AI in franchise

Franchise is a popular form of collaboration, also for hotels and many other services in the hospitality sector. In franchise an important role is reserved for technology, and technology is always on the move. Nowadays, all we hear is Artificial Intelligence (‘AI’). In this article we will explore the opportunities AI has to offer for franchise networks in the hospitality sector, but also the associated legal implications.

Since 1 January 2021, the Dutch Franchise Act defines a franchise agreement as follows: ‘A franchise agreement is an agreement whereby, in return for a fee, the franchisor grants a franchisee the right and imposes on him the obligation to operate a franchise formula in the manner determined by the franchisor for the production or sale of goods or the provision of services’. Besides definitions, the Franchise Act contains the franchisor’s (pre-contractual) obligations to provide information, consultations between franchisor and franchisees, and a right of consent if the agreement is amended or if a derivative formula is introduced. When a franchise agreement ends, it is mandatory to include a goodwill clause in the franchise agreement in case the franchisor takes over the franchisee’s undertaking. A post-contractual non-competition clause also comes with restrictions. The parties have to behave as a good franchisor and a good franchisee. 

In short, AI systems are algorithmic systems that process input – autonomously, self-learning or not – in order to generate targeted outputs (such as predictions, recommendations, or decisions). AI can play a role in, or can autonomously arrive at, analysis or decision-making.[1]

AI is developing rapidly and offers powerful tools to increase efficiency, improve analysis and decision-making, control and optimize processes and thereby reduce costs, and personalise customer experience throughout the franchise system. AI processes many data, often including competition-sensitive or privacy-sensitive data that are publicly available or originate from specific sources. AI systems usually work without providing source references.

Use of AI by franchisors

Franchisors in the hospitality sector use AI to improve efficiency and consistency in their large, often global franchise networks. By analysing real-time and historical data, they gain insight into performance differences between branches, regions and seasonal patterns in supply and demand on the market. This allows them to use a targeted approach, automated or not.

Besides, location data, traffic flows and demographic patterns are analysed by AI to determine the best locations to open new hotels or holiday accommodations. This is helpful to substantiate market access, predict cannibalisation risks between branches (such as competition between nearby hotels or restaurants within the same chain), and rank potential locations on the basis of their expected success.

AI also plays an important role in pricing; by analysing consumer conduct and local competition, room prices, menu prices and offers can be balanced according to region. On the whole, the arrival of internet platforms, price comparison sites and online sales has made the pricing of many products and services much more transparent.

In order to guarantee compliance and brand consistency, AI monitors price information that is available online, but also customer reviews and public messages, so that deviations from existing or historical price/promotion policy, branding or service are quickly traced and incorporated in the outcomes reported.[2]

Furthermore, smart chatbots and knowledge bases offer 24/7 automated support to franchisees, causing shorter waiting times at help desks and cost-savings.

Finally, AI-driven learning platforms enable personalised training for franchisees that auto-adjusts to their experience and learning style, while progress is carefully monitored (and reported) and training materials are constantly adjusted in order to diminish any differences in performance.

Use of AI by franchisees

Franchisees in hospitality also benefit from the use of AI tools, which at present still mainly relieve them of repetitive tasks. For instance, AI can automate stock control and staff planning on the basis of expected crowdedness, booking patterns, and regional events. This leaves franchisees more capacity and time for guest experience, service quality and growth. 

AI also plays a role in HR matters: it screens applicants for availability, skills and attrition risk. Sometimes, HR will also use AI systems for timetabling, trainings, file preparation, handovers and reports. For local marketing purposes, generative AI can create social media posts, e-mail campaigns and promotions that are consistent with the branding of the franchise formula, but also cater to the needs of target groups. This adds not only to the effectiveness of marketing campaigns, but also to customer loyalty and brand experience. 

When it comes to customer contact, virtual assistants like chatbots and smart point-of-sale systems can help customers with answering frequently asked questions, processing reservations, and making personalised suggestions for upgrades or additional services (such as late check-out), based on buying conduct or customer conduct. However, these AI systems are usually developed by the franchisors and offered optionally or not, unless the franchisees are Master franchisees and a specific demand from their region is catered to. 

Finally, through customer feedback (e.g. from online reviews) AI can signal trends, discover bottlenecks in the service and provide insight in what creates guest satisfaction. Examples are repeated comments about hygiene, waiting times, or quality of the food.

While the use of AI in franchise offers chances, it also raises various legal questions. Examples are the AI Act and other specific EU laws in the field of AI and data, but also the protection of personal data and privacy (GDPR), intellectual property issues, and the risks of bias and discrimination in relation to fundamental rights. In this article we focus on the question whether the deployment of AI may distort competition or may be regarded as a change of the franchise formula. Franchisors and franchisees face considerable risks precisely on these points, because they directly affect the heart of the collaboration and competitive relations within and beyond the franchise network.

Competition on the relevant market; the cartel ban

The use of AI within franchise networks may lead to risks of breaches of the cartel ban. AI systems may pave the way for collusion within the franchise network through price-fixing via algorithms. With the help of AI, franchisors can monitor price movements and detect deviations in the desired price level. This increases the risk of horizontal price-fixing and/or resale price maintenance, which is a restriction by object in competition law. Franchisors are not allowed to impose fixed sales prices or minimum sales prices on franchisees.[3] Franchisees must be free to set their own prices. Franchisees are not allowed either to fix prices among themselves (or via the franchisor as a ‘hub ’n spoke’), not even if they are in the same franchise network. However, franchisors are allowed to use maximum or recommended prices, as long as these do not become fixed or floor prices [4]. AI can help enterprises determine their prices more efficiently. Transparency in the market has already increased by e-commerce and online (booking) platforms. It will increase even further by the frequent deployment of AI and other data-driven systems, which will make enterprises operate less independently. Parallel conduct on the market is not prohibited. However, interrelated systems may also enlarge the risk of tacit collusion within a franchise network when algorithms exchange signals until agreement is reached on a certain price or promotion; in this process, price algorithms might arrive at a higher average price level than they would if it were left to the market.

Especially where self-learning algorithms are used, the risk arises that systems will independently fix price strategies, without the knowledge of the franchisor or the franchisees. This may result in coordinated conduct without human alignment, while human alignment seems to be required for the cartel ban to be applicable. Naturally, enterprises are responsible for designing the systems. It is not clear yet how this kind of situations must be qualified in terms of competition law. Another challenge is the detection and prevention of this form of collusion, which may indeed have a distorting effect on competition. 

The AI Act offers clues for supervision, e.g. via transparency obligations (Article 53 (1)) and cooperation between supervisory authorities (Article 74 (2)). Franchisors would do wise to implement compliance programs that test AI use against competition rules. Transparency and explainability of AI systems are crucial to supervision. As mentioned above, parallel conduct is not automatically proof of price-fixing, unless enterprises deliberately use the same AI system with predictable outcomes.

Price monitoring systems cannot be used to pressurize franchisees into not using lower prices than, for example, the recommended resale price (indirect price-fixing).[5] One example is the penalty that the European Commission has imposed on the fashion label Guess.[6] The European Commission found that Guess was prohibiting its authorised distributors from bidding for brand-related keywords. This prohibition had an anticompetitive effect, since pricing took place on the advertising platform. In AdWords, the price of an ad is determined via an auction mechanism in which the eventual price depends on the demand for the keyword, which is an algorithm-driven process. By eliminating competition on these keywords, Guess could keep demand artificially low, which caused the price of ads to drop. The algorithm thus had a direct role in the pricing, and it was Guess’ policy to influence this effect strategically. The Commission regarded this as a breach of the cartel ban.

Franchise agreements

The Franchise Act defines a franchise formula as follows: ‘an operational, commercial and organisational formula for the production or sale of goods or the provision of services, which regulates the uniform identity and image of the franchise undertakings that are part of the chain in which the formula is applied, (…)’. This has to include in any event ‘a trade mark, model or trade name, house style or drawing’ and also know-how, which is subject to specific hard requirements. 

Could AI implementations lead to a change in the franchise formula that – if included in the franchise agreement – will exceed threshold values and require the franchisor to obtain the consent of the franchisee(s)?

This may be imaginable in theory, but precisely because the franchisor and franchisees use AI mostly to make existing processes more efficient, consistent, qualitatively better and cheaper, both parties have an interest in this and it is not likely to expect a negative financial impact on the franchisee, which cannot be earned back easily. Besides, it does not seem obvious that the introduction or further professionalization of the deployment of AI could be a ‘derivative formula’ that triggers a right of consent. After all, there is no question of the introduction of a competing item under the same brand and for the same products and/or services.

A right of consent might only exist if the introduction of AI leads to radical changes to the franchise formula with negative financial consequences (above the threshold values). It is conceivable that the obligation of the franchisee of a fancy restaurant to replace all the waiting staff by robots, to be purchased from the franchisor, results in such a different appearance that there will be financial consequences. On the other hand, Japan already has restaurant chains that function well this way – with only robots as waiters – but there too, this is an exception and part of the formula. It will have to be evaluated according to the market context of the time and the location/region concerned whether something is radical and has financial consequences. 

Despite these future scenarios, before implementing or further professionalising and deploying AI in a franchise network it is important to assess carefully whether and to what extent the operation of AI interferes with the franchise formula and how this impacts the franchisees. Furthermore, franchisors would do well to include the expected integration and use of AI during the term of the franchise agreement and the associated costs (as far as these can be estimated) as an obligation for the franchisee in the franchise agreement, in order to prevent unexpected consent requirements.

If consent is required nevertheless, franchisors may choose to obtain consent via i) the (ordinary) majority of the franchisees domiciled in the Netherlands, or ii) each of the franchisees domiciled in the Netherlands who are financially affected by the change. If you want to prevent such consent procedures, you should include concrete and specific threshold values in the franchise agreement. 

In most cases things will not get that bad and the deployment of AI will not be so drastic as to constitute a ‘change’ with financial impact on the franchisee. However, franchisors may still be obliged to provide information on their plans with AI.

AI offers franchise in hospitality chances to improve uniformity, quality, efficiency and control, but may also entail various risks, including – besides privacy – prohibited price-fixing agreements and consent procedures about changing the franchise formula. Franchisors would do wise to assess carefully whether the use of AI is compatible with competition law and the Dutch Franchise Act, and to involve franchisees in good time if the changes are radical and have financial impact.

[1] Artikel 3(1) Verordening (EU) 2024/1689 (AI Act).

[2] International Bar Association – International Franchise Association Joint Conference, 6–7 mei 2025, sessie en paper getiteld “News From Around the World, ‘AI’ in Franchising”, Chair: Martine de Koning.

[3] Richtsnoeren inzake verticale beperkingen (PbEU 2022, C 248/01) (185), p. 45 (eur-lex.europa.eu/).

[4] ‘Leidraad Afspraken tussen leveranciers en afnemers’, acm.nl, 7 juli 2022 (www.acm.nl).

[5] Richtsnoeren inzake verticale beperkingen (PbEU 2022, C 248/01) (190-191), p. 46 (eur-lex.europa.eu/).

[6] ‘Antitrust: Commission fines Guess €40 million for anticompetitive agreements to block cross-border sales’, ec.europa.eu, 17 december 2018 (https://ec.europa.eu); Volledige besluit te lezen via:https://ec.europa.eu/competition/antitrust/cases/dec_docs/40428/40428_1205_3.pdf.