TECHNOLOGY

How can small and medium-sized music venues harness AI?

Simon Coates
4 June 2026

© DHP Family

“The rapid growth in the amount of AI content swamping every platform is already provoking changes in people’s attitude towards live events. Real music made by real people has even more value when your senses are swamped by machine-generated sound and vision.” Mark Davyd, CEO of Music Venue Trust, the UK charity that protects UK grassroots music venues, is talking about the proliferation of AI and how LLMs (Large Language Models) have become an unstoppable facet of the music business, including the live sector. 

While multinational organisations like Live Nation, AXS, AEG and Ticketmaster have been using AI to improve their businesses for some time, where does that leave music’s smaller, grassroots venues?

The multinationals can afford to develop generative artificial intelligence strategies, but independent music spaces often lack the budget and manpower to spend time working out ways to use AI. Plus, the understandable sense of consternation around the use of AI systems in the music world right now is especially applicable to spaces that are already struggling to survive.

Delia Sparrow of independent London venues The Lexington and The Waiting Room has considered using AI, but her experiences so far have been unpredictable. “I’ve put questions into it that I know the answers to, and it’s been laughably wrong,” she says. “I think it can be a good starting point, but then you have to double-check all sources and not be complacent about the info being correct.”

However, there are measurable, affordable ways in which independent music venues can make the systems work in their favour, saving time and increasing efficiency.  Importantly, AI models like ChatGPT and Claude.ai can be seen simply as an extension of an internet search engine. This is where Delia’s accuracy concerns come into play, as the models aggregate information from websites that might not be factually correct or are opinion-based.  Yet there is an art to asking an AI model the right question (or prompt).

Anton Lockwood is Director of Live at DHP Family, the owners of grassroots venues Rock City in Nottingham, The Garage in London and Bristol’s Thekla, among others. Scrolling through other small venues’ websites to see which acts they are programming gives DHP an insight into any artists they might be missing out on. “That’s a great use of AI as it’s tedious, fiddly and time-consuming to do by hand,” he says. It also means artists are offered dates at venues they may not otherwise have considered.

Changing the parameters accordingly, a ChatGPT (for example) prompt to gather this kind of information might look something like this:

"I want to know which artists are performing at small, independent UK music venues over the next [insert time frame, e.g., 30 days/month of April]. Please research the upcoming schedules for these specific venues [insert venue name and town/city].  Provide the output in a table format with the following columns: Date | Artist/Band | Venue | Location. Focus on emerging talent or indie artists."

The AI models’ data processing abilities can be equally as helpful. Canada-based Brodie Conley works for the Center for Music Ecosystems and Water & Music, a New York research and strategic advisory organisation focused on music technology. “In some cases, AI may offer useful administrative support,” he says. “For example, around scheduling, marketing, accessibility or reducing some routine labour.”

Thus, there are opportunities for AI models to provide analysed feedback on data around bar and merchandise stock control, timings (the best days or nights for a performance, optimum stage times, set lengths) and staff rotas. Excel spreadsheets, Word documents, PDFs, .txt files and other application formats can be uploaded to AI models. And, given the right prompt, the model can produce meaningful, usable results in table formats.  Even without uploading data, a simple staff rota can be generated using a prompt along these lines:

"Create a weekly staff rota for [number] employees for the week of [dates].

Shifts Needed:[e.g., morning: 10AM-6PM (2 staff)] and / or [e.g., evening: 6PM-1AM (3 staff)].

Constraints & Rules:Each employee must work between [min number] and [max number] hours. No employee should work more than [number] days in a row. [employee name] is off on [date/day]. Ensure at least one [role, e.g., supervisor] is present on every shift. Respect the following availability: [list requests, e.g. if a staff member is on leave].

Output Format:present the final rota as a table, organised by employee, showing their shifts for each day of the week, total hours worked and any scheduled days off."

Cate Bentley is the Operations Director at Kendal’s Brewery Arts venue in the north of England, and the Brewery Arts team has been investigating how AI can help with day-to-day tasks. “It’s a conversation we’re involved in through Future Arts Centres (the UK network of inter-supportive independent venues), and is being discussed with our board and teams,” she says. “We’re making some use already to help with admin procedures – drafting rotas, training plans and so on. I’m also aware there are organisations using it to help with funding bids. We’re in the process of assessing our programme to maximise ticket sales and revenue, and adjusting performance timings to help generate increased bar revenue. I’m sure this is something AI could help with.”

Following Cate’s example, a training plan prompt template would look like this:

“Draft a training plan for new staff members joining a small, independent music venue [capacity e.g. 200 people]. Include health and safety regulations compliant with rules in [insert country], rules around staff rotas, and any other relevant information.”

AI can also be used to help write policies and guidelines. A prompt to write a simple door policy would look like this:

“Create a door policy for a small, independent music venue [capacity e.g. 200 people] in [insert city/country] that serves alcohol. Include details on acceptable forms of ID and any other relevant information.”

There are ways to use AI to help customer service processes, too. For example, a prompt for creating a reply template for customers requesting a ticket refund by email would look like this:

“Draft a series of polite but firm customer service email replies for staff to use in the instance of a ticket-holder emailing to ask for a refund. Ensure the replies are legally compliant with consumer laws in [insert country].”

Updating a venue’s social media accounts can be time consuming. Again, AI can help. A social media posts marketing prompt would look like this:

“Create a series of social media posts for the forthcoming [insert name of act] show on [insert date] at [insert name of venue]. Separate the posts by platform e.g. Facebook, X, etc. Bear in mind the target age group is [insert age range], and the audience might also be fans of [insert acts/artist names].”

In all cases, the prompts are customisable, and the results gleaned from the AI platforms can be changed to fit circumstances.

Writer and Scottish Music Centre board member Arusa Qureshi picks up on Brodie’s point on using AI to benefit fans. “I’d like to see the technology used for accessibility,” she says. “Whereby venues can work towards finding new ways to change their existing strategies for the benefit of audiences that may need more support.” In this case, AI-generated digital floor plans would help those with mobility needs navigate venues, and screen-based, real-time AI captioning allows audience members with hearing issues to follow lyrics and announcements.     

Issues around potential threats to jobs and the AI models’ environmental impact exist alongside concerns over artificially created music and artists. High energy usage means AI infrastructures are one of the fastest-rising contributors to global CO2 emissions. In 2025, the World Economic Forum reported Google’s carbon emissions surged nearly 50% in five years due to increasing demand from AI data centres.

Recognising growing fears around AI and job security, industry-wide platform UK Music’s recent Manifesto For Music Scotland report includes positive measures to ensure AI policies continue to support homegrown creativity and independent venues.

David Demange is the director of La Rodia, a grassroots venue in the French city of Besançon. In step with UK Music, David has written a charter for his team, laying out the uses and pitfalls of AI. Underscoring the importance of human oversight and maintaining artistic integrity, the charter states, AI is an assistant serving our teams, never a substitute for human sensitivity and artistic uniqueness that define our identity and AI may assist production but does not transfer responsibility. Guiding principles in the charter include using AI to work better rather than work more, reinvesting time saved through AI use into social, cultural and environmental causes, and ensuring all AI-driven tasks comply with GDPR and applicable legal obligations. 

Brodie Conley also advises a balanced approach to AI; one in which grassroots venues maintain their environmental integrity and unique cultural value without getting left behind.  “As AI contributes to a wider saturation of synthetic cultural content, independent live venues may become even more valuable as spaces of shared, embodied, local experience, where culture is still social, collective and rooted in actual human presence,” he says. “In that sense, the rise of AI could make the distinctive value of independent venues clearer, but only if we – as artists, researchers, fans, communities – actively recognise and defend that value.”