Textile art has recently experienced a resurgence within the contemporary art space, confirmed by a growing number of exhibitions, awards, and engagement from galleries. One of the most recent exhibitions in 2025 was ‘Woven Histories; Textiles and Modern Abstraction’ shown in The Museum of Modern Art with over 150 interdisciplinary works on display. This exhibition captured the direct link textile art has to history and highlights ‘issues of labour and identity that are intertwined with modern textile production.,’ as stated by Tate Modern.
Exhibitions creating a space for textile art shifts how it’s being viewed, moving away from a “domestic craft.” The purpose of textiles has developed over time, shifting from fulfilling fundamental human needs to becoming a medium for artistic expression. Alongside this resurgence, there have also been advancements in technology, particularly in artificial intelligence. These developments have sparked conversations among artists about the impact on their practice, often creating debate about where AI advancements fit in the art world. As a response to these discussions, I will be weighing up the pros and cons of using AI as a tool for production, for a slow process medium which could be seen as a contrast with the speed of AI.
Using artificial intelligence as an element of creation provides an automatic means of producing imagery. ChatGPT for example allows text-to-image generation using a system called DALL.E 3. that allows users to input a text prompt that generates an image. This image is then generated in 5-15 seconds on average from when the prompt is entered. When compared to artistic practices that are slow making processes, such as textile-based art, it raises questions: in a time when we are often conditioned to value speed in both what we consume and create, why would artists embrace slower production methods? And is this embracement coming from a position of rejecting the use of AI?
Bonnie Peterson is a textile-based artist whose work is passionately driven by environmental science. She embroiders onto natural materials as a means of translating typically text-heavy information into tactile, visual forms. She works through vast amounts of data and begins reproducing it in a way she deems more accessible, transforming graphs, equations, and statistics, often only available in digital formats—into physical materials. This process not only broadens potential viewership but also encourages deeper engagement by making complex information more accessible and materially present. This also changes the environment it’s now available in, allowing it to be removed from a digital container and transformed within a space to be a stand-alone artefact, impacting how the information is perceived.
Bonnie Peterson, Global Temperature Anomaly (2021)
One example of this approach can be seen in works such as Global Temperature Anomaly, where climate data is reinterpreted through labour-intensive stitching. By choosing a time-consuming process to represent research that is itself time-consuming, Peterson uses her medium to further embody the labour within her subject matter. This contrasts with AI-generated imagery that is rapidly produced through automated systems. Her work foregrounds time, effort, and human intervention as fundamental components of meaning, while automatic production involves far less visible labour, depriving its meaning from being reinforced.
This contrast reflects a broader tension in contemporary art. While AI offers speed, efficiency, and accessibility, it can also obscure the labour involved in production. Peterson’s focus on climate change supports this. Although climate change is accelerating, it is often perceived as slow-moving. Her use of slow, repetitive stitching mirrors the long-term labour of climate research, encouraging sustained viewer attention in contrast to the immediacy of digital imagery.
At the same time, handmade textile work is often associated with higher value due to the labour, time and materials involved. For those unfamiliar with the process, it may not seem worthy of the cost. As a result, viewers may hold preconceptions about textile art, outdated and impractical within a technology driven culture. AI creates both a challenge and opportunity, having the potential to devalue manual processes while also reinforcing the conceptual significance of labour in contemporary art.
Tapestry created from and AI generated pattern , Ellen Ramsey, DALL-E 07.51.35 (2024)
Ellen Ramsey is another textile artist. Ramsey produces tapestry works and, like many contemporary practitioners, holds mixed views on the use of artificial intelligence in her practice. To better understand its potential, she began experimenting with AI during both the planning and production stages of her work. Resulting in a piece created using an amalgamation of her prompt and a wide range of images AI software’s can access from public domains.
Ramsey is not unfamiliar with digital tools, having previously used photo-editing software to manipulate images before translating them into textile patterns such as Photoshop and or licensed stock circuit illustrations. However, AI-generated imagery introduces new concerns. Systems developed by companies such as OpenAI source material from vast areas across the internet, raising questions around authorship and copyright. For many artists, including Ramsey, the lack of transparency regarding source material is a significant drawback.
However, issues of authorship and ownership are not new to the art world, AI simply amplifies them. A notable example is the Cariou v. Prince case. In this instance, Richard Prince transformed images from a photobook “Yes Rasta” by photographer Patrick Cariou. After a complex legal process, the court ultimately ruled in favour of Prince, stating that the images had been altered sufficiently to be considered aesthetically different and therefore not infringing copyright.
For artists like Ellen Ramsey, using an AI-generated image as the basis for a later physical textile piece could similarly be seen as transforming the source material enough to constitute a new work.
It is also important to acknowledge that the tradition of handmade textile work often involves collaboration, including the use of other designers’ patterns, often in the form of shared hand drawn pattern books, which can be seen as early as the 15th century, facilitated by the printing revolution. In this sense, working with software to develop patterns could also be viewed as a form of collaboration.
This raises a broader question: is it important for artists to use whatever tools are available to them? As discussed earlier, we are creating art in a fast-paced world. The issues that artists respond to are rapidly evolving, and the platforms through which we consume and publish media are constantly expanding, providing a more constant engagement with content, shortening individuals processing capacity. The average time spent looking at a piece in a gallery setting is 15-30 seconds, these environments are curated to maximize engagement with the work with things such as slow looking, as advised by galleries such as the Tate modern. Where we consume art has also broadened outside of these spaces, creating another consideration for artists making work. Responding to these shifts by adopting new methods may be essential to sustaining an artistic practice.
The resurgence of textile art may in part overlap with developments in AI. Textiles resurgence began prior to technologies developments so there isn’t a direct correlation, however the affects these advancements have had, has accelerated and enabled the resurgence. Artists who choose not to engage with AI are making conscious decisions to work in mediums that contrast sharply in both process and outcome. Whether this is an act of resistance or simply a reflection of personal practice, slow-making methods, where time is embedded into the material, often communicate these values directly to the audience.
At the same time, access to AI and other technological developments within textile production, such as embroidery machines, may also contribute to this resurgence. Faster methods of production can encourage artists, who might otherwise see textile work as too time intensive. These tools allow ideas to be developed more quickly and efficiently, expanding the possibilities of the medium.
The resurgence of textile art within the context of rapid technological advancement highlights a significant tension in contemporary artistic practice. While artificial intelligence offers unprecedented speed, accessibility, and opportunities for experimentation, it also raises difficult questions surrounding authorship, originality, and the visibility of labour. As demonstrated through the practices of Bonnie Peterson and Ellen Ramsey, textile artists are not simply rejecting technology, but actively negotiating its role within their work.
Peterson’s emphasis on slow, labour-intensive processes foregrounds time and materiality as essential components of meaning, offering a counterpoint to the immediacy of AI-generated imagery. In contrast, Ramsey’s experimental engagement with AI reflects a more integrative approach, suggesting that digital tools can function as part of a broader creative process rather than a replacement for traditional methods. Together, these perspectives illustrate that the relationship between art and technology is not defined by opposition, but by adaptation and critical engagement. Ultimately, the continued relevance of textile art suggests that in an increasingly automated world, the value of labour, process, and human input remains significant. Rather than being displaced by AI, slow-making practices may gain renewed importance as sites of reflection, resistance, and meaning.