Episode Details

There are many reasons to debate the ethics and implications of AI. But while we do that, hundreds of the world’s biggest brands are rushing to implement the technology into creative and coding workflows. At a time when shareholders are being unforgiving and policy making is volatile, business leaders are looking to AI to gain any advantage possible.

Jan Emmanuele is one of the experts that these Fortune 500 corporations rely on to identify and build GenAI creative workflow augmentations and automations. He works for Superside —whom you might remember from our episode with Philip Maggs (Listen here)— because they’re on the leading edge of creating an LLM that interprets your briefing process, design system, brand guidelines, marketing campaigns, and data to automate high-volume creative tasks.

In this episode, we focus on how and where AI is applied within organizations and workflows. It details how organizations can prepare themselves for implementing AI and how to address the core barriers and risks of the technology.

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What was most interesting about this conversation was his prediction that the adoption of AI will explode in enterprise orgs starting in 2026 and that it could continue into the 2030s. He believes that the value of AI in enterprise has already been proven and that more use cases exist than anyone can believe. That adoption thus far has only been limited because of legal and procurement policies.

If this is true, organizations that aren’t already at least planning for this workflow-automated future will soon be at a huge competitive disadvantage. Finding 10x augmentations of creative output is routinely achieved, and more will be possible for organizations with highly-structured and easily-repeatable workflows. The gains will be largest in orgs that leverage the uniquely-LLM capability of contextualizing outputs based on data. Examples include localizing campaigns to micro-niche segments or regions of the world.

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Headwinds will reduce the number of creatives earning a living wage

As we barrel towards the increasingly inevitable reliance on LLMs, it puts creatives in the uncomfortable position of fighting for their survival and protesting for what’s ethically correct.

The music industry is the canary in the coal mine in this battle. Many artists earn the majority of their income from their back catalogues and LLMS are effectively using those albums as mulch to improve generative capabilities.

On one side, you have an entire way of life being threatened; on the other, you have artists that will quickly need to learn how to master generative capabilities to become an indispensable musician regardless of the headwinds that will reduce the amount of music earning a living wage. As platforms get better, we’ll just generate the music and images we need instead of hiring professionals.

Overcoming the uncanny valley: Not being able to determine what was generated by AI

What has made all of us feel more comfortable has been that AI still sucks at a lot of creative tasks. Blooper reels and countless articles of AI creative ge