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When tools like Claude went mainstream, many knowledge workers felt uneasy. For freelance copywriter Leigh Ann Shelton, the impact was immediate and financial. Shelton’s job was to do what good copywriters have always done: translate a client’s voice into persuasive marketing language. Websites. Campaigns. Brand messaging. The kind of work that depends on tone, clarity, and emotional nuance. And then, almost overnight, her clients discovered AI.
Suddenly, companies that once hired her to craft product descriptions or marketing emails were experimenting with generative AI tools instead. Some decided “good enough” machine-written copy was cheaper. Others hired lower-cost writers who were using AI to boost their output.
Her field, commercial copywriting, was one of the first white-collar professions to feel direct economic pressure from generative AI. Shelton faced a stark choice: resist the technology and risk fading out, or learn to work with the very systems threatening her livelihood. She chose the harder, more forward-looking path.
What makes Shelton’s story powerful isn’t that she instantly mastered AI. It’s that her evolution was messy, experimental, and very human. At first, she approached AI defensively. Could she train tools like ChatGPT to mimic her tone? Could she use it to draft first versions faster, then layer in her expertise? Her early experiments were tactical: productivity boosts to help her compete in a market where speed and price were shifting.
But over time, her relationship to AI matured. Instead of asking, “How do I stop AI from taking my work?” she began asking, “What can I do that AI alone can’t?” That shift reframed her role.
She stopped seeing herself purely as a producer of words and started positioning herself as:
In other words, she moved up the value chain. AI handled more of the raw generation; she owned the judgment, refinement, and alignment with real human goals.
One of the key ideas in How to AI by Christopher Mims, is that experts benefit most from AI, not beginners. Shelton’s journey is a vivid example of that principle in action.
A novice with AI can produce generic copy quickly. But Shelton’s years of experience meant she could:
AI didn’t make her expertise irrelevant. It made her expertise more leveraged. Her professional value shifted from typing every sentence to shaping the direction, quality, and meaning of the work.
Shelton’s biggest transformation wasn’t gaining new technical skills. It was psychological. She stopped defining herself by the task (writing every word from scratch) and started defining herself by the outcome (effective communication that drives results). That distinction gave her room to evolve. Where AI commoditized basic copy, she leaned into:
Rather than compete with AI on volume, she differentiated on judgment, empathy, and context, areas where machines still rely heavily on human direction.
Shelton’s experience isn’t just about copywriting. It’s a template for many professionals now standing at a similar crossroads. Her story shows that:
She didn’t outrun AI. She learned to run with it, then repositioned herself where human judgment still leads and AI follows.
That’s why Shelton’s journey stands out in How to AI. She isn’t a tech insider or a corporate executive. She’s a frontline knowledge worker who felt the pressure first and turned it into a reinvention story. For anyone wondering whether AI will make their skills obsolete, Leigh Ann Shelton offers a more nuanced answer: Not if you’re willing to redefine what your expertise really is.
Originally published at Forbes