AI 2030: What happens when AI goes mainstream?
In 1,650 days it will be the year 2030. 2025 is already seeing an acceleration in the process of automation, at a speed and pace of change that has outstripped the previously planned and measured expansion of workplaces. Workplaces stand out today as complex ecosystems that are embracing change and undergoing profound transformation. As such, they provide the ideal setting for an informed strategy on the impacts of technology transformations across the globe.
Confronting that reality, UnWork and WORKTECH convened an internal Workplace Transformation & AI workshop with more than thirty leading architects, building operators, engineers, project managers, and workplace strategists who rotated through five exercises. With sweeping decision-making powers, they have worked in partnership with employees and representative groups to deliver answers to the most urgent contemporary working challenges. Their notes paint a remarkably clear picture of both opportunity and risk.
We’re humans working with humans (connection and collaboration)
Today the physical and social fabric of the workplace must catch up with new cultural adjustments and demographic transformations in the workforce. The first step is to reconnect the workforce to the workplace environment and remove friction from common experiences. Many of the technologies required to achieve such a goal are in place already, using a diverse range of approaches from connection to collaboration. Apps like Kadence autobook space for you, depending on your schedule, making sure premium collaboration space is for meaningful in-person interactions.
Designing with, not against the machine (assistants and apps)
“AI will eliminate 80% of PM tasks by 2030” says Gartner, 2018. “We currently think of cross-functional project teams as a group of individuals, but we may soon think of them as a group of humans and robots. Today our technologies are somewhere between AI agents, systems that can take actions, and innovators, AI that can aid in invention. ClickUp generates workflows based on your priorities and Forecast helps operational leaders plan, run and track project in one platform. Clockwise navigates complex schedules to build in uninterrupted deep-work periods. Zoom automates summaries, generates action items and drafts follow-ups.
Saving costs by directing energy to the right places (space management)
The built environment contributes 37% of global energy emissions (UNEP). AI technologies are being re-worked for an age of healthier workplaces, based around energy and cost reduction, environmental sustainability, efficient use of existing resources. XYSense accurately and anonymously counts people entering and exiting spaces. It uses AI to produce occupancy insights, so building operators can forecast workforce space needs. Doing this supports them reducing the operating cost and energy expenditure of buildings by rightsizing commercial space, validating space types and allocating resourcing to only working floors. One medical company saved $60M in leasing costs with another $1.5M saved in build-out.
Innovation in workplace experience
The future of work is clean, safe, healthy, convivial and productive workplaces. The innovation is in technology adapting to human needs: data and automations are ensuring comfortable workplace experiences without manual intervention. AppSpace is one such company, measuring CO2 levels and ensuring optimal environmental conditions by closing space that doesn’t meet quality standards. CXAI uses agentic AI booking via voice command to seamlessly remove friction from common experiences.
At the close of the workshop, it was argued that the theme emerging from 2025 was transformation. This change naturally poses questions for the workplace: what long-term dependencies are such transformations putting before us and how flexible are these forms to change? How are new technologies demanding different infrastructures and questioning the traditional role of workplaces?
The coming 5 years will see answers unveiled, as we start to form a better understanding of how AI will look in 2030.
