What can AI do for the furniture industry?

Product developers can already create realistic virtual furniture models with 3D visualisation. AI-generated simulations should also help to analyse materials and designs, thus improving the quality and durability of furniture. New approaches take this a step further, aiming to use machine learning to identify the latest trends. Design proposals tailored to these forecasts could help to provide exactly what customers want.

Many furniture products have a wide range of variants, and process flows are often complex. As a result, the keystone for the successful application of AI is the meaningful integration of data. AI tools help to organise and simplify the available information. The ever-increasing pool of data can supply a continuous flow of information to improve the whole process chain. Service platforms can support businesses with digitalisation and standardisation of data.

Recent studies show that a majority of businesses believe that AI improves customer relations. Furniture sales and 3D visualisations become more targeted and personalised. In large stores, virtual showrooms and augmented reality can help with bespoke planning of interiors. In the future, more and more AI-based bots will be able to make individual recommendations to customers for the most suitable mattress or that special piece of furniture.

AI will also enable better accuracy and efficiency of on-site furniture assembly. 3D measurement allows complex structures to be built into spaces or surfaces with millimetre precision. Existing elements, of a fitted kitchen for example, can be measured without the need for disassembly. Once measurements have been made, the production specifications for the built-in elements to be added can be sent directly to the manufacturer.

AI supports the optimisation of both process and delivery chains in furniture production. Predictive technology can help to avoid waste and anticipate potential problems in good time. Software can identify areas where there is potential to reduce waste while also cutting down on energy use and emissions.

AI-led automation can reduce costs by improving efficiency in areas such as assembly, packing, and logistics. Even previously time-consuming manual processes such as cutting fabric into lengths can be automated by AI with pattern recognition. The technology also offers new opportunities for customising furniture. With help from AI, flexible production processes can make it profitable to produce small runs of special parts, enabling furniture collections to be better adjusted to customers’ personal preferences.

We are only starting to discover the potential for AI use in the furniture industry. Experts agree that future competitiveness will depend on our ability to recognise and harness its potential. The first Interior KI Summit conference on AI in the furniture industry, held at the start of the year in Bielefeld, Germany, reached a clear conclusion: AI opens up new possibilities for the furniture industry and can boost competitiveness and cost efficiency – but this requires investment in the necessary infrastructure.