliance is struggling to keep pace.
Marketing teams are under pressure to move fast, adopt new tools, and prove ROI, while compliance, legal, and risk functions are asking hard questions about data privacy, algorithmic bias, vendor liability, and transparency. The gap between the two is creating real business risk.
This session bridges that gap. Drawing on 400+ hours of hands-on AI implementation and collaborative work with Cambridge University, Kathryn Strachan cuts through the hype to give compliance and marketing leaders a shared framework: how to embrace AI's genuine commercial potential while building the guardrails that protect the business, the brand, and the customer.
Content tools, CRM enrichment, ad targeting, lead scoring, chatbots: the exposure is real, and regulators are catching up fast.
This session gives you the knowledge to ask the right questions, set the right policies, and ensure your organisation can scale AI use without creating legal or reputational liability. Uniquely, it's delivered by someone who works at the intersection of marketing leadership and AI implementation not a theorist, but a practitioner who has navigated these tensions with real clients.
● Data privacy in AI: GDPR, consent, data residency, and third-party vendor risk
● Algorithmic bias in marketing: how it happens, how to spot it, and what to do about it
● Transparency and explainability: what regulators expect and how to communicate AI use to customers
● Liability and accountability: who is responsible when AI-driven marketing goes wrong
● Building an AI use policy: what to include, how to get buy-in, and how to keep it current
● Real-world case studies: where compliance and marketing have collided, and the outcomes
● Practical next steps: a starting framework attendees can apply the same week
Marketing teams are under pressure to move fast, adopt new tools, and prove ROI, while compliance, legal, and risk functions are asking hard questions about data privacy, algorithmic bias, vendor liability, and transparency. The gap between the two is creating real business risk.
This session bridges that gap. Drawing on 400+ hours of hands-on AI implementation and collaborative work with Cambridge University, Kathryn Strachan cuts through the hype to give compliance and marketing leaders a shared framework: how to embrace AI's genuine commercial potential while building the guardrails that protect the business, the brand, and the customer.
WHY SHOULD YOU ATTEND?
AI is already inside your marketing function whether you know it or not.Content tools, CRM enrichment, ad targeting, lead scoring, chatbots: the exposure is real, and regulators are catching up fast.
This session gives you the knowledge to ask the right questions, set the right policies, and ensure your organisation can scale AI use without creating legal or reputational liability. Uniquely, it's delivered by someone who works at the intersection of marketing leadership and AI implementation not a theorist, but a practitioner who has navigated these tensions with real clients.
AREA COVERED
● The current AI marketing landscape: tools, adoption rates, and where B2B teams are investing● Data privacy in AI: GDPR, consent, data residency, and third-party vendor risk
● Algorithmic bias in marketing: how it happens, how to spot it, and what to do about it
● Transparency and explainability: what regulators expect and how to communicate AI use to customers
● Liability and accountability: who is responsible when AI-driven marketing goes wrong
● Building an AI use policy: what to include, how to get buy-in, and how to keep it current
● Real-world case studies: where compliance and marketing have collided, and the outcomes
● Practical next steps: a starting framework attendees can apply the same week
LEARNING OBJECTIVES
- Understand which AI tools B2B marketers are actually using and the compliance risks each one creates
- Know what GDPR, data residency, and consent frameworks mean in the context of AI-driven marketing
- Recognise how algorithmic bias enters marketing workflows — and how to audit for it
- Understand what customers and regulators now expect in terms of AI transparency and explainability
- Be able to build or review an AI use policy that marketing teams will actually follow
- Apply a practical risk framework to assess AI adoption decisions before they create problems
WHO WILL BENEFIT?
Chief Compliance Officers, General Counsel and Legal teams, CMOs and VP Marketing in regulated industries, Risk and governance professionals working on AI policy, B2B technology, fintech, and professional services firms scaling AI use in customer-facing functions
AI is already inside your marketing function whether you know it or not.
Content tools, CRM enrichment, ad targeting, lead scoring, chatbots: the exposure is real, and regulators are catching up fast.
This session gives you the knowledge to ask the right questions, set the right policies, and ensure your organisation can scale AI use without creating legal or reputational liability. Uniquely, it's delivered by someone who works at the intersection of marketing leadership and AI implementation not a theorist, but a practitioner who has navigated these tensions with real clients.
Content tools, CRM enrichment, ad targeting, lead scoring, chatbots: the exposure is real, and regulators are catching up fast.
This session gives you the knowledge to ask the right questions, set the right policies, and ensure your organisation can scale AI use without creating legal or reputational liability. Uniquely, it's delivered by someone who works at the intersection of marketing leadership and AI implementation not a theorist, but a practitioner who has navigated these tensions with real clients.
● The current AI marketing landscape: tools, adoption rates, and where B2B teams are investing
● Data privacy in AI: GDPR, consent, data residency, and third-party vendor risk
● Algorithmic bias in marketing: how it happens, how to spot it, and what to do about it
● Transparency and explainability: what regulators expect and how to communicate AI use to customers
● Liability and accountability: who is responsible when AI-driven marketing goes wrong
● Building an AI use policy: what to include, how to get buy-in, and how to keep it current
● Real-world case studies: where compliance and marketing have collided, and the outcomes
● Practical next steps: a starting framework attendees can apply the same week
● Data privacy in AI: GDPR, consent, data residency, and third-party vendor risk
● Algorithmic bias in marketing: how it happens, how to spot it, and what to do about it
● Transparency and explainability: what regulators expect and how to communicate AI use to customers
● Liability and accountability: who is responsible when AI-driven marketing goes wrong
● Building an AI use policy: what to include, how to get buy-in, and how to keep it current
● Real-world case studies: where compliance and marketing have collided, and the outcomes
● Practical next steps: a starting framework attendees can apply the same week
- Understand which AI tools B2B marketers are actually using and the compliance risks each one creates
- Know what GDPR, data residency, and consent frameworks mean in the context of AI-driven marketing
- Recognise how algorithmic bias enters marketing workflows — and how to audit for it
- Understand what customers and regulators now expect in terms of AI transparency and explainability
- Be able to build or review an AI use policy that marketing teams will actually follow
- Apply a practical risk framework to assess AI adoption decisions before they create problems
Chief Compliance Officers, General Counsel and Legal teams, CMOs and VP Marketing in regulated industries, Risk and governance professionals working on AI policy, B2B technology, fintech, and professional services firms scaling AI use in customer-facing functions