This Is Not a Prediction. This Is What We Live Every Day.

I want to be clear about something: this is not a provocation, and it is not futurism. This is what we are living every day at Quanthome.

Our engineers have not written a single line of traditional code in three months. Everything is built through AI-assisted development, prompt engineering, and structured data pipelines. The software industry itself is being reinvented by AI, and we are watching it happen from the inside.

What excites me most is not a single technology but a structural shift: when data is properly structured behind the scenes, AI can generate interfaces, dashboards, and analyses on demand. The traditional software model, where you pay for a fixed application, train your team to use it, and adapt your workflow to its limitations, is collapsing. In its place, something far more powerful is emerging: ask a question, get exactly the analysis you need, in the format you want, in seconds.

This represents a fundamental power shift. In the old SaaS era, value lay in the application, the tool that organized and presented data. In the emerging Data-as-a-Service era, value migrates entirely to the data itself. The interface becomes irrelevant. What matters is having rich, structured, accessible data that AI agents can leverage.

Some analysts predict this "agentic economy" could be 10 times larger than the SaaS industry. That is not incremental change. That is the complete inversion of where value resides.

The New Economics: On-Demand Everything

Consider what this means practically. Today, you pay annual licenses for software that does perhaps 20% of what you actually need, with 80% of features you will never touch. You pay for dashboards designed for generic use cases that never quite fit your specific questions. You pay for interfaces that require training, maintenance, and constant adaptation to your workflows.

In a Data-as-a-Service world, none of this exists. You ask a question. An AI agent queries your data. It builds exactly the visualization, analysis, or report you need. When you are done, it disappears. No license. No training. No maintenance. Just the answer you needed, delivered in the format you wanted.

The cost implications are staggering. Software development, interface design, user training, ongoing support: all of these expenses collapse when AI can generate purpose-built tools on demand. Early evidence suggests that organizations with well-structured data are seeing analytical costs drop by orders of magnitude.

But here is the catch that should keep every CEO awake at night: this only works if your data is structured, accessible, and governed. If your information lives in scattered spreadsheets, incompatible systems, and PDF reports, you are locked out of this new economics entirely. You will continue paying premium prices for software to compensate for data chaos while competitors with clean data infrastructure access insights at a fraction of the cost.

The divide is stark. Structured data means dramatically lower costs and instant insights. Unstructured data means you are still living in 2015, paying 2015 prices, operating at 2015 speed.

Why We Chose to Build a Data Company, Not a Software Company

When we started Quanthome, everyone expected us to build dashboards and features, the classic SaaS playbook. Instead, we invested everything into structuring data: unifying building-level information with fund analytics, ESG metrics, and financial performance across the entire Swiss market.

People told us it was invisible work. That clients would not pay for infrastructure they could not see.

But I was convinced that in a world moving toward AI, the only lasting competitive advantage would be the quality and depth of your data. Software would become a commodity; data would become the moat.

That bet now defines everything we do. And it is proving right faster than I expected.

Today, we do not just provide data. We help our clients structure theirs. Because we have learned that the barrier to this new world is not technology. It is data readiness. The firms that cannot participate in the DaaS economy are not lacking software. They are lacking the structured data foundation that makes AI-powered analysis possible.

Why Real Estate Faces This Reckoning First

Here is the paradox: real estate has long been considered a technological laggard, trapped in a world of Excel spreadsheets and fragmented systems. Yet this very characteristic makes it the industry where the SaaS-to-DaaS transition will be most consequential.

The industry is simultaneously data-rich and data-poor. It generates massive amounts of information: property valuations, lease contracts, market comparisons, building sensor readings, energy consumption data. Yet much of this sits in silos, unstructured and inaccessible. A Deloitte survey found that over 72% of global real estate owners and investors plan to invest in AI-enabled solutions, while more than 60% still rely on legacy technology.

Regulatory pressure is mounting. Switzerland's climate disclosure ordinance now requires large companies to report climate-related risks in line with TCFD guidelines. The real estate sector accounts for nearly 30% of Switzerland's CO₂ emissions. Firms need granular data: energy grades, carbon footprints, climate risk exposure. In the old world, you would buy specialized ESG software. In the new world, you need structured ESG data that any AI agent can query and analyze on demand.

Competitive advantages are forming rapidly. Firms that can close acquisitions 30% faster using AI insights, or optimize property management with predictive analytics, will leave competitors behind. But the advantage does not come from having better software. It comes from having better data. The software is generated on the fly. The data is the moat.

The Promise That May Finally Be Kept

The digitalisation of the real estate industry has been promised since the early 2000s. Two decades of pilot projects, proof of concepts, and incremental progress. Conference presentations. Innovation labs. Strategic initiatives that went nowhere.

It may finally happen, not through traditional software adoption, but through AI systems that remove the friction entirely.

This could reshape everything. The processes, the analysis, the construction workflows, BIM, facility management, investment decision-making, portfolio monitoring. The entire value chain of the built environment is about to be transformed.

And this time it is not a promise. The technology is here.

For institutional investors, fund managers, and asset owners, this means accessing real estate intelligence the way they access financial data today. Instantly, conversationally, without intermediaries. Want to know which office buildings in your portfolio have the highest energy usage per square meter? In the old world, you would navigate through your energy management software, export data, manipulate it in Excel, and build a chart. In the Data-as-a-Service world, you ask the question. The analysis appears. Tailored to your exact need.

The Sovereignty Question

As data becomes the core strategic asset, a troubling question emerges: who controls it?

For years, a handful of tech companies have accumulated outsized control over global data and cloud infrastructure. In the SaaS era, this dependence was somewhat masked. You licensed software, and your data happened to live in someone else's cloud. Uncomfortable, perhaps, but manageable.

In the Data-as-a-Service era, this dependence becomes existential. If the data is the only thing that matters, and someone else controls your data, then someone else controls your business. Your decision-making autonomy vanishes. Your AI agents can only know what their data sources allow them to know.

If your institutional investment firm is wholly dependent on a single provider's data feeds for allocating billions in capital, who is really making the decisions?

Building for the Future

The end of software is not a threat. It is a liberation. We are standing at the threshold of an era where institutional real estate can access analysis and insight that would have cost millions in custom development, generated on demand for pennies. Where the barriers between questions and answers disappear entirely.

But this future has a price of admission: structured, governed, accessible data. And it requires a clear-eyed approach to how you build your data foundation.

Trust your partners. In a world where data is everything, relationships matter more than ever. Work with partners who understand your business, who are invested in your success, and who will be there as the landscape evolves. The technology is moving fast. You need partners who move with you.

Diversify your sources. Do not put all your resources into one monopolistic company. Use various sources of truth. The firms that depend entirely on a single provider for their data and intelligence are the firms most vulnerable to disruption, price increases, and loss of control. Build redundancy. Maintain options. Preserve your autonomy.

Structure your data. This is the work that determines everything else. The difference between participating in the new economics and being locked out is not budget or talent or vision. It is whether your data is ready. Audit what you have. Invest in structuring what you need. Partner with specialists who can help you get there.

The firms that structure their data today will shape the industry tomorrow. The firms that do not will find themselves paying premium prices for commodity insights while competitors operate at speeds and costs they cannot match.

So ask yourself this simple question: Is your data ready for a world where the software does not matter anymore?

The answer will determine everything.