In central Sharjah, HWKN is set to develop the UAE’s first AI-planned district featuring offices, cafés, childcare and healthcare facilities, and a mosque. District 11 responds to a specific urban gap the city that is historically residential and institutionally rich, but lacking in integrated commercial hubs. HWKN’s approach proposes a walkable ‘work resort’ that reflects the local context while introducing new forms of professional and social interaction, and integrated living.
Each of the masterplan‘s eleven buildings has been shaped by AI-generated prompts informed by HWKN’s research into Sharjah’s climate, cultural identity, and urban morphology. These inputs guided the planning of massing, shading strategies, and spatial configurations, particularly in relation to heat mitigation and walkability, with the goal being to expand the possibilities of automated design by using AI to compress research cycles and simulate environmental and programmatic outcomes before a single line was drawn.
District 11 aims to rethink the structure and social function of office neighborhoods in the Gulf, particularly by embedding AI into the conceptual framework of the masterplan itself. Matthias Hollwich, HWKN’s founding principal and known for his early research into aging and workplace design, describes the firm’s approach as a ‘reverse-engineering process,’ where AI is deployed to generate form based on desired social outcomes. Here, that means prioritizing collaboration, walkability, and thermal comfort, concepts that are less centered in commercial development, especially in the Gulf.
This AI-influenced methodology is also not HWKN’s first. The firm introduced the Work Resort concept in London’s Canada Water Dockside development, bringing together commercial workplace and hospitality logics. In Sharjah, that model is taken further and scaled to the level of an urban district, with the firm using AI across the entire project lifecycle: from environmental simulations to spatial programming and long-term adaptability. The intention is to use AI as a tool for reverse-engineering environments that prioritize collaboration, climate responsiveness, and walkability — criteria that is often secondary in conventional commercial planning.
