Can innovation truly deliver affordable housing to those who need it most?
Updated
January 8, 2026 6:35 PM
Close up of a 3D printer nozzle pouring concrete. PHOTO: ICON
The affordable housing crisis has become one of the most pressing challenges of our time. Across the globe, millions of people are struggling to secure a roof over their heads. In cities like San Francisco, housing prices are so high that even middle-income families find themselves shut out of the market.
The root of this crisis lies in a persistent imbalance: the supply of housing has failed to keep pace with growing demand. Factors such as high construction costs, bureaucratic hurdles, and limited available land in urban areas have made it increasingly difficult to build enough homes quickly and affordably. The result is a market where housing remains inaccessible to millions, even as the need becomes more urgent.
Technology is now stepping in to address these challenges in ways that were unimaginable just a decade ago. From streamlining construction processes to introducing new financing models and data-driven tools, tech innovations are rethinking how homes are built, financed, and accessed. But while these advancements offer hope, they also raise important questions: can they truly address the root causes of the housing crisis, or are they simply patching up a fractured system?
The housing crisis begins with supply shortage: we simply aren’t building enough homes. Traditional construction methods are expensive, slow, and reliant on labor that is increasingly hard to find. This is where technology is making its most significant impact. Startups likeICON and Veev are leading the charge, using cutting-edge solutions to make housing more efficient and affordable.
ICON, for instance, uses 3D printing to build homes faster and at a lower cost. By printing the structure of a house directly on-site, ICON reduces waste, labor requirements, and construction time. Entire neighborhoods of 3D-printed homes are already being built, showcasing how this technology can scale.
Veev, on the other hand, focuses on prefabricated construction. By manufacturing high-quality components like walls and steel frames in a controlled factory environment, Veev eliminates inefficiencies associated with on-site building. These components are then assembled on location, drastically reducing construction time and costs. This approach mirrors the principles of mass production seen in industries like automotive manufacturing, where efficiency and scalability are key.
While building more homes is essential, access to housing often depend son financing. For many people, especially those with low or irregular incomes, the traditional mortgage system presents insurmountable barriers. Fintech innovations are stepping in to make housing financing more inclusive and flexible.
Access to affordable housing often hinges on financing, and innovative financial technology (fintech) solutions are beginning to change the landscape. Some platforms are offering new ways for individuals to transition from renting to owning, while others are introducing shared equity models that reduce the traditional barriers of large down payments and strict credit requirements. For example, companies like Point use shared-equity financing, where homeowners receive funds in exchange for a percentage of their home’s future value instead of taking on traditional debt. Meanwhile, startups are building tools that automate and simplify and revolutionizing the mortgage process, making it easier for underserved populations to access loans tailored to their needs.
Blockchain technology is also changing the game. By digitizing land titles and creating secure records of financial transactions, blockchain reduces the complexity and difficulty of accessing credit, especially for those with limited traditional credit. This is particularly impactful in regions where informal economies dominate and traditional proof of income is scarce. These tools create a pathway to homeownership for individuals who would otherwise be excluded from the system.
Beyond building and financing, technology is transforming how we understand and address housing needs. Artificial intelligence (AI) is revolutionizing risk assessment in the mortgage industry by analyzing a broader range of financial behaviors, such as rent and utility payments, to provide a more inclusive picture of creditworthiness.
At the same time, AI and big data are helping policymakers and developers make smarter decisions about where and how to build. By analyzing population trends, commuting patterns, and infrastructure needs, these tools ensure that new housing developments are built in the right places, reducing wasteful construction and improving urban planning.
For example, startups are using 3D scanning and machine learning to map informal settlements and identify buildings at risk of collapse. These insights not only improve safety but also guide investment toward areas where housing is most desperately needed.
The housing crisis is one of the most complex challenges of our time, and technology alone cannot solve it. But it can provide powerful tools to address specific pain points, from streamlining construction to expanding access to financing. Startups like ICON, Veev, and Landis are proving that innovation can lower costs, improve efficiency, and make housing more inclusive.
However, the ultimate solution lies in a combination of technology, policy reform, and community engagement. Governments must work alongside tech innovators to create urban environments that prioritize affordability, sustainability, and accessibility.
The future of housing isn’t just about building more homes; it’s about building smarter, greener, and fairer cities where everyone has a place to call home. By integrating cutting-edge technologies with forward-thinking policies, we can move closer to a world where affordable housing is not an aspiration but a reality.
The question is no longer whether technology can solve the housing crisis—it’s how we will use it wisely to create lasting change.
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Backed by Menlo Ventures, BrainGrid tackles planning gaps as AI makes software building accessible to more founders.
Updated
April 1, 2026 8:37 AM
A phone screen with app icons. PHOTO: UNPSLASH
As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.
That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.
The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.
In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.
BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.
The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.
For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.
The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.