We are on the verge of a new maker boom—driven by artificial intelligence and the creation of augmented reality scenes. Why augmented reality? Because it is becoming a new communication channel in the near future. It turns everyday touchpoints (packaging, print, products, spaces) into an interactive channel that you control: direct customer feedback, instant updates, and measurable experiments without apps or large budgets. All this becomes possible thanks to technologies such as WebAR (creating and launching AR scenes via a web browser, without of downloading new applications), the growing accessibility of AR platforms that let you create AR scenes without programming skills, and GenAI tools. In 2020, we launched the MyWebAR platform for creating AR content. Today, this community of creators, designers, educators, and corporate teams—with over 250,000 users in 180 countries and over 200 universities—develops and ships AR products every day. What used to take large production studios months now takes hours: marketing managers and small business owners create an AR layer, place a tiny QR code on a box, test messages or offers, run polls and mascot mini-games, collect zero-party data. We also see incredible projects in the arts and education. For education, AR is literally becoming a new fuel thanks to its clarity and creativity. Our creators launch products in a matter of hours thanks to AI tools: creating scripts, 3D objects, animations, voiceovers and music, converting text to code, and more. AI has helped eliminate production bottlenecks, allowing "makers" to focus on ideas, not on production processes. I am confident that as the use of consumer augmented reality glasses grows, AR maker culture will reach a new level—constantly accessible spatial content for creativity, education, business, creative storytelling, and social networks.
For us, a Vancouver maker space was our launchpad. It was our entire R&D department on a subscription basis, giving us access to six-figures worth of industrial equipment without the capital risk. This allowed us to prototype our sofa design affordably. The community there became our initial supply chain. We partnered with a metalworker and a textile artist we met in the space, who helped us source materials and create custom components. We were able to perfect our product and prove market demand before we ever signed a lease on our own workshop. From my POV, companies still use maker spaces as agile, "skunkworks" labs to accelerate R&D . After prototyping and achieving product market fit, they can commit to larger production runs. For AI, you could argue that it's a natural complement to the maker movement because it makes it so much easier to operate as a solo maker. Solo makers typically have very thin margins and are short on time, so the ability to "delegate" hundreds of tasks to an AI that previously would have required hiring or outsourcing, makes the entire maker endeavour that much more viable.
As a business owner, I've seen the "maker" concept evolve beyond its roots in tech and crafts into a real driver of innovation inside companies. At The Laundry Basket(r) LLC, we apply a maker-space mindset by encouraging our team to test new ideas quickly, whether that's eco-friendly packaging, community partnership models, or integrating AI into our logistics. We treat these experiments as small "maker projects," giving space to prototype and fail fast without big risks. I think AI/GenAI makes this even more exciting, suddenly, small teams can generate concepts, analyze data, and simulate outcomes in ways that used to take months. That hands-on, creative energy is what keeps businesses like mine innovative and competitive.
From my experience with companies integrating maker spaces to drive innovation, I've noticed a definite shift towards blending traditional tech with cutting-edge fields like AI and GenAI. These spaces are no longer just about soldering and coding; they've evolved into hubs where AI prototypes are created, algorithms are tested, and data is visualized in ways that weren't possible before. By providing tools and a collaborative environment, these spaces encourage spontaneous brainstorming and rapid prototyping which is essential for innovation. Moreover, some companies have been really creative, extending the maker concept beyond the physical spaces. For instance, virtual reality (VR) setups where you can design and manipulate 3D models in a virtual space. This approach is particularly useful for remote teams that need to collaborate on projects without being in the same room. It's all about making the technology accessible and letting diverse groups of people use it to solve real-world problems. The key takeaway here is to think of maker spaces not just as places to tinker, but as springboards for practical innovation that can be applied in real business or research scenarios.
I've noticed companies increasingly treat Maker spaces as innovation incubators rather than just communal workshops. At my previous role, we set up a hybrid Maker space where engineers, designers, and data scientists could experiment with AI and generative models on real-world prototypes. For instance, one team used GenAI to rapidly iterate on user interface concepts, while another explored predictive maintenance tools for our hardware products. The biggest advantage was giving employees permission to fail fast and test unconventional ideas without formal project pressure. Beyond tech, some teams brought in crafts, 3D printing, and even storytelling exercises to spark creative problem-solving, showing that making doesn't need to be purely digital. I've seen these spaces accelerate innovation cycles because they combine hands-on experimentation with cross-disciplinary collaboration, creating ideas that wouldn't emerge in standard meetings or purely virtual brainstorming sessions.
Appreciate the opportunity here. I wouldn't have called it the "Maker mindset" at the time, but that's exactly how my new product CashbackHQ started. I was tired of wasting time clicking between cashback portals just to figure out who was offering the best rate. I wasn't trying to build a business—I just wanted something that worked well for me. So I threw together a rough tool that pulled the rates in one place. It was clunky and ugly, but it saved me time. That was enough to keep going. I didn't have a roadmap; there was no deck or vision. I built the thing because I needed it. Then friends started using it. Then strangers. That's when I realized I might be onto something. Even now, I still approach problems like that. Just fix what's broken or use AI tools to help me optimize my life. I've used some AI tools along the way—not to be trendy, just because they help. I'll use it to write some page copy, check data faster, whatever takes friction out of the process. But the core hasn't changed: build what's useful. Improve it when you can. I think that's a pretty good example of the Maker mindset!
The Maker Movement did not die. It moved in-house, got a budget, and teamed up with AI. Inside forward companies, maker spaces are no longer hobby corners. They are rapid learning labs that turn ideas into working demos in days, not quarters. Demos beat decks. If it is not built, it is not discussed. AI is the co-maker. Teams use GenAI to draft firmware stubs, generate 3D variants, synthesize test data, and run evaluation harnesses before a dollar hits production. AI turned every workbench into a software bench. The fastest idea wins. No-code is the new soldering iron. Product and marketing stitch APIs, sensors, and language models into live workflows without waiting for full sprint cycles. Think Lean Startup with power tools. Build, measure, learn. Repeat. Public build walls create belief. When teams ship in the open, you get commitment and social proof that money cannot buy. Name your lab and you brand your speed. Category clarity attracts talent and budget. The operating model is simple. One-sentence briefs. Forty-eight-hour sprints. Monthly show-and-tell that includes customers when you can. A small shadow budget people can actually spend. Legal and security seated at the same bench so progress does not stall. Score what matters. Time to first prototype. Cost per validated learning. Percent of the roadmap influenced by maker outputs. Revenue or cost-to-serve impact from ideas born on the bench. Optional: patents filed and adopted. Guardrails keep you fast and safe. PII stays out of sandboxes. Models get red-teamed. IP and rewards are clear so people know who owns what.
When I think about the Maker Movement today, I see it less as a niche hobby and more as a mindset for how companies approach innovation. In the past, it was all about physical spaces where people tinkered with gadgets and electronics. Now, technology has expanded what "making" can be. As a founder in the tech space, I see Maker principles applied to digital creation just as much as physical prototypes. AI and GenAI, for example, are becoming the new tools in these spaces. Teams are experimenting with AI to quickly test concepts, generate design options, and even simulate outcomes before committing resources. It's a different kind of prototyping that accelerates creativity in a way that wasn't possible a few years ago. For companies, the focus isn't just on having a space or a tool, it's about encouraging a culture where experimentation is safe and visible. Bringing people together, whether physically or virtually, sparks cross-disciplinary thinking. I've seen design teams treat AI like a colleague, feeding ideas into models and iterating faster than ever before. The technology amplifies human creativity rather than replaces it. In that sense, modern Maker spaces are less about the tools themselves and more about the process of collaboration and rapid experimentation, blending human intuition with the computational power of AI.
I'd say the Maker Movement hasn't disappeared but it's evolved. Early on, it was about 3D printers, DIY electronics, and community workshops. Today, many companies are reinterpreting that spirit through innovation labs and internal maker spaces, where employees experiment with ideas that may never make it into a product roadmap but often spark breakthroughs. AI has become a natural extension of this - instead of soldering circuits, teams now "make" by prototyping prompts, testing automation workflows, or blending data with creative storytelling. In my own industry, I've seen marketing teams use maker-style hackathons to test AI-powered campaign tools that later scaled into client-ready solutions. The core of the Maker Movement - hands-on creativity, learning by doing, and community - is still very much alive, but the tools have shifted from physical materials to digital platforms.
I run Telsen, a digital food safety platform that helps restaurants and hospitality groups move away from paper checklists and manual compliance by using IoT sensors and digital checklists. I've been around maker spaces for more than 15 years, from uni through to my career as an engineer, but these days we've taken that mindset in house. At Telsen our team focus on real customer problem statements and use AI coding tools like Lovable and Cursor to quickly throw together MVPs we can test straight away. If it solves the problem, we keep building. If it doesn't, we scrap it and move on. That cycle means we get fast feedback and don't waste time on ideas that won't land. We also use 3D printing to trial different types of sensor rigs. Back when I started out, you needed a shared maker space for that kind of prototyping, and the printers were finicky, high cost, and high maintenance. Now the tech is affordable, the quality is great, and we can do everything in-house with almost no hassle.
In my experience, some companies are using GenAI to simulate failure conditions instead of only creating ideal product prototypes, envisioning how a product might break, malfunction, or be misused. According to TechTarget, failure prototyping is an essential step in product development because it allows developers to identify and address any potential issues before launching the product to market. The best way to stress-test virtually is to spur innovation by designing stronger, safer, and more adaptable solutions before investing in physical R&D. I believe that this mindset is crucial in today's fast-paced and ever-evolving technological landscape.
I am noticing that companies are now deploying AI that tracks subtle facial expressions, vocal tones, or biometric signals during product demos, rather than relying on surveys. The emotional insights fuel innovation by revealing hidden frustrations or delights that customers may not express verbally. For instance, an AI-powered camera that reads expressions can track the product's performance in a real-life setting. This information can then be used to improve future iterations or new products. According to research, emotional analysis through AI can increase sales by up to 20% and decrease customer churn by 50%. This shows the potential of AI in understanding and connecting with customers on a deeper level. I must say that AI is truly opening up new possibilities for businesses to deliver a more personalized and seamless experience to their customers.
We have implemented internal hubs where teams can experiment with new tools and link building techniques, similar to maker spaces, to encourage creativity and knowledge sharing between specialists. For example, we are actively experimenting with AI tools for analyzing large amounts of data, which helps to find potential opportunities for quality links faster. We created an internal "craft zone" for team brainstorming, where instead of computers you can use physical materials - this promotes outside-the-box thinking. In addition to technology, we encourage cross-functional projects where marketers, developers and creatives work together on new ideas - it's like a maker space for different specialists.
Hi there, I'm Justin Brown, co-creator of The Vessel — a leading personality development platform. We borrowed the maker ethos and built a tiny, repeatable "ship lab" that now drives most of our product and content innovation. That's why I'd like to respond to your query: For us, "making" means setting aside time to build something tangible every week, test it with real people, and see if it holds up outside our heads. A few years ago we started running what we call our studio sessions. Every Monday morning, the rule is simple: no slide decks, no brainstorms, just build. Each person has two hours to create a usable artifact. Sometimes it's a worksheet, sometimes a tiny interactive tool, sometimes a prototype lesson. The constraint is that by 11 a.m. it has to be something a stranger could try in under 90 seconds. If it's not demoable, it doesn't survive. That rhythm has changed the way we work. Instead of chasing big launches that take months, we've embraced small, scrappy experiments. Where AI comes in is as a kind of tireless intern in these sessions. We lean on GPT, not to dream up entire products, but to do the grunt work: generate edge cases, polish copy for a specific audience, or suggest how to break what we've built before someone else does. That's where it's surprisingly useful. The model isn't our strategist — it's the assistant that helps us spot cracks we'd otherwise miss. For example, in one session it stress-tested a conversation simulator we were building by throwing contradictory instructions at it. That saved us days of manual QA. If you zoom out, the maker ethos hasn't disappeared — it's evolved. For us, maker culture is a discipline: make small, test fast, learn loudly. Thanks for the thoughtful prompt! Don't hesitate to reach out if you need more info. Cheers, Justin Brown Co-Founder, The Vessel https://thevessel.io/
Client Relations Specialist at GO Technology Group Managed IT Services
Answered 8 months ago
At GO Technology Group, we've seen makerspaces evolve from simple "tinker labs" into strategic environments where schools and community organizations spark innovation. Our work often involves guiding these spaces with the right mix of technology; whether it's interactive display panels that bring collaboration to life, 3D printers that turn STEM concepts into prototypes, or secure device management for fleets of iPads and Chromebooks. What makes makerspaces powerful today is how they connect creativity with real-world skills, giving students and community members the chance to design, test, and iterate in ways that mirror modern workplaces. Looking ahead, tools like AI and GenAI are accelerating this shift. We're seeing educators combine AI-assisted design with 3D printing to move from concept to prototype faster, or leverage AI-driven collaboration platforms to enhance teamwork across devices. As a Chicago managed service provider, our role isn't just keeping the technology running; it's empowering schools and organizations with the IT support and consulting they need to sustain safe, scalable, and future-ready makerspaces that truly fuel innovation.
Nowadays, the Maker Movement is becoming one of the most potent innovative factors in various industries. Companies are also using maker spaces as cross functional brainstorming spaces to experiment with generative AI and AI applications, in addition to creating prototypes. These places enable intra-disciplinary inventiveness, with technology and design and art, and community problem solving forming a synthesis. They are increasingly used by academics, tech and other innovators to experiment, test ideas / concepts in rapid time and breakthrough the next generation solutions since humans + emerging digital tools are balance.
The maker ethos has definitely evolved from soldering irons and 3D printers into a much broader sandbox for experimentation, especially inside companies. We're seeing "corporate maker spaces" pop up as internal labs where employees can tinker with emerging tech like AI and GenAI without the pressure of immediate ROI. The value isn't just the prototypes that come out of it, but the culture shift—when people feel safe to experiment, they come up with unconventional ideas that wouldn't surface in a standard meeting. AI in particular has become a natural fit. I've seen teams use maker-style workshops to rapidly prototype AI-driven customer service bots, marketing content generators, or even supply chain forecasting tools. Because the barrier to entry is so low now—many GenAI tools are plug-and-play—you don't need to be a data scientist to test an idea. That democratization of innovation is powerful. Some companies also use maker spaces as a cross-disciplinary hub. Marketing sits next to engineers, who sit next to product designers, and suddenly you've got a cross-pollination of skills that sparks creative breakthroughs. It's less about the gadgets and more about the mindset: making gives people permission to play, and play is often where the real innovation happens.
I've always been fascinated by the Maker Movement for what it represented: curiosity, experimentation, and community. At its core, "making" was never only about technology or tools—it was about giving people the space to tinker, learn, and create something new. Fast forward to today, and I see that same energy being channeled into innovation through modern maker spaces, but now with AI and GenAI at the forefront. What's exciting is how these spaces have evolved. In the past, they might have been filled with 3D printers, woodworking tools, or soldering irons. Today, you're just as likely to find teams huddled around whiteboards, experimenting with AI-powered platforms, or running rapid prototyping sprints where ideas move from concept to reality in hours instead of months. For example, I've seen companies create "AI labs" where marketers, engineers, and designers work side by side, testing prompts, generating visuals, and refining workflows in real time. The AI essentially becomes another tool on the bench—a power tool for ideas. What makes this so powerful isn't just the technology itself but the mindset it cultivates. Maker spaces, whether physical or virtual, encourage people to try, fail, learn, and iterate without the pressure of perfection. That freedom to experiment lowers barriers, sparks creativity, and often leads to breakthroughs that wouldn't have happened in a more traditional, rigid setting. In my own experience, I've seen how this approach not only accelerates innovation but also strengthens culture. When people feel safe to experiment and collaborate across disciplines, they're more willing to share ideas, take risks, and stay adaptable. AI democratizes the "making" process, giving people with little technical background the ability to create something meaningful—whether that's drafting a PR campaign, mocking up product visuals, or building customer experiences. It transforms maker spaces into environments where everyone, regardless of skill set, can participate and contribute to innovation. The tools will always change, but the principle stays the same: when you give people permission, resources, and a supportive space to experiment, they'll surprise you with what they can create. For me, that's the future of innovation—a blend of human creativity and emerging technology, coming together in modern maker spaces that honor the spirit of "making," just in new and interesting ways.
Maker spaces have evolved from hobbyist workshops into real engines of corporate and academic innovation. Companies use them as low-risk labs where employees can prototype and test ideas quickly without long approval cycles. The biggest shift today is the integration of AI and generative tools, which accelerate design, automate routine tasks, and make it easier to move from concept to working prototype. Universities also reframe maker spaces as incubators that combine AI, robotics, and IoT, preparing students for interdisciplinary problem-solving. What hasn't changed is the spirit—rapid creation, breaking, rebuilding, and iterating. The difference now is that technology like AI compresses the distance between idea and execution, making innovation faster and more accessible.
Creating spaces that carry the spirit of the maker movement has influenced how we think about finance innovation at Fig Loans. Instead of a workshop filled with 3D printers, our "maker space" is a collaborative environment where engineers, product managers, and customer service teams experiment with tools like AI and generative tech to solve very real problems in lending. One example is how we've used these shared spaces to design loan products that balance affordability with transparency. We invite team members with different backgrounds to bring their own "making traditions" into the process. Someone with customer-facing experience might highlight pain points around repayment, while an engineer might prototype a smarter way to analyze repayment behavior using AI. That mix of perspectives sparks ideas that feel both practical and inventive. For us, innovation in finance doesn't come from sticking to formulas. It comes from creating a culture where building, testing, and remixing ideas is encouraged, much like a maker lab—except here, what we're building are financial solutions that people can truly trust.