In the age of doubt, people still believe people.
People trust people like them. That’s never changed.
Before the demo, before the sales enquiry; buyers look for someone who faced the same problem and came out the other side. They always have. But when AI slop is everywhere and seeing is no longer believing, authentic customer stories aren’t just valuable. They’re essential.
More with less
Advocacy teams have fewer people, tighter budgets, and shorter cycles. The demand for customer stories is growing, but the capacity to produce them is shrinking. And immediacy matters; by the time a story is finally published, the moment it was meant to serve may already have passed.
So teams reach for AI. And much of the output is indistinguishable from everything else. It reads like it was written by nobody, for nobody. It erodes exactly the trust that customer advocacy is supposed to build.
Editorial judgment
The best advocacy practitioners have always known something the AI debate has obscured: the skill was never just the writing. It was the editorial judgment. Knowing which detail makes a story land. Knowing when a statistic does more work than a quote. Knowing what the customer actually meant, even when they didn’t say it clearly.
AI hasn’t made that judgment less valuable; quite the contrary, because now there is so much more raw output to apply it to.
Editor-Enhanced Content. A new category for the age of AI-assisted storytelling.
Not human. Not machine. The best of both; in the right proportions, for the right story, at the right level.
EEC is what happens when skilled editorial judgment is applied to AI-accelerated generation. Not a workaround. A new standard.
There is no single correct ratio of human to AI in EEC. The blend is a function of two things: the type of output, and the stakes of the story. EEC makes that calibration explicit and intentional.
EEC doesn’t reduce the editor to a proofreader. It changes what the editor is responsible for – and raises the ceiling on what they can produce.
Deciding what material the AI works from. Interview selection, quote curation, brief construction. The quality of AI output is a direct function of the quality of the editorial setup.
Choosing which story shape serves this audience. A technical win, a transformation narrative, a competitive displacement; each demands a different architecture.
Ensuring the customer sounds like themselves. The moments where AI flattens something real are exactly where editorial judgment matters most.
Holding the line on what the customer actually approved, what the brand can claim, and what the legal team would stop. Compliance that comes from understanding, not checklists.
Your expertise becomes the differentiator, not the bottleneck. EEC makes it possible to do more stories without losing the judgment that makes them land.
EEC is a new service line and a new value conversation. The ability to run an editorially-led AI workflow is a premium skill – not a threat to what you do.
EEC gives you a language for AI that isn’t threatening – to your team, your agency partners, or your customers. It’s not AI replacing humans. It’s humans getting better tools.
A framework that scales
EEC doesn’t replace what great advocacy content teams, agencies, and practitioners have built. It names and systematises the judgment they were already exercising – and gives it a framework that scales.
If you have 25 years of practitioner knowledge, EEC makes that knowledge more transferable, more teachable, and more scalable than it has ever been. The experience doesn’t become obsolete. It becomes the thing that separates good EEC from great EEC.
Editor-Enhanced Content
is the principle behind everything Proofpoints produces. AI handles volume and structure. Human editorial judgment shapes quality. The blend varies by story – and that's the point.
Proofpoints is being built around the EEC model. If you want to help shape what that looks like in practice, the Founding Originals invite is open.
Join the Founding Originals →