👋 Greetings earthlings,

Emma here from Spark AI. Over the past few months, I’ve noticed something important happening inside creative production agencies - while many creative agencies are still stuck in the messy middle of AI adoption, production partners are quietly reorganising themselves at speed.

In this edition I’m spotlighting two examples - Tuncarp and POD LDN - who are already reshaping pricing models, redesigning roles, and rebuilding delivery workflows for the AI age. They’re moving fast, not by trying every new tool, but by systematically upskilling teams and cultivating a culture of innovation. They are doing this at speed because they have to; margins demand it. 

This is in contrast to what the majority of 149 creative agencies told us in our recent research with The Industry Club – high excitement, low consistency, lots of tools, no shared way of working. Here’s a snapshot of what 149 leaders of independent, network and in-house creative agencies told us about their AI maturity:

Across all agencies we work with, the ones pulling ahead aren’t the ones experimenting the most—they’re the ones treating AI as a business transformation programme, not a collection of tools. They understand that pricing, talent, workflows and margins only shift when the organisation shifts.

Below, you’ll find a breakdown of what Tuncarp and POD LDN have implemented and how they did it.

Table of Contents

• 1. The Commercial Shift

• 2. The Talent Shift

• 3. Next steps your agency

1. The Commercial Shift

How Tuncarp built an AI-enabled content studio (and kept their margins high)

Tuncarp is a production and white-label partner founded by Chris Murphy (ex-Ogilvy and Publicis). They operate across Manila and the UK, with around 40 staff - most in traditional production, and a fast-growing AI team.

They didn’t start with a grand AI strategy. Like most of us they started with curiosity - but what stood them in such good stead was what they did next: they chose to invest deliberately in people.

Four pillars of capability

Tuncarp built an AI function across four distinct roles:

1. AI Strategy
   Research, UX artefacts, personas, planning. This is the “thinking” layer.
   

2. AI Operations
   Working with ops to automate onboarding, HR, briefing and delivery.
   All the unglamorous but essential work that saves hours every week.
   

3. AI Creative
   Designers who work across image, video, storyboarding and final edits.
   One person now spans what used to be separate design and motion roles.
   

4. Engineering
   A developer using AI to build internal tools and explore productisation.
   

The talent behind this?

Their entire model depends on upskilled people. Without that team capability, none of this works - not the new workflows, not the pricing, not the margins.

The commercial impact

Tuncarp can now create high-end video work for around £5k - work that used to cost £20k in traditional production. Because they price by asset, not hours, they’re maintaining 70–80% margins.

They’ve now been appointed Publicis’ AI content studio, proving that boutique specialists can plug directly into global networks if they have the capability.

💡 Our takeaway:

You cannot decouple pricing from upskilling. If your team can’t use AI confidently, consistently and creatively, you can’t shift your commercial model - and your margins stay trapped in the old world.

2. The Talent Shift

How POD LDN are hiring for aptitude, not years of experience

POD LDN started exploring AI two years ago. Now it’s embedded across post-production, with a dual-track talent model that combines retraining and new capability.

Like Tuncarp, their biggest breakthrough wasn’t subscribing to a specific AI tool - it was a hiring method.

The AI film competition

Instead of reading CVs and hoping for the best, they asked candidates to make an AI-generated film. They weren’t looking for pedigree or years of experience. Just: show us how you think and what you can make.

It removed bias, surfaced new types of talent, and provided a much clearer signal than a portfolio.

Retraining and reskilling their existing team

POD also protected time for their internal artists to upskill - more than just watching tutorials, instead time to experiment with purpose, reflect, and push the tools in meaningful ways.

They now expect baseline AI literacy in every role, even client services.

Again, the same message: everything depends on capability.  If your team can’t use these tools with skill, judgement, creativity and consistency, your business model stays stuck.

💡 Our takeaway:

AI is less about hiring unicorns and more about creating conditions where your existing team can evolve - and evaluating new talent based on aptitude, not history.

Next steps for your agency

You cannot fix your pricing, your workflow or your margins without fixing your team’s capability first. Upskilling and building out your new AI enabled workflows is the hinge everything else swings on.

It is the foundation for:

• consistent delivery

• quality control

• commercial clarity

• faster turnaround

• less internal resistance

• better pitches

• and, ultimately, a sustainable 2026 AI roadmap

The choice of AI tools you subscribe to doesn’t matter if your people can’t use them. Your SOPs don’t matter if no one follows them. Your pricing won’t change unless your team can confidently talk about how you use AI and deliver in new ways.

This is why these production agencies are pulling ahead. They’re not just using AI - they’re skilling up, building out new ways of working, and evolving with it.

Three ways to apply this inside your agency

1. Re-think your next hire

You may not need another designer or PM. You may need someone with the aptitude to live comfortably between concept, craft and code.

2. Audit your commercial model

AI accelerates certain types of work (localisation, cut-downs, pitch visualisation). These could become fixed-price assets if your team is upskilled enough to deliver consistently.

3. Test for aptitude

Instead of relying on CVs or portfolios alone, give shortlisted candidates a small, structured AI task. You’ll immediately see who has curiosity, adaptability and commercial judgement - qualities that matter in an AI-enabled team.

Some simple ideas on how to test for aptitude:

If you’re building your 2026 AI plan, we can help

If you’re ready to turn energy into structure and scale your team’s capability, here are two practical next steps:

Join Spark’s AI Accelerator

Our 3 month AI Accelerator Programme is built specifically for agencies who want to:

• upskill teams without burning them out

• define and build clear AI workflows and SOPs

• figure out how AI-enabled delivery fits into their commercial model

• create alignment across sceptics and believers

• stop the chaos of everyone doing their own thing

We’ve helped 60 agencies move from enthusiasm to structure this year.

Read our #1 Bestselling Book Shift - AI for Agencies

And if you want to do more reading around the subject first, our new #1 bestselling book Shift - AI for Agencies takes everything we’ve learned from working with 60+ agencies and turns it into a clear, practical roadmap you can use right away - from capability building to workflow design to commercial models.

If you’re shaping your 2026 plan, this is the handbook you’ll want next to you.

That’s all for today. Let me know if you found this helpful below, I always love to hear. See you next week!

Emma 

Co-founder and CEO of Spark AI

About Spark AI

Spark AI empowers creative and brand leaders turn AI curiosity into confidence through structured training and business transformation.

We have worked with 60+ agencies running AI Fundamentals workshops and AI Accelerator programmes based on our # 1 bestselling book Shift - AI for Agencies.

Trusted by Oxford University Saïd Business School and backed by Innovate UK.

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