Amazon drops new marketing AI solution

Hi ,

Amazon Web Services released a new AI marketing tool.

It generates campaign images by learning from your previous successful campaigns. Upload past assets. Describe new campaign. AI creates visuals matching your brand guidelines and proven strategies.

Uses Amazon Bedrock, OpenSearch, and Nova models. Bancolombia has been testing it for over a year.

This is AI that learns what worked before and applies it to new work.

First, here’s today's financial automation framework and regulatory compliance reality check (then see what AI-powered campaign generation means for marketing...)

🔥 Prompt of the Day 🔥

Financial Systems Automation: Use ChatGPT or Claude

Act as an expert Financial Systems Architect and Automation Specialist.

I have established the mindset and the environment. Now I need to automate the behavior to reduce decision fatigue and reliance on willpower.

Essential Details:

• Income Account: [WHERE REVENUE HITS]

• Profit Account: [WHERE PROFIT GOES]

• Operating Expenses Account: [WHERE EXPENSES COME FROM]

• Allocation Percentages: [YOUR PROFIT FIRST PERCENTAGES]

• Current Monthly Revenue: [AVERAGE AMOUNT]

• Banking Platform: [YOUR BANK OR TOOL]

Create one implementation workflow for profit allocations including:

• Allocation Schedule (step-by-step ritual for 10th and 25th of each month: logging in, calculating percentages, making transfers)

• Automated Rules (If/Then rules for banking: "IF revenue hits account [Income], THEN immediately transfer [X]% to [Profit]")

• Emergency Protocol (specific protocol when operating expenses exceed remaining cash - not "borrow from profit" but behavioral action plan to cut costs or boost immediate sales)

• Failsafe Checks (what to verify before each allocation)

• Progress Tracking (how to measure system effectiveness)

• Adjustment Triggers (when and why to modify allocation percentages)

If anything is unclear or you need additional details to improve your response, please ask me for clarification.

Automate behavior to eliminate decision fatigue.

✅ Tips & Tricks Thursday ✅

AI Regulation Navigation

The EU AI Act and state-level regulations are hitting businesses now.

Most companies ignore compliance until they face penalties.

The Problem

AI regulations are live. Not coming. Here.

EU AI Act went into effect. California, Colorado, and other states have AI-specific laws. Federal guidelines are evolving.

Most businesses using AI don't know what's required. They assume someone else handles it. They wait until legal sends a memo.

By then, violations have already happened.

Get Ahead of Requirements

Use AI to monitor regulation changes affecting your operations. Set up alerts for new laws in jurisdictions where you operate.

Audit your current AI usage against compliance frameworks. Document what AI you're using, where, and for what decisions.

Implement human oversight where regulations require it. Some AI decisions legally need human review before execution.

Keep compliance documentation updated as rules evolve. Static compliance fails. Regulations change. Your documentation must track them.

What This Looks Like

If you use AI for hiring decisions, document the process. Show human oversight. Prove non-discrimination.

If you use AI for customer service, ensure transparency. Customers may need to know they're interacting with AI.

If you use AI for content creation, understand copyright implications. Some jurisdictions require disclosure.

If you're in healthcare or finance, stricter rules apply. HIPAA and financial regulations intersect with AI laws.

Why This Matters

Penalties are real. EU fines reach €35 million or 7% of global annual turnover, whichever is higher.

U.S. state penalties vary but include fines, injunctions, and private lawsuits.

Beyond fines, non-compliance damages reputation. Customers care about ethical AI use.

The Action Steps

Document your AI systems now. What are you using? Where? For what decisions?

Identify high-risk applications. Hiring, credit decisions, healthcare, law enforcement—these face stricter rules.

Add human oversight checkpoints. Automated decisions need human review where required.

Create transparency protocols. Know when and how to disclose AI usage to customers.

Monitor regulation changes monthly. Laws evolve. Your compliance must keep pace.

Proactive Compliance Avoids Expensive Legal Problems

Most companies wait for legal trouble before addressing compliance.

That's backward.

Compliance isn't about avoiding innovation. It's about doing it responsibly.

The businesses that survive AI regulation are the ones building compliance into their workflows today, not after lawsuits arrive.

Did You Know?

AI can determine which married couples will divorce by analyzing their group photos at social events, identifying micro-expressions of contempt that predict relationship failure.

🗞️ Breaking AI News 🗞️

AWS Launches AI Marketing Image Generator That Learns From Previous Campaigns

Amazon Web Services released a new AI solution that generates marketing campaign images by learning from historical campaign assets.

The system uses Amazon Bedrock, OpenSearch Serverless, and Nova models to analyze previous campaigns and create new visuals aligned with brand guidelines.

What Changed

Marketing teams traditionally create campaigns from scratch or rely on static brand guidelines.

This solution analyzes previous successful campaigns, extracts what worked, and applies those insights to new image generation.

Upload past campaign assets. The system describes them using Amazon Nova Pro, generates embeddings with Titan Multimodal Embeddings, and stores them in OpenSearch Serverless.

When creating new campaigns, users describe what they want. The system searches previous campaigns for relevant references, generates an enhanced prompt combining new requirements with successful past elements, and creates images using Amazon Nova Canvas.

How It Works

Reference image processing: System analyzes historical campaign images, generates detailed descriptions, and creates vector embeddings.

Search and retrieval: When creating new campaigns, system performs similarity searches to find relevant reference images from past campaigns based on campaign objectives and target audiences.

Prompt enhancement: System combines user's campaign description with descriptions from selected reference images to create optimized prompts.

Image generation: Enhanced prompts feed into Amazon Nova Canvas to generate final campaign visuals.

Why This Matters

Historical campaign data identifies what works. Color schemes, compositions, visual techniques that drove engagement.

Maintaining brand consistency across campaigns becomes automated instead of manual.

Marketing teams scale production while maintaining quality. AI learns from past successes rather than starting from generic templates.

Real Implementation

Bancolombia, one of Colombia's leading banks, has been testing this approach for over a year.

Juan Pablo Duque, Marketing Scientist Lead: "Our goal was to directly tackle three major industry pain points: Long and costly iterative processes, difficulty maintaining context across creative variations, and lack of control over outputs. This allows us to validate new AI creations against our current library, ensuring we don't over-rely on the same visuals and keeping our brand's look fresh and engaging."

The bank uses it to streamline creative workflows while ensuring generated visuals align with strategic intent.

What Gets Better

Campaign creation speed: Generate visuals in hours instead of days or weeks.

Brand consistency: AI learns your successful visual patterns and applies them automatically.

Reference utilization: Past campaign investments become reusable assets instead of one-time work.

Strategic alignment: Filter references by campaign objective and target audience to ensure relevance.

Technical Components

Amazon Bedrock: Foundation model access (Nova Pro, Nova Canvas, Titan Multimodal Embeddings)

OpenSearch Serverless: Vector search for finding relevant reference images

AWS Lambda: Processing functions for image analysis, embedding generation, and indexing

Amazon S3: Storage for campaign assets

Amazon Cognito: User authentication

Step Functions: Orchestration of image processing workflow

Availability

Complete solution available in AWS GitHub repository with deployment instructions.

Requires AWS account with access to Amazon Bedrock models.

Implementation can be adapted to specific organizational needs and brand guidelines.

Over to You...

What would change if you could generate campaign visuals in hours instead of weeks?

Hit reply and tell me what you'd do with that time.

To speed advantages,

Jeff J. Hunter 
Founder, AI Persona Method | TheTip.ai

NEW: “AI Money Group” to Learn to Make Money with AI