LLM Visibility Assessment

The Invisible #3

JE Dunn is the third-largest semiconductor fab GC in America — but when buyers ask AI for recommendations, the company barely exists.

#0
ENR Semiconductor Ranking
Top-tier credentials, industry-recognized
0%
Clean LLM Recommendation Rate
Only 3% of AI responses recommend JE Dunn without caveats
0%
Turner Unprompted Mention Rate
Turner dominates AI-generated answers about semiconductor GCs
$1B+
Estimated Annual Revenue at Risk
Lost opportunities from AI-mediated buying decisions
Executive Summary

The substance is there. The signal isn't.

A 700-question simulation across seven procurement stakeholders reveals a structural visibility gap that's costing JE Dunn opportunities before anyone picks up the phone.

The Visibility Deficit

57.6% of LLM responses contain confidentiality friction language. Only 8 unique third-party sources cite JE Dunn, versus 15+ for Turner. The AI information layer is structurally biased against JE Dunn.

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Seven Broken Paths

Each stakeholder on the buying committee encounters a different version of the gap. Procurement sees Turner in 42% of responses. The Owner's Rep faces 48% hedging language. Risk counsel barely encounters competitors at all.

Meet the committee

1 of 18

JE Dunn wins just 1 of 18 competitive visibility metrics against Turner Construction. The scorecard reveals systematic disadvantages across source authority, digital presence, and AI-specific findability.

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$1B+ Annual Revenue at Risk

Every year, the visibility deficit could cost JE Dunn over $1 billion in semiconductor construction revenue — the conservative gap between fair market share and realistic capture with current AI visibility.

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The Fix

Three pillars — Signal Amplification, Technical Credential Deepening, and AI Findability — deployed across three phases over 12 months. Starting with actions JE Dunn controls entirely.

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The Compounding Problem

Turner is investing in AI visibility. Skanska is entering the semiconductor market. LLMs reinforce their own biases. Every quarter unaddressed widens the gap — and the revenue at risk grows.

Understand urgency
The core finding: JE Dunn has the credentials, the track record, and the capabilities to compete for every major semiconductor fab project in America. But the AI systems now mediating buyer research don't know that — and they're actively directing procurement committees toward Turner Construction instead.
Spotlight

About This Assessment

Who We Are

Spotlight is an AI visibility firm. We help B2B companies control how they appear in the AI-mediated research layer that now shapes enterprise buying decisions — the LLM responses, AI summaries, and algorithmic recommendations that procurement teams increasingly rely on before they ever pick up the phone.

Why We're Credible

We do influence and visibility work every day for leading technology clients — Adobe, Google, IBM, Dell, Intel — helping them show up the right way when buyers and analysts go looking. This assessment applies the same proprietary LLM simulation methodology we use across technology and advanced manufacturing to diagnose JE Dunn's position in the AI information layer.

700 buying questions simulated across 7 stakeholder personas — the most comprehensive AI visibility audit available for the commercial construction market.
Methodology

How we measured this

A rigorous simulation of real-world AI-mediated buying behavior, designed to surface exactly what JE Dunn's target buyers see when they ask AI for help.

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Buying Questions Simulated
100 questions per stakeholder persona
0
Stakeholder Personas
CFO to Owner's Rep across the buying committee
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Source Citations Analyzed
Every claim traced to its information source
0
Trusted Voices Mapped
The influence network shaping committee perception

The Simulation

We constructed seven detailed buyer personas mirroring a real semiconductor fab procurement committee — from the CFO evaluating financial risk to the Owner's Representative validating references. Each persona was given 100 questions calibrated to their specific funnel stage and decision criteria, then processed through leading LLM platforms from the perspective of a neutral market analyst.

The Analysis

Every response was classified across six analytical dimensions: competitive positioning, source authority hierarchy, confidentiality friction, engagement signals, stakeholder-specific patterns, and trusted voice identification. The result is the most comprehensive picture available of how AI systems represent JE Dunn to the buyers who matter most.