How Should an Economic Development Organization Describe Incentives So Site Selectors and ChatGPT Get Them Right?
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.
Incentives are a late stage topic in a site search, but they are the part of a community's story most likely to be quoted as a single number. This guide shows how an economic development organization can describe each incentive program with its conditions, timeline, and date, and how to check what ChatGPT says about it.
Key takeaways
- Incentive negotiations typically happen in the third phase of a site search, after screening and site visits have narrowed the field.
- A large headline figure can hide the conditions behind it, such as tax credits that can only be used against a company's own income tax liability.
- A consultant writes that a six month approval process is a liability, not an incentive, so approval time belongs next to the amount.
- We found no published study of how answer engines describe incentives, so the practical step is to publish one dated record and test it.
Quick answer: Describe each incentive as a dated record that states the program name, who qualifies, what the amount is made of, how it is claimed, how long approval takes, and what conditions apply. Then ask ChatGPT about it three times, and mark each answer a match, a gap, or an error against that record.
When do incentives matter in a site search?
They matter most late, after the field has been narrowed.
A University of North Carolina School of Government article, published November 7, 2025, describes site selection in three phases. Incentive negotiations take place in the third phase, as the company chooses among finalists. The article adds that incentives "can help sway the final decision at that stage."
That does not make incentives unimportant earlier. In the same article's reporting of Area Development's 2024 surveys, 98% of site selection consultants and 87.8% of corporate respondents rated state and local incentives as very important or important. Area Development's 2026 survey says cost has been reframed, and that incentive competitiveness "remains near the top of the rankings," though no longer the organizing principle of a location decision.
The practical reading is that incentives are screened for, discussed late, and often quoted early as a single number. Getting the description right protects you at every stage.
Why do incentive summaries go wrong?
Because a headline figure rarely says what the number is made of or who can actually use it.
Daniel Young, Director of Economic Development at Moore & Van Allen PLLC and a former executive director of the South Carolina Coordinating Council for Economic Development, gives an example in an Area Development column published in Q1 2026. For a 200 job project looking in the most rural areas of South Carolina, he writes that a state level package might be shown at around $29 million. The same project in an urban center might be around $1.5 million, because the job credit drops from $25,000 per job to $1,500 per job for five years.
His larger point is about conditions. He describes a company that thought the state would write a check for $25,000 a job every year for five years, when the credits could only be used against the company's own corporate income tax liability. In his words, "Incentives are important but should be considered the icing on the cake, not the reason the cake was made."
That is one author's example from one state, and the figures are his illustration, not a current program summary. The lesson applies anywhere: a number without its conditions invites a wrong conclusion, from a person or from an answer engine.
What do site selectors want from the financial case?
They want a clear case that fits the project's actual constraint, and speed they can count on.
Danielle Campolo of Strategic Development Group wrote in Area Development on September 23, 2026 that cost competitiveness is "table stakes rather than a differentiator" at the late stage, and that what sets communities apart is presenting their financial case clearly: land costs, utility rates, tax implications, cost of living, health care, and housing. She also writes that many incentive policies were "written for a different era" and that "If an approval process takes six months, that's a liability, not an incentive."
She matches incentives to the problem:
| If the project's challenge is | She suggests considering | Source |
|---|---|---|
| Speed to market | Expedited permitting and a dedicated project implementation specialist | Campolo, September 23, 2026 |
| Upfront development costs | Site preparation grants | Campolo, September 23, 2026 |
| Long term operating cost | Property tax abatements | Campolo, September 23, 2026 |
The Kansas Department of Commerce training deck, posted in December 2021, adds three checks for any financing and incentive package: whether there is a proactive process with dry runs, whether there are claw back performance clauses, and what the state's programs are.
How do you write an incentive record that holds up?
Write one record per program, in the same layout every time, and publish it where you control the wording.
- •Name the program and the authority. Use the program's official name and say which agency or government runs it.
- •State who qualifies. Include project size, wages, location tiers, and industries, as the program states them.
- •State what the amount is made of. Say whether it is a grant, a credit, a rebate, or an abatement, how it is calculated, and over how many years.
- •State how it is used. If a credit can only offset a particular tax, say so, as Young's example shows.
- •State the approval steps and the typical time. Give a number of weeks or months, and say what it is based on.
- •State the conditions. Include performance requirements and claw back terms, as the Kansas deck suggests.
- •Add the official source link and a checked on date. Update the date whenever any term changes.
| Fact | State it this way | Why it needs care |
|---|---|---|
| Amount | Calculation basis and years, not only a total | Young's rural and urban example shows how totals vary by tier |
| Use | What the credit or grant can offset | Credits may not be usable if tax liability is small |
| Timing | Approval steps and typical time | Campolo treats a six month approval as a liability |
| Conditions | Job, wage, and investment requirements; claw back terms | The Kansas deck lists claw back clauses as a check |
| Date | Checked on date and official link | Programs change |
This is our recommendation, built from the practices above. Many incentives are negotiated case by case, so describe the program and its published terms, not a promise to a particular company. Have your counsel or the agency that runs the program review the wording.
How do you test what ChatGPT says about your incentives?
Compare each answer to your record, and look first for errors in amounts and eligibility.
- •Write five prompts. Examples, with your names filled in: "What incentives are available for a 200 job manufacturing project in [county]?" "How are the [program name] credits calculated?" "How long does approval take for [program name]?" "Who is eligible for [program name]?" "Compare incentives for [county] and [neighboring county]."
- •Run each prompt three times in new chats. One run is one sample.
- •Mark each fact a match, a gap, or an error. Pay special attention to a total with no conditions, to programs that have changed or ended, and to state and local programs blended together.
- •Save the engine and the date.
- •Fix the published record first, then test again. Ask partners who list your incentives, such as state agencies and regional groups, to correct their pages.
This is the Detect step of the DRIFT Framework. When an answer states an old figure or a closed program, that is AI Narrative Drift at the level of a single fact. The full audit method is in How to Audit What AI Says About Your Region.
What is not known yet?
- •We found no published study of how answer engines describe incentive programs or amounts.
- •We have not tested any specific program, and we do not claim to know what ChatGPT says about yours.
- •The sources here are trade publications, a university center, and a state training deck, not statutes or program rules. Check official program documents for current terms.
- •Young's South Carolina figures are an author's illustration, not a program summary.
When is this not the right approach?
It is not the right first step when incentives are not what is holding you back.
Young argues that other factors have a greater long term effect than incentives. The Area Development 2026 survey reports site readiness and due diligence status rose from 78% to 98.5% as a factor. If sites, power, or workforce are the constraint, work on readiness first. A record is also not the right tool for confidential, case by case offers, which should stay out of public pages.
Frequently asked questions
Should we publish dollar amounts for incentives?
Publish the published terms, such as rates, caps, and how amounts are calculated, and avoid implying a figure for a particular company. Many incentives are negotiated, so a total with no conditions can mislead.
How often should we update an incentive page?
Whenever a program term changes, and on a set schedule, such as each quarter. Put a checked on date on the page so readers and answer engines can see how current it is.
Why does approval time belong on the page?
Because speed is part of the offer. Campolo writes that a six month approval process is a liability, not an incentive, and that expedited permitting can be the right incentive for a speed challenge.
Can we correct what ChatGPT says about our incentives?
You cannot control it directly. You can correct your own pages and partner listings, then test again and keep a dated record of what the answers say.
Sources and references
- •Daniel Young, Moore & Van Allen PLLC, Area Development, Last Word: When Incentives Lead, Projects Follow, Often in the Wrong Direction, Q1 2026, published April 7, 2026, checked October 23, 2026
- •Danielle Campolo, Strategic Development Group, Area Development, Ready to Show: Five Things Every EDO Should Be Able to Answer Right Now, Q3 2026, published September 23, 2026, checked October 23, 2026
- •University of North Carolina School of Government, Community and Economic Development, Perspectives on the Business Location and Site Selection Process, November 7, 2025, checked October 23, 2026
- •Area Development Research Desk, 40th Annual Corporate and 22nd Annual Consultant Site Selection Survey Results, Q1 2026, checked October 23, 2026
- •Kansas Department of Commerce, Office of Rural Prosperity, Economic Development 101 training deck, December 2021, checked October 23, 2026
Related reading: How Do Answer Engines Describe Regions? A Guide for Economic Development Organizations · Does AI Describe Your Region by the Criteria Site Selectors Now Use? · How to Audit What AI Says About Your Region · How Should an Economic Development Organization Choose an AI Visibility Program?