Videos
AI in Advertising — Cohort-Based Training Proposal for Paramount Advertising
Program Overview
This training series builds AI fluency across advertising teams through a structured, highly applied learning journey — moving from foundational understanding into real ad tech workflows, then into day-to-day role usage across Paramount teams. Each session includes industry examples, competitive context, Paramount-specific applications, weekly quizzes, and open office hours for deeper application.
Cohort Format
350
participants
35
people per cohort
10
total cohorts
4
live sessions per cohort
Fee - $400 per student - $140,000
Strategic Outcomes
Teams walk away with:
1
Fluency across ML, DL, GenAI, and Agentic AI
2
Competitive knowledge of how media and ad tech peers are using AI
3
Paramount-specific use cases tied to workflow and revenue
4
Clear client-facing language to explain AI confidently
5
A role-specific AI workflow ready for immediate use
🧠 SESSION 1 — AI FOUNDATIONS
Objective: Establish shared language and clarity around AI concepts so teams can confidently speak about AI with clients and internally.
🔹 Topic 1 — Machine Learning (ML)
Definition: Pattern recognition and prediction using supervised and unsupervised learning approaches.
What Competitors Are Doing:
  • Meta Advantage+ campaigns
  • DV360 automated bidding
  • Amazon Ads audience optimization
How Paramount Can Use It: Audience clustering and inventory scoring before campaign launch to improve targeting precision and yield optimization.
🔹 Topic 2 — Deep Learning (DL)
Definition: Neural networks that uncover complex behavioral patterns across multiple data layers.
What Competitors Are Doing:
  • Netflix retention models
  • Roku recommendation system
  • Disney+ forecasting algorithms
How Paramount Can Use It: Predictive content affinity modeling across BET, Paramount+, Pluto TV, and linear television to enhance cross-platform audience understanding.
🔹 Topic 3 — Generative AI (GenAI)
Definition: Net-new output generation via vector space, embeddings, and natural language prompting.
What Competitors Are Doing:
  • Google Performance Max creative automation
  • Adobe Firefly asset generation
  • Amazon dynamic ad creation
How Paramount Can Use It: Creative iteration support and client-facing language assistance to accelerate campaign development and pitch personalization.

🧪 SESSION 1 EXERCISE — "EXPLAIN IT TO A CLIENT"
Activity: Teams explain ML, DL, and GenAI using clear, client-facing language with zero technical jargon.
Goal: Build confidence and establish shared internal vocabulary that translates to client conversations.
Reinforcement:
  • Weekly quiz
  • Live office hours for questions and deeper application
Homework: AI in the Wild" — Find 2 recent AI examples in advertising and document how Paramount could apply similar approaches
⚙️ SESSION 2 — AGENTIC AI & APPLIED MEDIA WORKFLOWS
Objective: Show how AI is already reshaping campaign planning, optimization, targeting, and identity — and teach teams how to position AI clearly with clients.
🔹 Topic 1 — Agentic AI
Definition: AI systems that can reason, plan, and act autonomously—moving beyond reactive chatbots to proactive campaign management.
What Competitors Are Doing:
  • Agency AI pilot programs
  • DSP campaign automation tools
  • Pacing simulation platforms
How Paramount Can Use It: Autonomous media planning assistance and automated client brief generation to streamline pre-meeting preparation.
🔹 Topic 2 — AI Inside Today's Ad Tech Stack
How AI Powers Current Workflows:

🗣️ SESSION 2 EXERCISE — "BUILD A CLIENT PITCH EXPLAINING AI"
Activity: Teams write a 2–3 paragraph pitch that covers:
  • The 4 types of AI (ML, DL, GenAI, Agentic)
  • Why they matter in advertising
  • How Paramount can apply them
  • One specific client benefit
Pitch Requirements:
  • ✔ Must use client language — not jargon
  • ✔ Must reference one competitor example
  • ✔ Must include one Paramount opportunity
  • ✔ Must end with "how this helps your campaign perform better"
Homework: Pitch Prep with AI Context — Take an actual upcoming client meeting and create an AI-enhanced strategy brief
🧰 SESSION 3 — USING AI IN YOUR DAY-TO-DAY JOB
Objective: Turn AI into a daily advantage. Each participant builds their own practical AI workflow they can use immediately.
AI Applications by Function

💡 SESSION 3 EXERCISE — "YOUR JOB, UPGRADED WITH AI"
Activity: Participants choose their actual role and build a repeatable AI workflow using pre-built prompt templates.
Outcome: Each participant leaves with a personal AI playbook that can be implemented the next day.
Homework: "30-Day AI Workflow Challenge" — Implement their personal AI playbook and track measurable results over 30 days
✅ SESSION 4 — 30-DAY CHECK-IN & REAL-WORLD APPLICATION REVIEW
Timing: 30 days after Session 3
Objective: Reinforce AI concepts through real-world application stories, troubleshoot challenges, and identify opportunities to scale successful workflows across teams.
1
Concept Quick Review
A rapid-fire refresher on the 4 AI types, key competitive examples, and Paramount's AI application areas.
  • Interactive polls and discussion on new AI tools discovered.
2
Application Showcase
Participants share results from their "30-Day AI Workflow Challenge", detailing successes, challenges, and quantified impact on their roles.
  • Focus on sales strategy, research, client communication, and campaign planning.
3
Group Discussion — Wins & Challenges
Facilitated dialogue on surprising AI benefits, tasks still better without AI, and identifying future training/tool needs.
4
Cross-Team Learning
Participants exchange successful AI practices and commit to adopting a new peer-shared workflow for the next 30 days.
  • Top workflows documented for a company-wide playbook.