Keynotes, panels, workshops, and webinars on AI agents, responsible AI, and AI strategy for enterprise marketing teams. I also design and facilitate closed-door executive sessions, including the Marketing + Media Alliance (MMA) CMO AI Transformation Summit and CEO + CMO Summit. Past audiences include AI4, POSSIBLE, MAICON, Copyleaks, MMA, and TEDxNYU.
Alec Foster is the Chief Agent Officer & Responsible AI Lead at the Marketing + Media Alliance (MMA), where he owns the AI infrastructure, governance, and digital operations for a 90-person global organization serving 825+ corporate members.
Alec co-leads MMA's AI Leadership Think Tank (ALTT), a practitioner community of 300+ marketing and AI leaders from 180+ companies including GM, AT&T, Mastercard, Kroger, Home Depot, Coca-Cola, Unilever, and Hilton, whose CMOs sit on MMA's boards. He designs and facilitates the executive rooms where that community makes decisions, including the CMO AI Transformation Summit and the CEO + CMO Summit, and he advises member CMOs on their own AI strategy. He oversees the Future Labs, which has run 75+ AI studies inside live campaigns, including the 29 controlled experiments across 18 global brands in MMA's Consortium for AI Personalization (CAP), which delivered an average +160% lift in advertising performance over baseline.
Alec is also MMA's CDO and CISO, managing all integrations, AI tooling, and security policy. He built the AI Agent Foundry, a mandatory company-wide program requiring all staff to develop AI fluency, build workflows, and dedicate 10% of capacity to building AI agents. He also led the company's enterprise AI platform migration, deployed custom AI assistants pre-loaded with institutional knowledge for every employee, and built a RAG-powered research assistant grounded in scientifically validated marketing knowledge (200+ empirical generalizations distilled from 10,000+ peer-reviewed studies).
Alec holds a CIPP/US privacy certification and an M.St. in AI Ethics from the University of Cambridge. His dissertation, Protocols of Power, examined the governance challenges of multi-agent communication protocols (MCP, A2A): how autonomous AI systems negotiate, delegate, and share control across organizational boundaries.
Based in the Bay Area, Alec spends his free time creating immersive art, teaching electric hydrofoiling, and boxing.
Stop having your team start every AI conversation from scratch.
How MMA gave every one of its 90 employees MAVEN, a custom AI assistant pre-loaded with org context, brand standards, tool integrations, and data-handling rules. The session covers the architecture, the governance rules that ship inside the assistant so staff comply by default, and how we moved 88 seats between AI platforms without breaking anyone's workflow. It includes live demos, and attendees take home the MAVEN template.
proof: Deployed across 90 staff in 19 countries
audience: AI workflow integration, team enablementformat: 20-min keynote · 30-min keynote · 45-min talk with live demo
02
What's Actually Working: AI Across the Ad Funnel
You can get real value from AI in advertising without generating a single new ad.
Results from MMA lab experiments with brands including Kroger, GM, Shell, and MLB: matching existing creative to audience and context, reweighting audiences mid-flight, scoring creative before launch, and AI-assisted production. Wins sit next to tests that showed no lift, and every number carries its baseline, so you can tell a live campaign result from a brand survey or a model. It closes with new research on motivational alignment and AI-search visibility, plus a one-page template for designing your own test.
proof: Named results from Kroger, GM, Shell, and MLB, including the tests that showed no lift
audience: data, measurement, AI analytics, case studiesformat: 20-min keynote · 30-min keynote · 45-min talk
03
Building an AI-Capable Workforce
What to teach people once they already know how to prompt.
The training model MMA runs across its global staff: a gamified, self-paced AI Mastery program, a tiered certification track (Foundations → Agent Development → Agent Management), and the AI Agent Foundry, a mandatory program where every employee spends 10% of their capacity building automations. We show what people built, from meeting transcripts that update the CRM to lead discovery pipelines and weekly reporting. Attendees get our validated impact templates.
proof: 100% staff trained, 40+ live production workflows
Governance your team follows because the tools enforce it.
How to build governance into the tools, approvals, and architecture your team already uses, so the responsible choice is also the easiest one. The material comes from MMA's Responsible AI Innovation Lab (RAIL), which has published 8 governance frameworks adopted by Fortune 500 marketers, and from my Cambridge research on multi-agent governance. It covers automated risk tiering, usage policies that travel inside the assistant, self-enforcing data classification, and approval workflows that route by risk level without creating bottlenecks.
proof: 8 published RAIL frameworks, Fortune 500 adopted
The protocols connecting your agents carry design choices that favor the companies that wrote them.
Original University of Cambridge research on the agent communication protocols (A2A, MCP) that govern how AI agents coordinate across enterprise systems. Standards marketed as "open" contain design choices that concentrate control with platform owners, turn agents into auditable subjects, and quietly reposition human workers as managers of AI teams. Marketing leaders adopting agentic AI need to know whether their agents end up working for them or for the platform.
proof: The executive version of my Cambridge dissertation, Protocols of Power (07 is the lecture)
Which marketing roles stay human, which become agentic, and what that does to the org chart.
Three plausible versions of the 2030 marketing org, each with different assumptions about agent autonomy, headcount, and where trust breaks. We work through which roles compress, which expand, which new ones appear, and what to hire and reorganize for now. It runs as a keynote or as a facilitated scenario session where your leadership team argues its way to a position, drawing on MMA's research and the AI Leadership Think Tank's work with CMOs partway through the change.
A protocol specification is a political text. Read it as one.
My Cambridge dissertation treats Google's Agent2Agent protocol as what Foucault called a diagram of power: an architecture that governs conduct at a distance. Working from Foucault, Bowker and Star's classification theory, and Galloway's protocological control, I read A2A's technical and governance documents as governmental texts and trace how the Agent Card makes agents legible, rigid message formats discipline them, mandatory logging builds a panopticon, and a founders-only committee launders corporate authority as open governance. What emerges is a new subject, the docile digital worker, caught before this infrastructure turns invisible.
proof: 15,287-word M.St. dissertation, University of Cambridge, 2025 (05 is the executive version)
audience: AI ethics and STS scholars, policy researchers, governance leads, university and think-tank audiencesformat: 30-min talk · 45-min lecture
08
The Data Dilemma: Privacy Against Fairness
Detecting bias needs the demographic data that privacy law tells you to delete.
AI governance treats privacy and fairness as rival values, and the tension is real: GDPR's data minimization and special-category rules strip out the attributes a bias audit needs, while fairness pursued without limit invites surveillance. Reading Barocas and Selbst on proxy discrimination against Viljoen's relational theory of data governance, I argue the binary is false. Amazon's hiring tool, the Apple Card, and IBM's exit from facial recognition show what each regime hides. The question underneath is who decides which sensitive data gets used, and under whose authority.
Beyond Principles: Why Responsible AI Stalls Inside the Firm
AI ethics has an oversupply of principles and a shortage of mechanisms.
Rakova and colleagues' interviews with 26 practitioners show responsible AI work stalling on the same failures: no authority, no aligned incentive, no metric that competes with revenue. Marchant asks whether professional societies like the ACM and IEEE can fill the vacuum with soft law. I read both against two earlier experiments in industry self-regulation, the Fair Labor Association and the Interactive Advertising Bureau, and argue that without structural separation between standard-setting and member advocacy, and a credible regulatory threat behind it, self-governance reproduces ethics washing at industry scale.
2026-10-15·MAICON (Marketing AI Conference)·Cleveland, OH
What's Actually Working: AI Across the Advertising Funnel
You can get real value from AI in advertising without generating a single new ad. Drawing on MMA lab experiments with Kroger, GM, Shell, and MLB, the session shows where AI improves the decisions behind a campaign: which audience sees which existing creative, in which context, and which creative to run. Strong results sit next to tests that showed no lift, along with where AI-generated creative held up against human work and where it fell short. It ends with new research on motivational alignment and AI-search visibility, plus a one-page template for designing your own test. Thursday, Oct. 15, 10:00 a.m. ET, Ballroom C, Applied AI track.
A ZapConnect panel with Philip Lakin (Director of AI Transformation, Zapier) and Chris McDermott (North America AI Strategy & Enablement Lead, DENSO) on getting AI past a few power users to everyone on a team. Most companies "rolled out AI" by buying licenses, and everyone but the builders went back to their inbox. I covered MMA's past year of getting every person on staff, in every role, building their own agents and automations: what worked, what didn't, and how to bring a whole organization up to speed.
The AI Upskilling Playbook: A Framework for Enterprise AI Training
How to build enterprise AI training that changes how people work. It covers a tiered certification path (foundations → agent development → agent management), the mandatory hands-on Agent Foundry where every employee builds real automations, and why you should measure capability gains and workflows shipped rather than course completions. The examples come from MMA's company-wide rollout.
An in-person evening session at WPP's Düsseldorf office on leading responsible-AI change inside marketing organizations. I argued that governance works only when it's built into the tools, approval flows, and architecture teams already use.
2025-05-28·AI Dev Summit·San Francisco, CA
Responsible AI for AI Builders
A developer-track session at one of the largest AI engineering events, on translating responsible-AI principles into the evals, guardrails, and runtime controls that engineering teams ship.
2025-03-19·MMA Webinar·Virtual
Navigating AI Regulation: Marketing in a New Era
Where global AI regulation stands (the EU AI Act, emerging US state laws, and disclosure rules) and what compliance looks like in day-to-day marketing operations. It also covers copyright and training-data questions for generative tools, and the changes to make in your stack before the rules harden.
AI Agents in Marketing: Navigating Hype, Risk, and Opportunity
What marketing agents can and can't do today, and where they affect the business: efficiency, operational capability, revenue growth, competitive advantage, and brand safety. It also covers how to sequence an implementation with governance built in, and how to prepare an organization for more autonomous workflows.
Ethical AI Marketing: A Toolkit for Responsible Innovation
A working toolkit for responsible AI in marketing: practical frameworks for risk tiering and governance, how to address bias and keep deployed systems transparent, and the case for treating responsible AI as a competitive advantage.
From Theory to Practice: Responsible AI in Marketing
Presented at AI4, the largest AI industry conference in North America. The talk covered moving responsible-AI principles into deployed marketing practice: the frameworks, the deployments, and the organizational changes that make governance stick.
2024-05-21·The Original Source Podcast (Copyleaks)·Podcast
Fostering Ethical AI
A long-form conversation on responsible AI and content provenance: how to build trust into generative tools, the ethics of training data and attribution, and what 'responsible' means once AI-generated content is everywhere.
A session for marketing leaders on why responsible AI belongs on the CMO agenda, with tactics for building ethical guardrails into AI marketing projects before launch.
2023-03-02·Tea Time with Tech Marketing Leaders·Podcast
Ethical Marketing Through Transparent Consumer Privacy
A conversation on privacy-first marketing: how a CIPP/US lens shapes data strategy, and why treating privacy as part of the product builds consumer trust and growth.
An early-career fireside chat in Autopilot's Marketers & Founders series on growth marketing for startups: running acquisition experiments, building funnels that compound, and finding the channels that work before there's a budget to spend.
2015·EFF & MIT Freedom to Innovate Summit·Cambridge, MA
Building a Campus Digital Rights Movement
A talk at the EFF- and MIT-convened Freedom to Innovate Summit on organizing students around digital rights: building campus coalitions for privacy, open access, and free expression, and turning scattered concern into a movement that outlasts any one graduating class.
