Agenda at a Glance

AI is changing how marketers create visual content, from campaign concepts and product imagery to social ads, website visuals, and short-form video. But strong results don’t come from typing a prompt and hoping for the best. Marketers need a practical framework for turning a campaign brief into assets that are usable, on-brand, and aligned with real business goals.

This hands-on workshop teaches that framework across both images and video: how to structure prompts, guide style and composition, build creative directions, and refine outputs into campaign-ready visual assets. It also tackles one of the biggest challenges in AI visual creation – hallucinations and quality issues like distorted products, generic visuals, weak text and logo handling, off-brand styling, and inconsistent outputs. Attendees leave with a repeatable workflow to create, evaluate, and improve AI visuals with more confidence and control.

Key Takeaways

• Identify where AI-generated images and video fit in marketing – and where they don’t.
• Accelerate ideation by generating and testing multiple creative directions at speed.
• Build a repeatable workflow that takes a campaign brief all the way to a finished, campaign-ready image.
• Craft prompts that produce on-brand, campaign-ready visuals.
• Transform static AI images into short video concepts and campaign clips.
• Diagnose and fix hallucinations and other common AI problems.

Who Should Attend: Marketers, brand and content teams, and creative leads who want to use AI for stronger campaign visuals and video – suitable for beginner/intermediate users. No design or technical background required.

Agenda and Activities

(subject to change)

0:00 – 0:10 (10 minutes)  Welcome, Intro & Workshop Roadmap

• Brief welcome and instructor introduction
• What this session is: practical and marketing-focused
• Workshop roadmap and what attendees will leave with

0:10 – 0:30 (20 minutes)  Module 1: Where AI Visuals Fit in Marketing

• Where AI-generated visuals support marketing work
• What AI does and doesn’t replace

0:30 – 0:50 (20 minutes)  Module 2: The AI Visual Workflow

• The core framework
  • Defining the core framework and how to routinely deploy it.

0:50 – 1:20 (30 minutes)  Module 3: Prompting for High-Quality Marketing Visuals

• The prompt framework
  • How outputs shift as elements are adjusted

1:20 – 1:30 (10 minutes)  Short Break

1:30 – 2:10 (40 minutes)  Module 4: Live Campaign Walkthrough with AI Images

• The centerpiece: building visuals for a real marketing scenario, step by step
• Attendees follow along in real time
• Campaign examples will be pre-tailored to the audience
• Designed to mirror real marketing work, not just a tool demo
• Questions taken throughout

2:10 – 2:35 (25 minutes)  Module 5: Extending AI Visuals with AI Video

• How AI-generated visuals become short motion assets, campaign teasers, video concepts, and storyboards
• Image generation creates the visual direction; AI video turns it into motion
• What we'll cover:
  • Where AI video fits in marketing workflows
  • Turning a static AI image into a short video concept
  • Writing motion prompts for marketing content
  • Controlling camera movement, subject movement, pacing, and mood
  • Avoiding common AI video problems
  • Using AI video for ideation, pitch decks, ads, social, and campaign testing

2:35 – 2:55 (20 minutes)  Module 6: Fixing Hallucinations & Common AI Problems

• Practical fixes for common problems:
  • Generic AI look, distorted limbs, fake-looking faces
  • Inconsistent product packaging, wrong logo or text, off-brand styling
  • Visual noise, wrong aspect ratio, poor composition, unrealistic lighting
  • The model getting stuck in a loop (regenerating the same flawed output or ignoring corrections)
  • Images that look impressive but aren’t usable

2:55 – 3:00 (5 minutes)  Wrap-up & Final Q&A

• Recap of the workflow
• Closing questions

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So, you're hearing all this buzz about AI in marketing, right? It feels a bit like everyone got a fancy new gadget, but the instruction manual seems to be missing, or maybe it's written in a language you don't quite speak yet. If you're wondering how to actually make AI do useful things for your marketing – things that go beyond just spitting out generic fluff – then you're absolutely in the right place. This workshop is all about rolling up our sleeves. We'll start by cutting through the noise of "The AI Revolution," giving you a clear, straightforward picture of what’s really changing for marketers and how you can confidently navigate these shifts without getting bogged down by the hype.

Then, we get to the real meat and potatoes: prompt engineering. Think of it as learning the 'magic words' – or rather, the smart, practical ways – to ask AI for exactly what you need, when you need it. In "Prompt Engineering 101," we’ll cover the essentials, the fundamental dos and don'ts that make all the difference. With "Prompt Engineering 102," we’ll dig a bit deeper, exploring how to craft prompts that get you truly insightful, creative, and on-brand results for your campaigns and content. Because the goal here isn't just to use AI; it's to use it well, making it a tool that genuinely makes your job easier and your marketing sharper. You'll discover how to make AI your helpful work buddy, not something that feels like another confusing task on your plate.

Key Takeaways for Marketers:

• Get a straight-to-the-point understanding of how the AI Revolution truly impacts your marketing work and what you can do about it.
• Learn the core skills of prompt engineering so you can talk to AI effectively and consistently get the results you actually want.
• Discover how to write more advanced prompts that help you generate genuinely creative ideas and higher-quality marketing content.
• Find practical ways to use AI prompts in your everyday marketing tasks to save time, spark new angles, and achieve better outcomes.
• Leave with a clear set of proven techniques and practical approaches you can use right away to make AI a valuable, human-directed part of your marketing toolkit.

Agenda and Activities

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For two decades, the search bar was the great equalizer—the one place a customer arrived neutral, ready to be won. That moment is disappearing. AI assistants now intercept discovery long before the click, returning a single synthesized answer with preferences and recommendations already baked in. Your customers aren't searching for you anymore; they're asking about you, and a model that never requested your permission is summarizing your brand narrative on your behalf. For senior marketers, this is more than a channel shift—it's a fundamental rethink of what brand presence, share of voice, and "ranking" even mean when the homepage may never get a visit.

This keynote panel brings together SEO, partnership, and product marketing leaders to unpack how brands earn the recommendation, not just the ranking, in an AI-mediated funnel. Expect a candid, practitioner-level conversation on Generative Engine Optimization (GEO), the credibility and entity signals that get a brand cited, and how to protect voice, accuracy, and attribution when AI sits between you and the customer. The throughline: vague positioning gets averaged out, while specific, defensible narratives get surfaced—making the AI-native era a forcing function for sharper marketing.

Key Takeaways

• Rethink visibility for a "zero-click" world where winning the AI recommendation matters more than winning the ranking.
• Unpack Generative Engine Optimization—the structured, authoritative content and consistent entity signals that get your brand cited inside the answer.
• Reposition brand and content to be machine-readable and recommendation-ready for a journey that may never touch your homepage.
• Leverage first-party data and strong partner ecosystems as a competitive moat once AI intermediates discovery.
• Measure brand influence directionally and repeatedly, tied to real prompts, so you can prove impact in an AI-mediated funnel.
• Sharpen your point of view into a specific, defensible narrative—because averaged-out positioning gets ignored while clear ones get surfaced.

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Every marketing organization has a measurement problem. It surfaces in every QBR, everyone agrees it matters, and it never gets fixed. The reflex is to buy another dashboard, and now to point AI at it. But the dashboard was always the last step, not the first. Measurement fails because the layer underneath it was never built: definitions no two teams agree on, data no one governs, and ownership no one holds. AI does not fix that. It scales it.

This session shows why measurement keeps failing in enterprise marketing, why more tooling and more AI make it worse when the foundation is broken, and what the next phase of going to market actually requires: a clean operating model that AI can stand on. Drawn from rebuilding measurement for a 2,000-person global function, where data error rates went from 30 percent to under 1 percent, it gives marketing and revenue leaders a clear-eyed way to tell real measurement apart from an expensive report nobody trusts.

Key Takeaways:

• Diagnose why the dashboard is the symptom, not the cause, of broken measurement.
• Build the four things that must exist upstream before any number is trustworthy: shared definitions, governed data, metadata, and ownership.
• Recognize why pointing AI at a broken foundation scales the mess faster, and with more confidence.
• Design the next phase of go-to-market with measurement built into the operating model, not bolted on after the fact.

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Every marketing team wants the benefits of AI. Faster content creation, easier access to knowledge, fewer repetitive tasks, and more time spent on high-value work. The challenge is that AI rarely struggles because of the AI itself. This session shares a real-world example of how one marketing organization scaled AI from scattered experiments to everyday use across content, communications, planning, and knowledge management.

Along the way, the team discovered an unexpected barrier. Content that was difficult to find, difficult to trust, and difficult for AI to use effectively. You'll get a practical look at the changes that made the difference, from improving content discoverability and structure to introducing new workflows, resources, and adoption tactics. More importantly, you'll see the results. What gained traction, what fell flat, what had to be rethought, and the measures used to determine whether the effort was actually working.

If you're trying to move beyond AI enthusiasm and create lasting behavior change, this session will give you a blueprint grounded in experience, not theory.

Attendees Will Leave With:

1. A practical playbook for driving AI adoption in a marketing organization
The approaches that helped move people from occasional experimentation to regular use in their daily work.

2. The content improvements that had the biggest impact on AI performance
Why content organization, discoverability, and structure mattered more than expected, and where to focus first.

3. Real-world results and lessons learned
What worked, what didn't, what surprised the team, and the metrics used to demonstrate value and sustain momentum.

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Access to AI is no longer the advantage – nearly every marketing organization now runs on the same models and tools. Yet a widening gap separates the teams generating real pipeline and ROI from those stuck in perpetual pilot mode two years in, and it rarely comes down to the technology. This panel brings together innovation, product marketing, and partner marketing leaders from Ogilvy, UiPath, Informatica, and First Advantage to unpack what actually pulls organizations ahead: adoption built on trust rather than mandates, work that's redesigned before the tool is deployed, and AI fluency distributed across the organization instead of hoarded by a small group of experts.

Drawing on hard-won, in-the-trenches lessons – including a compliance tool that jumped from near-zero uptake to 84% adoption simply by shifting from blocking to advising – our panelists move past the hype to the operating realities that decide who scales and who stalls: governance, executive sponsorship, cross-functional buy-in, and the critical difference between technical proof and the operational trust that turns a demo into daily use. If your organization is still piloting, this conversation will show you exactly where the bottlenecks are and how the leaders got past them.

Key Takeaways:

• Diagnose why pilots stall out – and why the wall is almost never the technology itself.
• Design AI adoption around human trust, giving people recommendations and agency instead of hard blocks and mandates.
• Redesign the work before deploying the tool, rather than plugging AI into a broken workflow and expecting different results.
• Distribute AI fluency across the organization so capability lives with the people closest to the work, not just a handful of experts.
• Involve IT, legal, and procurement in week one so pilots have a clear, pre-approved path to production and scale.
• Measure what "winning with AI" really looks like in pipeline and ROI numbers – and set ambition beyond doing yesterday's work faster.

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This session shows how a lean marketing team can use AI agents to monitor competitors, extract market signals, and convert insights into marketing initiatives. Based on real-world examples from an AI startup, the session will walk through the full workflow from idea generation and competitive research to messaging, draft creation, asset development, campaign planning, and pipeline follow-up.

Key takeaways:

• Build 24/7 agents for competitive intelligence.
• Transform competitor activity into messaging, content, and campaign ideas.
• Connect idea → research → draft → asset → campaign → pipeline.
• Identify what to automate versus what requires human review.

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AI is fundamentally changing how buyers discover, evaluate, and choose brands. Traditional demand generation models built around broad campaigns and linear funnels are struggling to keep pace with fragmented customer journeys, rising acquisition costs, and increasing expectations for personalization.

Join Nikhil Pandey, Associate Director – Digital at Unilever Food Solutions North America, for an engaging session on how AI is transforming demand generation from reactive marketing to predictive growth. Drawing on real-world experience across content, media, CRM, eCommerce, and customer engagement, Nikhil will share how organizations can use AI to identify demand signals earlier, personalize at scale, accelerate funnel velocity, and connect marketing investments more directly to revenue outcomes.

Whether you're just beginning your AI journey or looking to scale existing capabilities, this session will provide practical strategies for building a smarter, faster, and more effective growth engine.

Key Takeaways:

• Move from lead generation to demand intelligence by identifying buyer signals before prospects actively enter your funnel.
• Build a predictive targeting framework using AI, first-party data, and behavioral insights to prioritize the highest-value opportunities.
• Increase funnel velocity through AI-powered personalization, next-best-action recommendations, and smarter audience activation.
• Scale content production and optimization using AI while maintaining brand consistency and relevance.
• Measure what matters, connecting AI initiatives to pipeline growth, conversion performance, customer acquisition, and revenue impact.
• Avoid common AI adoption pitfalls and understand where human creativity and strategic oversight remain essential.
• Develop an AI-ready marketing organization that combines technology, data, content, and experimentation to drive sustainable growth.

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Every marketer knows the routine: logging into multiple platforms, exporting CSVs, formatting spreadsheets, and trying to extract meaningful insights before a big meeting or find a simple concise answer to the biggest question of all: Why? Data analysis and reporting are manual, time-consuming, and take you away from actual strategy.

What if you could offload that heavy lifting to AI?

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Marketing teams are surrounded by signals: customer conversations, campaign data, content engagement, competitor moves, analyst commentary, CRM activity, and market shifts. The challenge is no longer access to information. It is knowing which signals to trust, how to connect them, and when to act.

In this session, Philip Miller will share a practical framework for building an AI-ready GTM intelligence engine that turns fragmented signals into faster, more confident marketing decisions. The talk will show how marketers can move beyond isolated AI tools and build repeatable workflows that combine context, governance, and human judgment to sharpen messaging, prioritize audiences, adapt campaigns, support sales, and respond to market change.

Attendee Takeaways:

• A practical signal-to-decision framework for modern GTM teams.
• How to use AI to reduce noise, surface patterns, and support better marketing decisions.
• Why trusted context, governance, and human review matter when applying AI to GTM workflows.
• A repeatable workflow model for campaign planning, messaging, content prioritization, and sales enablement.

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