EXCLUSIVE: Alteryx’s Sabya Sen on AI and Dubai’s Real Estate Future

As Dubai’s real estate market continues to evolve, developers are increasingly turning to data, analytics, and artificial intelligence to support decision-making across project planning, sales, and investment strategies.

With off-plan transactions remaining a dominant force in the market and new supply continuing to enter the pipeline, the ability to interpret real-time buyer behaviour, forecast demand, and optimise project performance has become a key competitive differentiator.

In this interview, Sabya Sen, Vice President, Head of IMEA & APAC at Alteryx, discusses how analytics is reshaping real estate development, helping developers improve launch strategies, understand buyer preferences, reduce risk, and prepare for an increasingly data-driven future.

Interview: Sabya Sen, Vice President, Head of IMEA & APAC at Alteryx

How is the continued growth of Dubai’s off-plan market changing the way developers plan and launch new projects?

The pace of Dubai’s off-plan market shows how quickly developer decisions now need to be made. With off-plan transactions accounting for 76% of residential sales in Q3 2025 and more than 366,000 units in the pipeline through 2028, the market is leaving less room for static feasibility studies or planning based only on historical cycles.

The next step is making sure developers have the right data in place to track sales velocity, buyer trends, competitor launches, and infrastructure progress as conditions change. That is where analytics becomes a practical enabler, helping developers move from fixed assumptions to a clearer, real-time view of demand, supply, and risk as conditions change.

Why is real-time buyer demand data becoming more important in a market with such a high volume of new launches?

When dozens of projects launch simultaneously across overlapping districts, the window between buyer awareness and commitment to a competing development narrows. Traditional lagged market reports, even monthly ones, only describe where demand was, not where it is moving in real time.

Developers now need immediate visibility into evolving buyer behaviour. Real-time signals from CRM pipeline activity, website enquiry trends, broker registrations, digital engagement, and payment plan preferences provide a dynamic view of market demand as it develops.

Alteryx helps developers unify these fragmented signals across sales, marketing, and operational systems into a single analytics environment, enabling teams to get faster visibility into buyer intent signals and respond more quickly with more informed pricing, inventory, and launch decisions rather than relying on static reports that may already be outdated by the time they are reviewed.

How can analytics help developers improve launch timing, pricing strategy, and inventory release decisions?

These three decisions — timing, pricing, and release sequencing are deeply interdependent, and getting them wrong in combination is where margin gets destroyed. A tool like Alteryx allows development teams to run scenario models that simulate different launch windows against competitive supply schedules, test pricing sensitivities by unit type and floor level against comparable transactions, for instance, those recorded in the Dubai Land Department registry, and model the revenue impact of releasing inventory in tranches versus front-loading.

The goal would not just be to find the optimal scenario, but to understand the risk profile of each alternative, so commercial directors can make decisions with full visibility rather than relying on a single-point forecast.

What role does data play in improving lead quality and helping sales teams focus on more serious buyers?

In a high-volume launch environment, a developer's sales team can be flooded with thousands of registrations, most of which represent speculative interest rather than genuine buying intent. Without scoring models, salespeople waste time on low-probability leads while serious buyers, who may transact quickly, slip through.

Alteryx enables developers to build predictive lead scoring models that draw on historical buyer behaviour: which nationality profiles historically complete, which payment plan structures correlate with lower cancellation rates, and how soon after registration a serious buyer typically books a viewing. These models surface the highest-probability opportunities at the top of the funnel, letting sales teams allocate their time where conversion is most likely.

In a competitive off-plan environment, how can forecasting tools help developers reduce risk and make better investment decisions?

The two biggest risk categories for an off-plan developer are demand-side risk — launching a product the market won't absorb at the price needed — and delivery-side risk — missing handover milestones that trigger payment plan defaults or reputational damage.

Alteryx can address both. On the demand side, absorption models calibrated to micro-location supply data help developers stress-test take-up assumptions before committing to a land purchase or launch programme. On the delivery side, connecting construction progress data with payment obligation schedules lets finance teams model cash flow exposure if completion slips and proactively restructure to prevent a crisis.

McKinsey's analysis of more than 500 global capital projects found that cost overruns average at least 79% above initial estimates and schedule delays average 52%. The developers who get ahead of that curve are the ones treating delivery data as a financial instrument, not just a project management report.

How can developers use analytics to better understand buyer preferences across location, unit type, payment plans, and amenities?

Buyer preference data exists in almost every developer's systems; it just sits in silos. CRM records capture enquiry specifics; reservation contracts capture unit choices; payment plan selections reveal financial appetite; post-handover feedback captures satisfaction drivers.

Alteryx connects these disparate sources into a unified preference model, which can then be segmented by buyer nationality, investment versus end-user intent, and project type. The output is a genuinely actionable brief: a developer launching in Ras Al Khaimah, where average property prices grew 39% year-on-year in 2025, can know with precision whether their target market in that location skews toward two-bedroom end-user units with flexible post-handover payment plans, or one-bedroom investor units with high rental yield projections and design their product mix accordingly, before the architects finalise the layouts.

Do you expect data and AI-driven decision-making to become a standard part of real estate development and sales strategy in Dubai?

It already is, for the developers who are winning. The question is how quickly the rest of the market catches up because in a pipeline as competitive and concentrated as Dubai's, the analytics gap between developers will increasingly translate into a commercial gap.

Developers who can forecast absorption, score leads, model delivery risk, and simulate pricing scenarios in near real-time will launch with greater confidence, sell through more efficiently, and protect their margins when market conditions shift. Those still running feasibilities on spreadsheets and reading monthly market reports after the fact will be perpetually reactive.

The UAE government's own ‘We the UAE 2031’ goals around smart city infrastructure and digital economic transformation make the data trajectory clear. AI-driven decision-making in real estate is not a future capability; it is the present competitive baseline, and Alteryx is built to make it accessible to every developer's commercial and finance team, not just those with dedicated data science departments.