In today's fast-paced society, emerging generations, driven by a relentless quest for happiness and well-being, are demanding work environments that are in harmony with their individual values. These environments provide a haven from the relentless onslaught of digital stimuli to which they are constantly exposed.

While there is a general consensus on this need, illustrated by various movements such as The Great Resignation which emerged in the wake of the Covid-19 pandemic, there is as yet no universally identified solution other than widespread 'teleworking', which in itself is not a solution but rather a countermeasure.

However, for the first time in human history, we have methods, derived from artificial intelligence, capable of ingesting the multiple parameters of the social equation that greatly affect the efficiency of our working environments, in order to coordinate our dispersed solutions in both the design and day-to-day management of workspaces with a view to perhaps finally achieving Operational Excellence.

Deciphering our digital footprint to get to know us better

A study carried out by Domo Inc, entitled Data Never Sleeps 10.0, reveals that each individual generates around 150 GB of data every day. This data encompasses not only our digital interactions, but also everyday aspects of our lives such as our spending habits and our movements, all meticulously recorded by various devices such as surveillance cameras in urban spaces, IoT sensors scattered around buildings, smartwatches and our mobile phones.

However, the real challenge is not so much collecting this data as our ability to collate, format and structure it so that we can then interpret it in a meaningful way and ensure consistency among the inferences drawn from it.

This is where the superiority of artificial intelligence lies. It detects subtle correlations between different parameters with exceptional efficiency, and identifies recurring patterns in large quantities of data to reveal configurations that conform to our predefined objectives, without proving cause and effect relationships.

Let's take a few examples to better illustrate this new approach to solving everyday problems in our offices.

Data-driven space-time planning

WeWork, one of the world leaders in coworking, has been a pioneer in optimising the design and allocation of meeting rooms by taking advantage of artificial intelligence. Historically, determining the number of meeting rooms in an office was a challenge, often leading to inefficiencies with either too many underused rooms or a lack of available space. WeWork applied machine learning, specifically a neural network algorithm, to understand and predict meeting room usage patterns based on a number of factors such as company size and office layout. By analysing data from more than 800 meeting rooms around the world and taking into account variations in architectural designs, the company trained the model to predict meeting room usage with notable accuracy, outperforming human intuition by around 40%. This has enabled WeWork to create spaces that more accurately match the real needs and preferences of occupants, encouraging greater interaction and productivity, and paving the way for more accurate architectural planning and design. The effectiveness of the model is expected to improve continuously as more data becomes available, demonstrating the potential of AI to revolutionise architectural design and space allocation on a large scale.

Living (adaptive) buildings to harmonise comfort needs and ecological imperatives

The history of architecture has repeatedly shown that there is no such thing as a universal comfort temperature. Efforts to standardise deterministic algorithms (PMV, PPD) since the 1960s, aimed at predicting thermal satisfaction in order to automatically regulate HVAC systems, have led to widespread dissatisfaction and an increase in mass absenteeism. The adaptations introduced in the 2000s with the emergence of bioclimatic architecture, which gives occupants the freedom to regulate environmental parameters, have only partially solved the problem, as it is almost impossible to reach a consensus on environmental parameters between colleagues sharing the same space.

During this collective dissonance, the new ecological constraints were perceived as a punishment. From now on, no office should be heated above 19 degrees Celsius. However, the notion of 'thermal comfort' is much more complex than it seems, and depends on many factors other than ambient temperature alone, such as relative humidity, air speed, our metabolic rate and our level of clothing. But all this is subjective for each individual and changes throughout the day.

The first step towards a solution is to realise that humans have a dynamic perception and that they self-regulate every second to adapt to their environment. The environment must therefore adopt the same attitude and adapt every second to the changing needs of its occupants in order to serve them better. This is the way to avoid mismatches between energy needs and availability.

More concretely, our buildings need to learn usage patterns and preferences, and make automated micro-adjustments to maintain optimum conditions and comfort. Integrated with IoT devices and sensors, AI can analyse real-time data on environmental conditions as well as occupant density and preferences, so that we can find an optimal level between occupants' personalised comfort based on their individual preferences, and ecological requirements in terms of energy expenditure.

The same approach can be applied to other factors in the physical environment around us - lighting, acoustics, even olfaction - both quantitatively and qualitatively. Thanks to this intelligent control, companies can improve employee well-being while considerably reducing operating costs and energy consumption.

This dynamic, real-time match between needs, which depend on numerous external factors, and the resources needed to satisfy them, is surely the only way to ensure responsible consumption as part of our energy transition.

Accessible tools already available

Over the last decade, a new generation of software, enhanced by Artificial Intelligence, has emerged, amplifying the capabilities of our traditional software. What sets these modern tools apart is their innovative approach, in which the user's role shifts from designing or analysing data to identifying and formulating needs as a strategist.

In other words, our primary role is gradually evolving into that of "formulating the right questions", enabling AI to establish a solid working foundation. It does this by meticulously examining data from thousands of projects similar to ours, with the precision and acuity of a human expert. This frees us up to devote more time to fine-tuning the details of this AI-initiated work base.

The carefully selected examples below aim to highlight the discreet but essential contribution of AI to the design and management of spaces, including working environments.

Finch3D

Created in Sweden by a team of two architects and an engineer, Finch3D stands out as a parametric design tool designed to automate the generation of plans based on predefined constraints and objectives. Thanks to its Artificial Intelligence-powered engine, it facilitates accelerated design iterations, enabling architects to explore a multitude of design options with agility. Finch3D provides instant feedback on design performance, helping to detect errors at an early stage and offering optimal solutions to ensure regulatory compliance. In addition, its seamless integration with renowned tools such as Revit, Rhino, and Grasshopper simplifies the architectural design process, positioning Finch3D as a robust player in the AI-led revolution to create more adaptive and efficient working environments.

Maket.ai

Another start-up called Maket.ai, co-founded by architectural technologists, presents itself as a generative design platform capable of transforming a programme - essentially a list of rooms with dimensions and proximity relationships - into an elaborate architectural plan. The designer can iteratively impose more constraints on the generated plans, refining the results to better meet the original design intent.

Maket.ai also provides users with a virtual assistant capable of providing guidance on materials, costs and design options, helping users to make informed decisions at the outset of a project.

Space Designer 3D

Developed by Asynth SAS, a company co-founded in Paris in 2009 by two architects, Space Designer 3D is a general-purpose framework for designing, visualising and managing spaces in the cloud, enabling the creation of bespoke software that can be integrated into companies' established operational processes. It has the flexibility to be enriched with third-party data, processes and algorithms, allowing CAD and BIM files to be exchanged, and also establishes bi-directional interaction with ERP and CRM data, making space management more integrated and interactive.

By way of illustration, Saltmine, a Singapore-based start-up, has built its workspace design solution on Space Designer 3D technology. By leveraging various relevant datasets, Saltmine provides recommendations on how workspaces could evolve using its AI-based recommendation algorithms. The tool helps to use the insights or feedback gathered to optimise design time, improve operational efficiency and reduce management-related costs.

It is indeed remarkable that many of these innovations come from start-ups, often initiated by visionary young architects, rather than from construction software titans such as Autodesk, Nemetschek or Dassault Systèmes. These start-ups bring a breath of fresh air and an innovative approach to the sector, unveiling solutions that fully exploit the potential of artificial intelligence. They seem to be demonstrating greater agility and responsiveness in adapting to new technologies and evolving user requirements. This dynamic is invigorating the market and generating vigorous competition, encouraging all players, including the most established, to innovate and continually refine their offerings.

We are only at the dawn of this Revolution

The advent of artificial intelligence in the field of work environments means a significant shift in our trajectory towards greater Operational Excellence. By deciphering the complex weave of spatial dynamics, AI is metamorphosing into a maestro, orchestrating a myriad of solutions to the long unexplored enigmas of our professional spaces. The emergence of technology start-ups, armed with the arsenal of AI, sketches out a future where technology and humanity converge to create more optimal and resonant working environments.

However, we are only at the dawn of this Revolution, and the horizon of exploration remains vast and unexplored. Time will tell how these nascent innovations will adapt to the growing demands for personalisation and efficiency, and what resonance they will find in the grand socio-economic narrative.