AI DUNN Right Weekly - Issue #15

Big Story

The skills that'll make AI operators rich in 2026

Here's what's happening that everyone's talking about but most are missing...

If 2025 was the year of AI promise, 2026 is the year AI has to deliver real value on business metrics.

That simple shift changes everything for anyone working with AI... from product leads and engineers to revenue teams and consultants.

Three things are now clear:

• Prompt engineering is no longer a moat - Everyone can write prompts. That's not a skill anymore, it's table stakes.

• AI operators will out-earn AI generalists - Knowing AI broadly matters less than knowing how AI fits into specific workflows, industries, and business problems where money's actually leaking.

• Vertical AI beats generic tools - Companies solving problems for healthcare, legal, finance, or supply chain will win over tools that try to do everything for everyone.

Here's what I think...

The bar for success ain't novelty anymore. It's business impact. Tools that produce ROI get adopted quickly. Teams that can quantify value and show business improvement win.

Investors are warning of a market cleanup in 2026. AI companies without clear economic moats, solid revenue paths, or defensible technology will get weeded out. The early gold rush phase where easy capital flowed to any AI idea? That's ending.

This is actually good news.

It reveals where real value is being created and pushes resources toward operators who can actually build, deliver, scale, and measure performance. Not just talk about it.

The skills that'll pay in 2026:

• Contextual AI design • AI orchestration and systems integration • Governance and risk management • Business outcome modeling • Human-AI collaboration design

Not theory. Execution.

The operators who can combine technical capability with business savvy will be the ones commanding the best roles, projects, and opportunities.

What's New This Week

China built GPT-4 performance at a fraction of the cost

DeepSeek just published research showing they matched GPT-4 results using way less compute and energy.

Their method is called Manifold-Constrained Hyper-Connections.

Why this matters...

The US banned China from accessing Nvidia's best chips, thinking it would slow them down. Instead, it forced them to get smarter about efficiency.

DeepSeek's R1 model last year cost pennies compared to what OpenAI spent. Now they're dropping R2 in February with the same playbook... build better with less.

When you can't brute-force a problem, you're forced to actually solve it.

Here's what happened:

• Silicon Valley spent years optimizing for scale - more compute, bigger models, more data • China couldn't do that, so they optimized for efficiency instead • And now they're building better AI with less

For business owners, this means: faster and cheaper AI is coming. Tasks where cost or speed made AI impractical? Those barriers are disappearing.

Google's deepfake detector just went live

Google launched video verification in the Gemini app this week.

Upload a video. Ask "Was this generated using Google AI?" Gemini scans for SynthID watermarks embedded in audio and visual tracks. Tells you exactly which segments contain AI-generated elements.

Example response... "SynthID detected within the audio between 10-20 seconds. No SynthID detected in the visuals."

SynthID is an imperceptible watermark embedded directly into AI-generated content during creation. It survives compression, editing, format changes, and minor modifications.

Here's why this matters now:

• Deepfakes are getting better • AI-generated content is everywhere • Without verification, you can't trust what you see • Courts need provenance for evidence • News organizations need to verify sources • Platforms need to label synthetic media

Google's building the infrastructure for that verification. By end of 2026, most major AI platforms will have verification built in.

Amazon wants Alexa to replace your apps

Amazon expanded Alexa+ with four new integrations launching in 2026:

• Angi - Get home service quotes • Expedia - Book hotels through voice • Square - Schedule salon appointments

• Yelp - Search local businesses

These join existing integrations like OpenTable, Ticketmaster, Thumbtack, and Uber.

The goal? Turn AI assistants into app platforms. Instead of opening 10 different apps, you describe what you want and Alexa handles execution across multiple services.

The challenge... getting people to change behavior.

Most users engage with services through web or mobile apps. Voice needs to be easier, not just different. If AI assistants feel like ad platforms instead of helpful tools, users will reject them.

Early data shows "strong" engagement with home and personal service providers. People are actually using these integrations, not just testing them.

Tool of the Week

Content repurposing that actually saves time

This week I'm highlighting three tools that turn one piece of content into multiple formats without manual work:

• Repurpost - Turns your YouTube videos into Twitter threads. Drop in a URL, get a thread that matches your voice. No manual rewriting.

• Video To Blog - Converts videos into blog posts using GPT. Same content, different format. Reach people who prefer reading over watching.

• Stravo AI - All-in-one content creation platform with custom brand voices. Create blogs, ads, social posts... all sounding like they came from the same strategic brain.

If you're creating video content and letting it sit in one place, you're leaving value on the table.

These tools help you stretch one piece across multiple platforms without starting from scratch.

Quick Hits Worth Your Time

→ Wall Street is questioning whether AI is a bubble as tech spending soars and layoffs persist. Investors want to see revenue, not just research.

→ Investors predict AI is coming for labor in 2026, with experts warning AI could replace up to 800 million jobs worldwide by 2030.

→ Libraries are using AI that predicts which books will become bestsellers by analyzing reading speed and how often early borrowers pause at certain passages.

→ AI analyzing bird migration patterns discovered they deliberately fly through areas with specific magnetic anomalies that act like highways in the sky.

→ Smartphones' AI intentionally drains battery faster when you're near phone stores, using location data and usage patterns to encourage upgrades.

Prompt of the Week

90-Day AI Implementation Roadmap

Stop experimenting forever. Actually implement AI in your business in 90 days.

Act as an AI transformation specialist. Create one 90-day implementation roadmap for adding AI to [MARKETING AREA] that delivers results fast.

Essential Details...

- Marketing Area... [CONTENT/EMAILS/ADS/SOCIAL/ANALYTICS]

- Current State... [WHAT YOU'RE DOING NOW]

- Goal State... [WHAT YOU WANT IN 90 DAYS]

- Budget... [TOTAL AMOUNT AVAILABLE]

- Team Skill Level... [BEGINNER/INTERMEDIATE/ADVANCED]

- Top Priority... [#1 THING TO ACHIEVE]

Create one roadmap including...

Days 1-30 (Quick Wins)

- Which AI tool to start with

- First 3 tasks to automate

- Team training basics

- Success metrics to track

Days 31-60 (Build Systems)

- Full tool integration

- Workflow changes needed

- Advanced training

- Quality checks

Days 61-90 (Scale Up)

- Optimize what's working

- Expand to more tasks

- Measure ROI

- Plan next phase

Also include...

- Weekly team check-ins

- How to handle resistance

- Monthly progress reports

Why this works...

Most companies stay stuck in pilot mode forever. They test AI tools but never actually implement them into workflows.

A 90-day roadmap forces action. Quick wins build momentum. Systems thinking prevents tool sprawl. Clear metrics show whether it's working.

Get AI working in your marketing in 90 days, not someday.

My Take

The biggest news this week ain't a new tool or flashy model.

It's the fundamental shift in what the market demands from AI.

2025 was "look what AI can do." 2026 is "prove it made us money."

That changes everything.

If you can't connect AI to measurable business outcomes, you won't get budget. If you can't show ROI, pilots get canceled. If you can't quantify impact, you're just playing with expensive toys.

The operators who win in 2026 will be the ones who speak both languages... AI capabilities and business metrics. Not one or the other. Both.

They'll know:

• How to design contextual AI systems • How to integrate models with business logic • How to govern AI deployments • How to measure outcomes that matter

This ain't about prompts anymore. It's about operational infrastructure.

And here's the interesting part... constraints force creativity:

• Silicon Valley had unlimited resources and optimized for scale • China couldn't do that, so they optimized for efficiency • And now they're building better AI with less

The teams with unlimited resources often build slower than teams with constraints. Abundance allows laziness. Constraints demand solutions.

That's a business lesson, not just an AI lesson.

The operators who understand that... who can build systems that deliver measurable value... those are the ones who'll capture the opportunities in 2026.

That's it for this week!

What AI implementation have you actually completed, not just piloted? Hit reply and let me know.

Jackie