RADAR108

AI Skills Are Not a Differentiator Anymore

For a brief moment, AI skills meant something.If you knew how to prompt well, automate workflows, or integrate tools into your day-to-day MAAD work, you stood out. You were early. You were curious. You were valuable.That window closed faster than most people realize.There is a concept in economics called signal inflation. When too many people adopt the same signal, its ability to distinguish between candidates collapses.This has happened before.Knowing Excel once signaled analytical maturity. Knowing social media once signaled digital fluency. Knowing basic SEO once signaled marketing competence. AI followed the same curve, but at record speed.In MAAD roles, AI tools spread through organizations almost frictionlessly. The learning cost is low, the interfaces are forgiving, and the upside is immediate. That creates rapid standardization.Within a year, “I use AI” stopped telling hiring managers anything meaningful.Everyone does.So the differentiator shifted quietly. From a signaling theory lens, what matters is not whether you use AI, but where you intervene.Two people can use the same tool and produce equally polished output. The difference shows up earlier in the process.Who decided what question to ask the tool Who rejected outputs that looked right but felt wrong Who knew when automation would erase nuance instead of saving timeThese decisions are invisible unless someone knows how to look for them. Most hiring systems do not.This is where MAAD work becomes structurally different from many other functions. In marketing, analytics, design, and advertising, tools do not create advantage on their own. They amplify intent. They accelerate direction. They magnify judgment.Which means if the underlying thinking is shallow, AI simply helps you be wrong faster.This is uncomfortable because it breaks the tool-based narrative people prefer. It is easier to say “learn this platform” than to say “learn how to decide what not to automate.”There is also a sociological layer here.As AI became normalized, teams began using tool fluency as a proxy for ambition. Candidates who talked confidently about AI sounded modern, adaptable, forward-looking. But proxies fail when the underlying trait is no longer scarce.At that point, everyone looks ambitious. Everyone sounds current. Everyone claims leverage. The hiring signal becomes noise.What replaces it is not another tool.It is interpretive skill.Can you explain why an AI-generated insight should not be acted on yetCan you recognize when pattern recognition is masking causal understanding Can you articulate the risk of scaling something before it has been properly framed These are not AI skills. They are human filters applied to machine output. They also cannot be faked easily.In MAAD roles, seniority is no longer defined by tool access or technical range. It is defined by intervention timing.Junior use looks like “What can I automate?” Senior use looks like “Where should automation stop?”That difference does not show up in résumés. It shows up in conversations, in how people narrate their work, and in how they explain trade-offs.Which is why many candidates feel confused.They keep adding tools, but they do not feel more differentiated.That feeling is accurate.AI did not flatten the playing field. It raised the floor.Once the floor rises, standing out requires operating above it. Not louder, not faster, but more selectively.The MAAD professionals who will matter most in 2026 are not the ones who mastered the tools first.They are the ones who know when to distrust them.

Posted on 2/25/26, 12:00:00 AM.000

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