How AI Pricing Tools Set Prices—and What Franchise Owners Should Ask Vendors

AI pricing tools can either recommend a price for a person to approve or change prices automatically; the label “AI” does not tell you which. Franchise owners evaluating one should verify the data it uses, who can act on its recommendations, whether prices vary by customer, how decisions are audited, and what information and fees are shared across the franchise system.

How do AI pricing tools set prices?

Pricing software processes data to suggest or apply prices. The Competition Bureau of Canada describes algorithmic pricing as algorithms that set or recommend prices using data inputs. A tool may use business and market information such as demand, competitor prices, inventory, time, weather, local events, and transaction history. Some systems may also use consumer demographics, online behavior, or purchase history. The inputs depend on the product and its configuration; the words “AI pricing” do not specify them. Competition Bureau of Canada: Algorithmic pricing

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Rules-based systems

A rules-based system follows conditions and thresholds that people define—for example, a specified response when inventory falls below a level. The system can act consistently without learning a new pattern from each outcome.

Machine-learning systems

AI or machine-learning systems learn patterns from historical or incoming data and may adapt recommendations as market responses change. Their reasoning can be harder to interpret, which makes explanations and audit records important.

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These approaches can overlap. More important than the product label is what the software actually does: whether it only offers a recommendation, or has permission to deploy a price change without individual approval.

Dynamic pricing and personalized pricing are not the same

Dynamic pricing

Dynamic pricing adjusts to market conditions, such as demand, inventory, competitor prices, time, or local circumstances. A restaurant, for example, might receive a recommendation based on store-level sales patterns or a change in input conditions.

Personalized pricing

Personalized pricing uses information about a person or group—such as demographics, browsing, location, or purchase history—to tailor a price or offer. The Competition Bureau notes that real systems can combine market and consumer data. In a January 2025 staff perspective, the FTC described intermediaries using consumer information to tailor offers or prices; its initial review covered intermediaries working with at least 250 clients selling goods or services. That figure describes the intermediaries reviewed by FTC staff, not every pricing provider. FTC: Staff perspective on surveillance pricing

The FTC announced a draft enforcement policy statement on personalized pricing in August 2026. The announcement said undisclosed collection or use of personal data to set a price may violate the FTC Act, while also stating that the FTC does not have authority to ban personalized pricing in all circumstances. The comment deadline announced was September 18, 2026; the announcement alone does not establish what happened after that date. FTC: Draft enforcement policy statement announcement

Questions to ask a pricing-software vendor

Ask for concrete demonstrations and written answers, not just assurances that the product is “AI-powered.” These questions reveal the tool’s inputs, authority, controls, and consequences for the franchise relationship.

1. What data goes into the system?

Request a field-level inventory of inputs. Ask which are required, optional, inferred, or supplied by third parties, and how current they are. Relevant categories may include:

• Store sales, costs, demand, inventory, and transaction history.
• Competitor prices, local conditions, time, weather, or events.
• Customer profiles, loyalty information, browsing behavior, location, or purchase history.

Also ask whether the vendor uses your data to train or improve models that serve other customers.

2. Does it recommend prices or change them?

Ask the vendor to show the complete workflow, including default settings and user permissions. Establish which actions require owner approval, whether changes can be scheduled or deployed automatically, who can override them, and how to reverse a change. Get a clear account of what happens if the assigned approver is unavailable or the system receives bad data.

3. At what level does it set prices?

Find out whether recommendations are set by individual location, market, customer segment, or individual customer. Ask whether two customers could receive different prices or promotions because of loyalty status, identity, device signals, browsing, or other personal data. Clarify whether the system distinguishes a personalized promotion from a different base price.

4. Can you explain and audit a recommendation?

Ask the vendor to walk through a real or representative recommendation: the inputs used, the change suggested, the objective being optimized, and the person who approved or applied it. Request usable explanations and an audit log that records recommendations, changes, approvals, overrides, and reversals. This matters especially where machine-learning outputs are difficult to interpret.

5. What data and recommendations are shared across locations?

Ask whether the vendor pools nonpublic sales, cost, or pricing data from franchisees; how it aggregates that information; who can access it; and whether one model can generate recommendations for nearby competitors using pooled data. A current dispute illustrates why franchisees should understand those arrangements: the claims are allegations, not established findings. Associated Press: McDonald’s lawsuit and franchise pricing

6. What is the full cost over the contract?

Get implementation, integration, platform, data, support, and renewal charges in writing. Ask what triggers extra charges, whether integrations require separate vendors, and what happens to data and access when the contract ends. FTC franchise materials describe concerns about undisclosed technology and payment-processing fees, but do not determine whether a particular software contract or fee is lawful. FTC Franchise Rule compliance guide

7. What safeguards protect customers and the brand?

Ask how the system prevents extreme or rapid changes, detects stale competitor data and input errors, handles promotions, and helps keep advertised prices accurate. The FTC says dynamic pricing is permitted under the specific rule it discusses when pricing information is not misleading. Its upfront total-price provisions apply to live-event tickets and short-term lodging, so do not assume those provisions govern a franchise’s other sales channels. Check applicable rules for the business, channel, and jurisdiction. FTC: Consumer Reviews and Testimonials Rule FAQs

What the McDonald’s example shows—and what it does not

McDonald’s said on October 1, 2026, that its tool provides restaurant-specific recommendations, does not set or change prices, and leaves independent menu-price decisions to franchisees. The company also said its tool is not dynamic and does not price to an individual customer’s willingness to pay. These are the company’s representations about its own system, not an independent audit. McDonald’s cited a global network of more than 46,000 restaurants when explaining why local market conditions vary. McDonald’s statement about its pricing tool

An Associated Press report dated October 6, 2026, described a lawsuit alleging that McDonald’s uses nonpublic franchise-level data in a way that coordinates prices. McDonald’s denied the allegations and said its optional tools do not automate, coordinate, or fix prices. The dispute has not been established as a court finding in the cited report. AP also reported McDonald’s statement that franchisees own and operate 95% of its 14,000 U.S. stores. That U.S. figure is distinct from the company’s global restaurant count.

The example is useful because it separates three questions that are often conflated: what a tool recommends, who retains pricing authority, and what data is shared among locations. A franchise owner should verify each point in the specific contract, product configuration, and data terms rather than assuming another company’s description applies to their system.

How to compare vendors

Use a written comparison so that a polished demo does not obscure differences in authority, data use, or ongoing cost.

The available evidence does not establish a best vendor for franchise owners, so a vendor choice depends on product-specific verification against these criteria.

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