The Black Swan Problem
AI is trained on patterns. And most career data it learns from looks “normal” on paper:
linear progression
predictable titles
standard credentials
easy-to-verify timelines
If your path is unconventional: fast-moving, built through acquisitions, self-taught, doesn’t follow predictable patterns, AI may treat your work history as improbable.
Now you might be thinking improbable seems like a strange word to use, but out of billions of data points, it considers variations from known patterns as outliers. Statistically insignificant. What I call a Black Swan.
When AI considers you a black swan it doesn’t know what to do with you. It goes out of its way to find a template that you fit.
The Authority Gap
There’s a difference between:
your real-world authority (what you’ve done, what you’ve delivered, what your network knows), and
AI-recognized authority (what the system can connect, corroborate, and confidently attribute to you).
That gap is where people get stuck.
Because even if your expertise is real, AI won’t surface what it can’t verify. And if AI won’t surface you, the right people can’t find you.
The AI Authority Gap
What AI Does When You Don’t Fit the Template
When AI has low confidence in who you are, it often starts “helping” in the worst way:
Filling gaps with assumptions
Misattributing your experience
Blending your identity with other people who share your name
Pulling in stronger, older, or more “credible” sources, even when they’re wrong
Downgrading your authority because it can’t reconcile conflicting signals
The result is brutal: Your uniqueness gets stripped away, you get shoved into a generic box, and then you get penalized for not fitting it.
Why Your Current Signals Might Not Be Winning
Even if you’re posting, updating LinkedIn, and publishing content, those may be treated as “lower authority” signals compared to things like:
Archived conference pages
Old employer references
Third-party databases and directories
Outdated bios or titles that still exist online
Other people with the same name
So the system creates a story. But it’s the wrong story.
Identity Islands: How One Person Becomes Five
A common failure is fragmentation: AI can interpret one real person as multiple “versions” of that person.
Not because you’re inconsistent on purpose, but because your identity and proof live in disconnected places—like islands AI can’t confidently link together.
When those islands aren’t connected, AI can’t consolidate you into one trusted entity. And when it can’t consolidate you, it won’t confidently recommend you.
Identity Islands vs Identity Continents: How AI and the Knowledge Graph See Your Work History
Why Fixing Google Often Comes First
Many AI systems pull identity and authority signals from the same foundational sources. In practice, Google’s understanding of you often becomes an upstream identity layer that other systems inherit. Search and AI Discovery Platforms like ChatGPT Web Search, Perplexity, Google AI Overviews, and Distribution Platforms like LinkedIn and YouTube. All are influenced by the data in Google’s Knowledge Graph.
So when Google gets you wrong, you end up playing whack-a-mole everywhere else.
Fix the foundation, and the downstream systems become easier to influence.
What Changes When AI Gets You Right
When your identity signals consolidate, and your authority becomes verifiable:
You stop getting treated like an “opinionated stranger.”
You get surfaced more consistently in AI-mediated discovery
You’re more likely to be cited, referenced, or recommended
The right opportunities find you faster, and you’re trusted before the first conversation
Your expertise becomes legible to people AND to machines
In other words, you go from “best kept secret” to consistently surfaced.
The Real Takeaway
This is an authority verification problem.
If AI can’t verify who you are and what you’re credible for, it will either ignore you or build a version of you it feels safer trusting. And that version can quietly influence available opportunities long before people ever reach out.
Until next time,
Tia A. Williams, Principal Systems-Thinking Architect
Ex VP A Cloud Guru (Acquired by Pluralsight for $2B) / SVP CFI
I have 28 years of experience in datacenter, cloud infrastructure, EdTech SaaS, and executive leadership. Author of Born a Statistic. Built to Be a Leader. Founder of Solo Business Advisor and The Leadership Equation. I build systems that make expertise visible, trusted, and impossible to ignore.