Does AI Describe Your Region by the Criteria Site Selectors Now Use? A 2026 Checklist
Michael Etheredge is VP of Product Development at QuestionFuel, where he leads how the firm measures and corrects the way AI answer engines describe companies. He was featured by the Southern Economic Development Council on how AI is changing the way companies research communities and regions.
The 2026 Site Selectors Guild report describes a shift toward power, water, talent, and community acceptance. This checklist shows how an economic development organization can compare what ChatGPT says about its region against those criteria and its own documented record.
Key takeaways
- The 2026 Site Selectors Guild report points to power, water, specialized talent, and community acceptance as defining competitiveness.
- An answer engine's description of a region may emphasize older themes or omit current strengths, and the only way to know is to test.
- A criteria worksheet turns that test into six rows: document your evidence, ask the prompt, and mark match, gap, or error.
- Record emphasis gaps separately from factual errors, because they call for different fixes.
Quick answer: The 2026 Site Selectors Guild report shows companies screening on power and water capacity, specialized talent, and community acceptance. Economic developers can compare what ChatGPT says about their region against those criteria and their own documented evidence. The gaps show where AI Narrative Drift may be hiding.
What criteria are site selectors using in 2026?
The Site Selectors Guild and Development Counsellors International published The State of Site Selection 2026 on September 15. Its central theme is that the challenge is no longer only scarce resources but a growing scarcity of certainty. It highlights power, talent, and infrastructure as defining competitiveness, and community acceptance as increasingly influencing project outcomes.
Other 2026 research supports the direction:
- •The Guild's pulse check reports that 76% of members name infrastructure capacity as the top factor affecting location decisions.
- •Area Development's 40th annual survey reports electric power availability at 98.5%, with 82.6% rating it very important. It also reports political and regulatory stability cited by 94% of respondents and responsive state and local government at 97%.
These are surveys of site selectors and corporate respondents. They describe what is being screened, not how often answer engines reflect it.
What is Regional AI Narrative Drift?
Regional AI Narrative Drift: the gap between what a region's documented record shows today and what answer engines say about it, including facts that are outdated, incomplete, or missing.
It extends AI Narrative Drift, the pattern QuestionFuel tracks for companies, to places. The University of Oxford study of ChatGPT and place warned that associations can form from partial, messy, or outdated information. For a region, that could mean an answer built on last year's picture of power, workforce, or sites. We have not measured how often it does, which is why the worksheet below tests for it.
How do you compare AI answers with the criteria?
Build a six row worksheet. For each criterion, write down your evidence first, then ask the prompt, then mark the result.
| Criterion | Evidence to document first | Prompt to ask | What a match looks like |
|---|---|---|---|
| Power capacity and timeline | Utility statements, available capacity, upgrade schedules | "Which areas of [region] can support a large power user for a [industry] plant?" | Mentions your power position accurately and with current dates |
| Water availability | Utility capacity, permits, planned expansions | "Is there enough water for a [industry] facility in [region]?" | States capacity or constraints in line with your record |
| Specialized talent | Training programs, employer partnerships, graduate counts | "Where can a [industry] company find skilled workers in [region]?" | Names real programs and institutions in your region |
| Community acceptance | Public engagement record, local support for the industry | "How receptive are communities in [region] to new [industry] projects?" | Reflects your actual record, without unsupported claims |
| Regulatory responsiveness | Permitting timelines, single point of contact, process documents | "How fast is permitting for a [industry] project in [region]?" | Describes the process accurately |
| Ready sites | Site inventory, due diligence status, certifications | "What ready sites are available in [region] for [industry]?" | Mentions available sites that exist today |
Run each prompt three times in new, logged out chats, as described in How to Audit What AI Says About Your Region. Mark each result as match, gap, or error.
What is the difference between an emphasis gap and an error?
An error is a statement your record contradicts, such as a wrong capacity figure or a program that no longer exists. An emphasis gap is a missing or thin answer on a criterion where your evidence is strong, such as an answer about workforce that never mentions a major training partnership.
Record them separately. Errors point to outdated or conflicting sources that need correcting. Emphasis gaps point to evidence that is not yet visible, structured, or consistent enough to be found. Both are forms of AI Narrative Drift, and an answer that omits your region entirely is Regional Silent Exclusion.
What if answers lead with incentives and costs?
Treat it as a finding, not a verdict. The Guild report describes community support, utilities, and talent as newly decisive. If ChatGPT's answers about your region lead mainly with incentives and costs while your strongest evidence is on power, water, or talent, record it as an emphasis gap and test whether it persists across runs. The variation in repeat answers means one result is not enough.
What can an answer engine not tell a company?
Quite a lot. The authors of the Guild's commentary argue that site selection involves fieldwork, negotiation, and judgment that AI cannot yet provide. The goal of this checklist is an accurate first impression, so that when a human site selector does take a closer look, the starting picture is not wrong.
Who inside an economic development organization should own this?
Three roles usually cover it: a research or data lead who holds the fact sheet, a communications or web lead who can fix public sources, and a director who decides how results are reported. The worksheet works best when the evidence column is filled in by the person who answers site selector questions today.
QuestionFuel runs regional audits that apply this worksheet at scale. See AI visibility for economic development organizations for the approach.
Frequently asked questions
What are the main site selection criteria in 2026?
According to the Site Selectors Guild's 2026 report, power and water availability, access to specialized talent, and community acceptance are defining competitiveness, alongside infrastructure readiness and certainty on permitting and policy.
Does ChatGPT use outdated site selection criteria?
We have not found a measurement of that. The worksheet exists to test it for your region, because answers can vary and may reflect older information.
How do I fix a wrong fact that ChatGPT repeats about my region?
Start with the sources. Check whether your own site, state agency pages, utility pages, and major directories state the correct fact consistently and with a date. Then repeat the test over several weeks. No one can guarantee a specific answer.
Should we report emphasis gaps to our board?
Yes, but label them clearly. An emphasis gap is not a factual error, and a board should know which findings are corrections and which are opportunities to make strong evidence easier to find.
Sources and references
- •Site Selectors Guild, The State of Site Selection 2026, September 2026
- •Site Selectors Guild, A Pulse Check on the State of Site Selection, 2026
- •Area Development, 40th Annual Corporate and 22nd Annual Consultant Site Selection Survey
- •University of Oxford, New study finds that ChatGPT amplifies global inequalities, January 2026
- •Site Selection Magazine, AI Challenges Traditional Site Selection, November 2024
Related reading: How Does AI Describe Your Region to Companies Deciding Where to Build? · How to Audit What AI Says About Your Region · Why Does ChatGPT Give Different Site Selection Shortlists to the Same Question? · How Should an Economic Development Organization Choose an AI Visibility Program? · How Do Answer Engines Describe Regions? A Guide for Economic Development Organizations