10 Themes for the Next Ten Years - No 7

Number 7: #HumanIsTheNewLuxury
‘LLMs are the revenge of the Humanities Graduate’

As a History and History of Art Graduate, who bizarrely also spent twenty years coding and running software companies, it is very pleasing to see the rise of Large LANGUAGE Models, which are transforming what it means to code. Instead of understanding the odd syntax of Python or Javascript the new interface to computational power is language. Indeed the great AI Researcher Andrej Karpathy has said:

‘The hottest new programming language is English’

Natural Language Computing, where we use text or voice to interact with ‘the machines’, appears to be the future. Where we describe what we want, an LLM understands and processes our wishes, and then offloads the task or tasks to an army of computing ‘tools’ who do our bidding. Unlike historically where we had to precisely know how to do something, now the most important thing is to be able to describe precisely what it is we want done. Hence the revenge of ‘Humanities Graduates’ who have been trained to have great facility with words. The stumbling and mumbling of an archetypal ‘techie’ is now a hindrance. Clarity, precision and persuasiveness are all of a sudden superskills rather than arty affectations.

This is just one way that the future is going to be a lot more human than many people believe. Despite the world becoming ever more mediated by technology, it is going to be the acquisition and development of human skills that will become, for most people, their route to a successful life.

Because #HumanIsTheNewLuxury.

We humans are very hard to please materially. We strive to acquire the next big thing, are in thrall to it for a while once acquired, and then, every single time, become tired of it a little further on. It’s why so many very rich people are miserable; they rapidly learn that being able to have everything is a curse not a blessing. Arriving is no fun. The journey is always the enduring pleasure.

And with technology this is true in spades. There is a saying that ‘AI is anything that doesn’t work - as soon as it works it’s just…. statistics’. We move on very fast. It wasn’t that long ago that maintaining a phone signal while travelling in a car was hit and miss. Now we rage when our 4k video streaming at 80 mph drops off. Sam Altman, CEO of OpenAI has quipped that people veer between saying ‘AI will end the world’ one day to ‘It’s SO slow’ the next.

We're fickle. We're not really interested in technology itself - we care about what it enables us to do. And somehow, it's never enough.

Shania Twain nailed it:

‘Okay, so you're a rocket scientist
That don't impress me much’

And this will just become more and more obvious as technology improves. We’re realistically within 2-10 years of AGI - Artificial General intelligence, which OpenAI have defined as ‘a highly autonomous AI system that can perform most economically important tasks better than humans.’ But will we be impressed? For a while, but shortly thereafter it too will merge into the background. Once we can let AI do all the things needing doing, we’ll be back to the perennial question; Now what?

With a big caveat. That ‘perform most economically important tasks better than humans’ means that we’ll need to be inventing a whole new set of ‘economically important tasks’. Where the AI cannot substitute for us. We’ll need to be doubling down on being human. But being human that has economic value. Incentives matter to humans and we like to create value and be valued.

So where might this take us?

Where does our capacity for nuanced emotion, our desire for authentic connection, our appreciation of imperfection, become not just differentiators but essential qualities?

I think in seven key directions:

1. Personalised Experiences: This is a classic area where AI will help us be more human. It is very good at personalising at scale digitally, but if one can combine this personalisation with human delivery there are many opportunities to provide exceptional experiences.

2. Emotional Intelligence: Now, computers can ‘simulate’ emotional intelligence very well but there is an irreplaceable role for human empathy and understanding. Many high IQ people have very low EQ, but in a world where AI provides the IQ, working on one’s EQ makes a lot of sense.

3. Creative Problem-Solving: This is one of the great superpowers for the AI age. Problem solving alone is an intellectual muscle we all need to work on but if one can add creativity to it, then magical things can happen. From current research we know that using LLMs does raise the creativity of most people but it does so both in the same way, and in a different way to how humans are creative. We have more creative ideas, but they tend to all follow a similar pattern, and these ideas are not those we’d have left to our own devices. So humans need to work with LLMs but never lose sight of the need to inject humanity into the equation. Many products and services will be AI developed but the luxury ones will have that human je ne sais quoi.

4. Authenticity: The value of genuine, non-automated human connections will become incalculable. All our luxury moments will be authentic.

5. Artisanal and Bespoke Services: Custom, human-crafted solutions are already luxury offerings, but in a world of mechanical perfection we will actively seek out imperfection. The imperfect will be unique, the perfect a commodity. It is upside down, but humans like ‘character’ and few real characters are perfect. There is a sterility to perfect that we tire of. It is enervating. It bores us. We want to feel the human in the loop. Artisanal and bespoke services will definitely be a luxury we strive for. Think vinyl versus CD - the CD is perfect but vinyl speaks to your soul.

6. Human-Centered Design: Spaces and services designed to enhance human experiences and catalyse human capabilities will be the only spaces and services people actually want. They won’t always get them, but it will be what the luxury market provides. And as with personalised experiences, these will be the fruit of human + AI working in synergy, creating something that is better than either could create alone.

7. Community Building: The importance of human-facilitated social connections cannot be overstated. Remove community from society and we have nothing. This will be the ultimate luxury in an AI mediated world.

Given we spend more than 90% of our time inside buildings, real estate is the crucial canvas for bringing these human values to life. Here's six ways they might manifest themselves:

1. Concierge Services: High-touch, personalised property management will be the ‘premium’ offering. AI will help us know a lot about you but it’ll be a human that turns that knowledge into something special. Helping enable you to be ‘happy, healthy and productive’ is the aim, and that takes data, resources…. and a deft human touch.

2. Curated Spaces: Human-curated environments that cater to specific lifestyle needs will be essential. Curation is currently an under-appreciated skill - it won’t be in the future.

3. Relationship-Based Transactions: Personal, trust-based interactions in high-end real estate deals will distinguish them from the norm of automated transactions. Often we will want automated transactions but for those that really matter we want to deal with humans. If you could buy a home with just one push of a button, would you?

4. Experiential Retail: Retail was hit by online technology a decade, or two, before offices but it is clear that successful retail spaces focus on human-centred, memorable experiences. Offices will follow.

5. Wellness-Focused Design: ‘there is no wealth without health’ so spaces that prioritise human well-being and personal interaction are a very obvious luxury offering. This will become ever more so as we have more time to invest in it.

6. Community-Centric Developments: Real estate HAS to be designed to foster human connections and community engagement. We’re going to see a renaissance of mixed-use developments. The industrial era gave us  live, work, play separation - the AI era will bring all of these back together. Commuting is almost the antonym of luxury - AI will lead to its demise.

Does this sound like a world you’d enjoy? I think I would. Will it happen? I’m 100% certain it will, for some. #HumanIsTheNewLuxury is such a wonderful thing to aspire to. Putting humans, and humanity, at the centre of a good life.

The big challenge will be in making it the norm, not just a #Luxury.

Next Steps

What constitutes #Luxury in your business? Can that become your North Star to aim at? Let me know.

10 Themes for the Next Ten Years - No 6

Number 6: Outcomes as a Service - Beyond Software to Solutions

“Outcomes as a Service represents a shift from simply providing software or tools to delivering comprehensive solutions that guarantee specific results.”

This statement encapsulates a burgeoning hypothesis that promises to fundamentally reshape the technology landscape, particularly in industries like CRE.

Why SaaS Isn’t Enough Anymore
The traditional Software as a Service (SaaS) model, while revolutionary in its own right, is increasingly seen as a stepping stone to a more outcome-focused future.

This future is defined by Outcomes as a Service (OaaS), a paradigm shift where the value proposition moves beyond access to software and towards the guaranteed achievement of specific, measurable business results.

Driven by the demand for tangible value and empowered by advancements in Artificial Intelligence, particularly the emergence of sophisticated AI Agents, OaaS is poised to become the dominant model, profoundly altering the supply side of industries like PropTech.

The limitations of the pure SaaS model are becoming increasingly apparent. While SaaS democratised access to powerful software and streamlined operations, it often left the burden of achieving desired business outcomes squarely on the shoulders of the client.

Companies purchased software subscriptions, but the responsibility for successful implementation, user adoption, and ultimately, achieving tangible improvements, remained with them.

How AI and IoT Make OaaS Possible
OaaS addresses this gap directly. Rather than just providing a tool it offers a comprehensive solution, often combining software, hardware, services, and expertise, with the explicit commitment to deliver predefined business results.

The fundamental issue with Software as a Service is that in an AI mediated world there are things beyond just software that matter. With AI we need to understand what is possible, what data is required, how to collect it, how to cleanse it and then how to apply models to it that give us the outcomes we desire. It’s complicated. The number of moving parts has multiplied and a wide range of skills are needed to orchestrate a complete solution.

Software alone won’t get us where we want, and need, to go. And actually, we don’t want the process, we want the outcome.

It’s the difference between subscribing to, say, an energy management platform, and partnering with an OaaS company who will guarantee a specific percentage reduction in energy consumption, with their fees directly tied to achieving that target.

Other examples might be:

• Tenant Satisfaction Assurance: Committing to specific tenant satisfaction scores

• Sustainability Outcomes: Delivering specific environmental performance metrics

• Space Utilisation & Optimisation: Ensuring efficient use of space based on agreed metrics

This is the essence of OaaS – a move from selling (or buying) access to software to selling (or buying) tangible, measurable outcomes.

And several factors are converging to make OaaS the logical next step beyond SaaS.

Crucially, the demand for demonstrable Return on Investment (ROI) from technology investments is intensifying. Businesses are no longer satisfied with the promise of efficiency; increasingly they are demanding quantifiable improvements to their bottom line. Not least of all because, (whisper it quietly), they don’t know how to get the best out of all the software they’ve signed up to. We all know that installing software is one thing - getting your people to use it effectively is quite another.

But it is also because other technologies have matured and we now have access to IoT devices spitting out copious data points that have to be analysed in order to accurately measure and track progress towards specific outcomes. Our ‘Smart Buildings’ are outsmarting us!

The big push though is the new reality that AI is defining. We now have algorithms that can analyse massive datasets, identify patterns, predict future outcomes, and proactively optimise systems to achieve predefined goals. But …. it’s all very complicated.

On top of which we’re now seeing the emergence of AI Agents – autonomous software entities capable of performing complex tasks with minimal human intervention – and these are opening up whole new worlds of opportunity. Which, again, we mostly don’t understand but ‘know’ will be transformative.

These agents can continuously monitor building performance, adjust settings, even interact with tenants or building systems in real-time to drive specific outcomes like optimised occupancy or enhanced tenant satisfaction.

For example, an AI agent could dynamically adjust HVAC settings based on occupancy patterns and weather forecasts to minimise energy consumption, or proactively address tenant requests to improve satisfaction scores. This level of proactive, intelligent automation makes the delivery of guaranteed outcomes increasingly feasible and scalable. If only we had a way to get it all working.

Enter the OaaS providers. The ‘middleware’ if you like, between the technology and desired destination.

The Shift for PropTech Companies
It’s not just the demand side though that will be affected by all of this. The fundamental shift from selling software to selling outcomes will necessitate a dramatic transformation on the supply side, particularly for current PropTech companies. Their existing organisational structures, pricing models, and overall business models will need significant overhauls to effectively deliver on the promise of OaaS.

Organisational Changes Needed
First, organisational structures will need to evolve beyond feature-driven development and sales. Sales teams will need to become adept at understanding client business objectives and translating them into quantifiable outcome targets.

New roles, such as "Outcome Managers" or "Value Engineers," will become crucial, responsible for defining, orchestrating, and ensuring the delivery of agreed-upon outcomes. This will require strong project management skills, a deep understanding of both the technology and the client's business, and the ability to collaborate effectively across internal teams.

Data science and analytics will move from a supporting function to a core competency, critical for measuring progress, demonstrating value, and continuously optimising solutions.

Customer success teams will transform from reactive support providers to proactive partners, focused on driving adoption and ensuring clients achieve their desired results.

New Pricing Models
Secondly, the traditional pricing models of current SaaS companies will be disrupted. The predictable recurring revenue of subscription-based pricing will likely give way to more complex, performance-based models. We will see an increase in:

• Performance-based pricing: Fees directly tied to the achievement of specific outcomes (e.g. a percentage of cost savings, a fee per successful tenant placement).

• Risk-sharing agreements: Vendors share the financial risk, potentially taking lower upfront fees with larger payments contingent on achieving predefined targets.

• Value-based pricing: Pricing reflects the perceived value delivered to the client, directly linking costs to the realised business benefits.

This shift will require PropTech companies to develop sophisticated methodologies for measuring and tracking outcomes, along with robust contractual frameworks that clearly define the responsibilities and liabilities of both parties.

Evolution of Business Models
Finally, the overall business model will need to evolve from being primarily a software provider to becoming a comprehensive solution provider.

The software itself will become an enabler, but the true value will lie in the integrated suite of services, expertise, and partnerships that guarantee the delivery of outcomes.

This implies a significant increase in investment in areas like consulting, implementation, data analysis, and ongoing support.

PropTech companies will need to forge long-term, strategic partnerships with their clients, moving beyond transactional relationships to collaborative ventures focused on achieving mutual success. This also necessitates building ecosystems of partners to cover the diverse expertise required to deliver a wide range of outcomes.

What’s Next for the CRE Industry?
The question then becomes: who will be best positioned to capitalise on the OaaS opportunity? Several scenarios are plausible:

• Evolving Existing PropTech Companies: Some companies are beginning to experiment with outcome-based elements (Salesforce with their Agentforce service - Intercom with Fin, their customer support bot), though I’ve not seen it yet in PropTech. But they possess the core technology and understanding of the CRE industry. To succeed with OaaS, they will need to invest heavily in building out their service capabilities, developing robust data analytics infrastructure, and forging strategic partnerships.

• Emergence of Specialised Startups: We are likely to see the rise of new startups specifically designed to deliver niche outcomes within the CRE space. These agile companies can focus on specific problem areas and build deep expertise in delivering those particular results, potentially becoming acquisition targets for larger players.

• CRE Professional Services Firms: Established players like JLL, CBRE, and Cushman & Wakefield possess deep industry knowledge, extensive client relationships, and a strong understanding of client needs. They are uniquely positioned to integrate technology into their existing service offerings and offer comprehensive, outcome-based solutions. They could achieve this by developing their own in-house PropTech capabilities, acquiring promising startups, or forming strategic partnerships with existing technology providers. But, as history tells us, this is easier said than done. Particularly the adjustment to new core business models. How much of an ‘Innovators Dilemma’ does this constitute?

Ultimately, the future of technology in commercial real estate is likely to be shaped by a combination of these forces.

We may see the emergence of "ecosystem orchestrators" – potentially the larger CRE service firms or some of the more forward-thinking PropTech companies – who build platforms and cultivate partnerships to offer a broad spectrum of outcome-based services.

Regardless of who leads the charge, the shift towards OaaS would seem to be inevitable.

It represents a fundamental re-evaluation of value, placing the focus squarely on tangible business results and ushering in a new era of partnership and accountability.

It is an example of ‘Human + Machine Synergy’ - where new technologies enable things that were not possible before but maximising the potential requires a deep integration of human and computational capabilities. The very best outcomes will not be achieved by automation, but by a subtle blending of the quantitative with the qualitative.

We are humans after all.

Next Steps
If you’re curious about how OaaS might transform your business or want to share your experiences, let’s start a conversation. Your insights could shape the future of this paradigm shift.

10 Themes for the Next Ten Years - No 5

Number 5: Redefining 'what is the best affordable option?’

‘AI is not just making existing services more affordable; it's enabling access to high-quality services and products that were previously out of reach for many.’

We hear a lot about the downsides of Generative AI. It’s just a ‘Stochastic Parrot’, a plagiarism machine, a regurgitator of ‘average’. And, of course, ‘it’s not as good as a human’. And there are degrees of truth in all of this. But in a business context it all misses the point. Which is ‘can you afford better?’.

In business, the quality of service we receive is directly tied to what we can afford—and the same applies to the quality we provide. Every service operates within defined price points: pay more, get more. For decades, this has created a clear divide between those who can afford premium offerings and those limited to more basic options.

Generative AI is going to upend this apple cart. It is going to redefine what is meant by ‘affordable’. In terms of the services you receive, or the services you supply. In short, it is going to massively redefine ‘the best affordable option’.

In seven key ways:

1. Accessible Expertise: Generative AI-driven tools enable expert-level analysis and services at a fraction of conventional costs, making capabilities once reserved for large enterprises or high-net-worth individuals accessible to a much broader audience. Although these insights might not always be perfect, they are often “good enough” for immediate operational decision-making—and can then be refined through human oversight where needed. This opens the door for smaller companies to provide such things as strategic advisory at scale, low cost legal and compliance services, as well as rapid prototyping.

2. Generative AI as ‘Infinite Interns’: Think of these tools as a limitless pool of junior-level support—tirelessly parsing data, generating drafts, performing research, and handling repetitive tasks. This offloads routine work from expensive human resources, who can instead focus on higher-value activities. Think of using AI for research & data aggregation, customer service & lead qualification or content generation.

3. Co-intelligence Augmentation: Rather than treating Generative AI and humans as separate or competing entities, co-intelligence augmentation emphasises collaborative problem-solving. AI handles large-scale pattern recognition, humans handle strategic oversight, judgement, and creativity, resulting in solutions that neither could achieve in isolation. An example might be AI generating proposals optimised for energy efficiency or occupant wellbeing, with human experts refining for aesthetics and regulations.

4. New Product Enablement: Generative AI’s ability to rapidly analyse, adapt, and improve, can lower barriers for products and services that were previously too resource-intensive or complex to develop. By automating high-cost processes, AI frees budgets and human resources for innovation and experimentation. Dynamic pricing, space as a service marketplaces, new categories of health-focused living and working environments - what might we conceive of with a little more time to think?

5. Democratisation of Luxury: Previously exclusive, high-end experiences can now be delivered at scale through AI-driven operational efficiencies. By automating costly service components, businesses can offer premium experiences to broader market segments at more accessible price points. What might be possible in areas like personalised virtual experiences, or concierge services?

6. Scalable Personalisation: Generative AI can process large amounts of data about individual customers, tenants, or partners, allowing companies to deliver tailored offerings at a mass-market scale. This merges the best of mass production (cost efficiency) with the best of customisation (unique user experiences), opening up opportunities for exceptional tenant-focused solutions, on-demand amenities or custom financial products etc.

7. Augmented Decision-Making: Generative AI-powered analytics bring predictive insights, risk modelling, and scenario planning capabilities that were once the domain of top consulting firms or large corporate strategy teams. This levels the playing field for smaller companies competing in complex or rapidly shifting markets such as real-time market forecasts, scenario planning or financial & risk analytics.

Collectively, these 7 demonstrate how Generative AI is reshaping the business landscape by lowering barriers, boosting efficiency, and unlocking new forms of value creation.

What’s more it is important to appreciate that this is a moveable feast.

In autumn 2024, Klarna announced that they were planning on replacing Salesforce and Workday with internally developed AI-driven workflows. Now they are a tech company and have the internal skills to do something like this, whereas most companies could not. But with every month that passes the capability of off the shelf tools is increasing and this is enabling more and more companies to create sophisticated, customised solutions that were previously only available through high-end SaaS providers.

We’ve previously discussed (Theme Number 3) the rise of ‘Fast, Agile, Ultra-Productive Superteams’ and it is companies made up of these that will be pushing hardest in the 7 areas above. As they do, we’re going to see the landscape of who does what in real estate undergo a lot of change.

All of this amounts to a level of competitiveness that is new to the real estate industry. Combine deep domain knowledge and advanced, cutting edge technologies and the ‘best affordable option’ is not what it was just a few years ago. Extrapolate forward a few years - where might it be then?

10 Themes for the Next Ten Years - No 4

Number 4: Removing Friction and Enabling Discovery

What Does Not Change
Jeff Bezos said in 2021 that he thinks less about what’s going to change and more about 'What's not going to change in the next 10 years?' …. because you can build a business strategy around the things that are stable in time. ... in our retail business, we know that customers want low prices, and I know that's going to be true 10 years from now. They want fast delivery; they want vast selection.’

In the commercial real estate industry I’d posit that ‘Removing Friction and Enabling Discovery’ will be forever a constant. Our customers, and actually all our stakeholders, want to be able to do what they need to do painlessly, and based on the best possible information.

From a Bond to a Business
Historically, the commercial real estate industry has been designed to operate like a Bond, a financial instrument. What mattered was security and constancy of income. 25 year Leases, with 5 yearly “upwards only” rental increases were the norm at the start of my career. These morphed into 15 years, with 3 yearly reviews and have slowly gone down from there. Some still occur, but the norm now is for single digit lease lengths and ‘maybe’ a mid term review.

In practice, and despite the ‘living in denial’ mindset of much of the Investment community, the real estate industry is now, at core, an operational business. The days of effectively ‘lock up and leave’ being the ‘operating model’ are over. As such, our customers are now our users, not our investors. For investors to achieve the returns they want we have to put their interests behind those of our customers. Sure, they do not like this, and many are refusing to accept the new reality, but the smart ones are onboard and realise this is a massive opportunity to outperform. We are moving beyond everyone rising or falling in lockstep; today, you can differentiate yourself like never before.

And removing friction and enabling discovery are the foundations upon which you’ll build your differentiation.

Removing Friction
We all know that ‘friction’ has traditionally been endemic within real estate. How we consume or interact with space has been riddled with clunky processes that make it uncomfortable, time-consuming and inconvenient. And the same has applied to real estate transactions and business models.

For example:

• Complicated lease agreements: Lengthy, jargon-filled contracts that are difficult to understand and negotiate.

• Inflexible lease terms: Long-term commitments that don't adapt to changing business needs.

• Manual and inefficient processes: Think slow payment systems, manual access control, clunky visitor management, or outdated communication methods.

• Poorly designed spaces: Workspaces that don't support the activities people need to perform, are uncomfortable, or lack necessary amenities.

• Lack of transparency: Opaque pricing, hidden fees, and difficulty finding accurate information.

• Inefficient property searching: Difficulty filtering for spaces which meet the specific needs of a user.

And all this ‘friction’ has been at the expense of user experience. Which, to be honest, no-one cared much about in the ‘Real Estate as Bond’ days. It was just the way the industry worked. Today though, as we were learning before the pandemic but which those years made absolutely clear, no-one NEEDS an office, or a retail store - they have to be made to WANT them. And in this new world the old ways of real estate have no place.

Friction is the enemy of user experience, and has to be ruthlessly expunged, if you want to achieve product/market fit. As demand changes, so must supply. And this is not going to change.

Customer-centric design, technology integration, flexibility, adaptability, and all round operational excellence - these must form the core of our new operating procedures.

And mostly the user must not notice - the joy of a great user experience is the absolute removal of friction. Everything just works, exactly as you need it to.

Discovery: Empowering Choice and Efficiency
On the flip side, "enabling discovery" is about making it easy for people to find what they need, when they need it, and how they need it within the real estate context. This involves:

• Seamless access to information: Providing clear, concise, and readily available information about spaces, services, availability, pricing, and building performance.

• Personalised experiences: Tailoring the user experience based on individual needs and preferences. Think recommendations for spaces, services, or even connections with other users or occupiers.

• Data-driven insights: Leveraging data to understand user behaviour and preferences, enabling better space utilisation and informed decision-making.

• Intuitive interfaces: Using technology to create user-friendly platforms for booking spaces, managing services, and interacting with the building ecosystem.

• Serendipitous encounters: Designing spaces and experiences that facilitate chance meetings and connections between people, catalysing  collaboration and innovation.

The key is to anticipate user needs, even before they are aware of them, and ensure resources are readily available when required.

The Role of Technology
Technology, of course, is the key to removing friction and enabling discovery. We need to:

• Automate processes: Streamlining tasks like lease administration, payment processing, and maintenance requests.

• Provide real-time data and analytics: Offering insights into space utilisation, energy consumption, and user behaviour.

• Create digital marketplaces: Connecting occupiers/customers with landlords and service providers through online platforms.

• Enhance the user experience: Providing mobile apps for booking spaces, controlling building systems, and accessing amenities.

• Facilitate flexible space models: Enabling on-demand access to workspaces, meeting rooms, and other resources.

• Enable smart buildings: Using sensors and IoT devices to optimise building performance and create more responsive environments.

Essentially we need to understand the ‘wants, needs and desires’ of our customers in highly granular way, and then over satisfy them. Doing so is in reality about more than just technology, and the human creation and curation of the user experiences is a critical component, but with new technologies, especially AI, we can automate a lot of the ‘human touch’. Doing so authentically, rather than robotically, is going to become a super skill of real estate operators, but it is a necessity as the level of services now required is such that it cannot be provided economically through ‘humans’ alone.

The Foundations of #SpaceasaService - The TrillionDollarHashtag
Removing friction and enabling discovery is only possible with a deep knowledge of, and empathy for, the customer, but it is what provides the foundations for true #SpaceasaService. That is:

• User-centric: Focused on meeting the needs and expectations of the people who use the space.

• Flexible and adaptable: Able to respond quickly to changing business and market conditions.

• Efficient and sustainable: Optimising resource utilisation and minimising environmental impact.

• Data-driven and intelligent: Leveraging data to improve decision-making and create better experiences.

• Transparent and accessible: Providing clear information and easy access to services.

This is a call for a fundamental shift in the real estate industry. By embracing technology and adopting a user-centric approach, real estate can transform from a static asset into a dynamic service that empowers people and enhances their lives.

It isn’t just about improving existing processes, but developing entirely new business models. That recognise that the way to maximise value is by providing more than just space. In an AI mediated world (that is become more pervasively so each year) we need to focus on what can be done in our ‘assets’ that cannot be done in others. That act as a maven and a magnet for successful, forward thinking, businesses attuned to the new dynamics of business.

The commercial real estate industry ‘knows’ that it is at a liminal point, where it is morphing from what is to what will be. Importantly investors are slowly working their way to acceptance of this fundamental change from being a Bond to a Business. Last week I read a well known investor comment ‘Can real estate survive as a distinct asset class, or will it be absorbed in the real assets and private equity envelope?’. My instinct is that the industry is going to become ever more operational, ever more focussed on user experience, and ever more technologically savvy. And underpinning everything will be the quantitative and qualitative tools that ‘remove friction and enable discovery’.

We all want to spend our lives inside great real estate. Whoever provides that is going to win!

Next Steps
What's the first step your organisation could take tomorrow to remove friction and enable discovery? Would you want to be your own customer? Imagine your were - what then?

We’d love to hear your thoughts—what’s your biggest friction point, and how are you addressing it?

10 Themes for the Next Ten Years - No 3

Number 3: Fast, Agile, Ultra-Productive Superteams

The New Paradigm
The future of work will be characterised by small, highly skilled teams that leverage AI and advanced technologies to achieve exceptional productivity and innovation.

Seven Key Characteristics of Superteams

These "superteams" represent a new paradigm in organisational structure and performance. And they share key characteristics:

First off, they lean in heavily to AI augmentation, automation and synergy. Augmentation is where an AI enables you to achieve more in a given time, automation where you offload entire tasks (perhaps even goals - see last weeks newsletter), and synergy is where by working with AI you are able to create levels of output neither you, or an AI, can achieve on their own. Every task is assigned to one or other of these buckets.

Secondly roles tend to be fluid and team members adapt quickly, taking on various roles as needed. No-one is defined by their title - indeed titles are often done away with altogether.

Thirdly this is a world of rapid Iteration. Superteams are predicated on being able to prototype, test, and refine ideas at unprecedented speeds. This emphasis on rapid iteration isn't about 'move fast and break things.' Rather, the very act of working at speed necessitates a heightened level of focus and precision. Speed concentrates the mind not through recklessness, but through the need for careful, deliberate action.

Fourthly there is an emphasis on cross-functional expertise. Teams combine diverse skills and perspectives for holistic problem-solving. This approach not only breaks down traditional departmental silos but also enables teams to identify interconnected issues and opportunities that might be missed when viewed through a single disciplinary lens.

Fifth is a belief in data-driven decision making, often leveraging AI for real-time insights and predictive analytics. This does not eschew “gut” feeling (which is the brains synthesis of knowledge and experience) but does ground the team in reality. Realities can be changed, but not without acknowledging them first.

Sixth, and very much in the spirit of our times, continuous learning is core to these teams’ success. Team members constantly upskill and adapt to new technologies. The more you know the more you realise you don’t know.

And finally, these teams are very likely to be experts at remote collaboration. Our Cities have historically been the best venues for talent matching, but in an AI mediated world, nowhere agglomerates like the Internet. Often the best teams are dispersed because that is how you get the best people together. Increasingly we’ll be seeing seamless integration of in-person and virtual teamwork. Now the market for distributed working tools is so large, the supply of them is growing rapidly. Yes we need to be together, but we also need to be apart. Super productive teams work accordingly.

Some large companies will be able to create and curate superteams internally, but the natural habitat of such teams is going to be startups and smaller entities, often forming collaborative ecosystems to tackle complex projects. This dynamic is increasingly resembling the film industry, where individuals and small companies coalesce and disperse as projects begin and end.

The Economics Behind the Shift
Everything boils down to co-ordination costs, as the economist Ronald Coase pointed out in "The Nature of the Firm”, in 1937. This provides a fundamental explanation for why companies exist and how they determine their optimal size. He wrote about transaction costs and co-ordination (organisation) costs. His theory suggests that a company should expand until the cost of organising one more transaction within the firm equals the cost of carrying out that transaction in the market. In other words:

• If it's cheaper to do something internally (lower coordination costs than transaction costs), the firm should grow.

• If it's cheaper to outsource something to the market (lower transaction costs than coordination costs), the firm should remain smaller or contract out that activity.

How AI Lowers Coordination Costs
Now AI is poised to have a significant impact on both transaction costs and coordination costs, and will reshape how companies are structured and how they compete.

With transaction costs, AI enhances search and information acquisition, enables automating contracting and negotiation, and improves monitoring and enforcement.

With coordination costs, AI improves communication and collaboration, can automate task management and workflow optimisation, and power more informed decisions.

From Ecosystems to Micro-Multinationals
This, in turn, will make smaller companies more competitive, give rise to the ‘Micro-Multinational’, and opens up the potential for more decentralised organisations. Meanwhile enabling larger companies to focus on their core competencies, and outsource the rest.

This ‘feels’ inevitable.
Sure, these small, fast, agile, ultra-productive superteams are not appropriate everywhere in business, definitely have the potential to ‘combust’, and need smart, sophisticated management, but the upside from the wise pairing of ‘Human + Machine’ is so great that one can’t help but believe that at least some of them are going to perform outstandingly well. There are memes about ‘One Person Unicorns’ which seems outlandish, but it no longer feels impossible.

Y Combinator, the startup accelerator and venture capital firm, has recently been briefing about the potential for companies operating AI ‘Agents’ to be bigger than the SaaS industry. As they say:‘

Al replaces both software AND labor costs
Companies spend far more on employees than on software, making these smaller companies far more efficient and requiring far fewer employees’

The Real Estate Perspective
Commercial real estate is an intensely personal but also deeply technical industry. As such it is almost perfectly shaped to adopt AI. Last week we wrote ‘We need to look for workflows where AI and humans can each play to their strengths while compensating for each other's weaknesses.’ - CRE is full of these.

This further fuels the rise of superteams, given their complementary nature. What we need is to find the people with the characteristics mentioned above AND the sensibilities of a Real Estate person. People who can add intuition and judgement to analysis. Causal understanding to correlation.

This shift will likely present a significant challenge, especially for the largest incumbent firms. While smaller, more agile players may readily embrace this new approach, the largest firms face significant inertia. Their current market dominance may offer short-term protection, but a major digital transformation will be essential for long-term competitiveness.

Looking Ahead
My bet is that we’ll see the rise of a new breed of real estate company, with entirely different operating procedures, that embraces AI and all new technologies, and that will unbundle and re bundle the industries workflows (as discussed in last week’s newsletter), and lead us to somewhere very different.

These companies are going to be enormously productive. By optimising around the seven key characteristics of superteams, they will be very much working with AI, whereas many are going to be stuck competing against AI. And that is somewhere you really do not want to be.

Food for Thought
"What's the first step your organisation could take tomorrow to move towards enabling these kinds of high-performing, AI-augmented teams? And what's stopping you from taking that step today?"