More intelligent computing is starting to revolutionise how businesses work
Artificial Intelligence (AI) is a family of computer learning techniques that emulate the human ability to analyse and draw conclusions from diverse types of data. A key feature of AI is the array of learning techniques (such as machine learning, deep learning, computer vision etc.) that enable computers to continually self-learn, refine and improve. Deep learning for example, is a form of AI whereby machines use algorithms much in the same way as human brains do (which, as you know, uses a lot of data!). Clive Thompson of Wired magazine sums up the extensive influence deep leaning already has in the modern economy:
"Deep learning is the reigning monarch of AI. In the six years since it exploded into the mainstream, it has become the dominant way to help machines sense and perceive the world around them. It powers Alexa’s speech recognition, Waymo’s self-driving cars, and Google’s on-the-fly translations. Uber is in some respects a giant optimization problem, using machine learning to figure out where riders will need cars."
Maurice Grassau, CEO and Founder of Architrave shares with James Pearson, CBRE, how organisations need to streamline their processes and start exchanging data rather than PDFs and documents. They discuss how the gap between landlords who focus on efficiencies, and those that do not, is growing dramatically.
Architrave uses Artificial Intelligence to read documents and turn them into data, making documentation easy for property owners and managers with its platform for digital real estate management.
- More productive location decision making: Through taking into account a greater volume of hyper-personal data, the understanding of location becomes more complete and real time.
- Predictive maintenance: Increased ability through AI (and IoT) to anticipate the need to maintain or repair asset equipment.
Professor Nicolai Wendland, Co-Founder of 21st Real Estate shares with James Pearson, CBRE, how technology can enable investors make more agile and safer real estate decisions and drive real estate returns.
21st Real Estate creates tools and technologies to digitise and streamline the acquisition process for commercial real estate buyers.
AI can already drive better location decision making from both occupier and investor point of view, bringing in more ‘live’ data from various sources, and automating the insights. Numerous companies like this already exist.
Automating business processes transforms business models in order to enable humans to make better decisions, thus boosting productivity and revenue.
For landlords, AI can enable more effective deployment of flexible office, retail and I&L concepts across portfolios. With more live data on occupancy and “revenue-per-occupied-unit-of-space” fluctuations throughout the day, across assets and geographies, landlords will be able to more quickly and accurately understand the live arbitrage between more traditional, longer term leases, and more on-demand use of space.
Similarly, for occupiers, with AI-powered insight they will understand the need for longer-term core space versus flexible space across portfolios. Portfolio planning cycles will be shorter, leading to more effective utilisation of portfolios across assets and geography.
Supply chains will find it hard to keep up with AI, but through improving occupier and investor collaboration, supply chains may well reach their true AI-enabled state.
AI is already being used to drive more efficient and productive use of industrial and logistics space.
AI will be able to reconfigure workspaces depending on the activities happening on any given day, for example through understanding live workplace occupancy metrics throughout the day, and changing the workplace design as a result. This not only drives workplace efficiency, but the productivity of employees as a result.
AI has the ability to automate processes in a facilities management context, understanding equipment usage metrics on an ongoing basis and providing automated, actionable insights as a result. This, ultimately, can drive down energy and maintenance costs while also ensuring the smooth running of services for building users throughout the day.
We asked Tripty Arya, Founder and CEO of Travtus, about the potential impact of Artificial Intelligence, alongside the complexity of implementing it in the commercial real estate world.
Travtus is a London based Artificial Intelligence Research & Development company with an aim to automate property management by 2021.
In the future, AI’s impact won’t just be on boosting productivity and revenue, but through “higher-quality, more personalised, and data-driven products and services” for customers, clients and employees.
AI is already enabling retailers to personalise recommendations for their consumers. The next step will be tracking online-to-offline sales journeys in order to understand the “productivity” of physical stores and how retailers might finesse the in-store experience. Shopping centre landlords in particular should consider the monetization opportunities for introducing AI driven sales tracking into their stores.
AI will be able to revolutionise the employee work day in terms of their consumer experience, putting them well and truly at centre of the workplace. This can be achieved by understanding employee preferences (e.g. coffee, preferred working environments throughout the day etc.) and constantly refine their consumer touchpoints throughout the day. These refinements are then delivered either through mobile devices or physical experiences, depending on the employee preference in question.
CBRE’s Nick Wright and Jo Tasker from Tech London Advocates discuss the growing desire for tech in the property industry, and the need for better education and understanding.
Tech London Advocates is a network of more than 6,000 tech leaders, entrepreneurs and experts in London, across the UK and in over 50 countries worldwide.
- Objective: Improve customer experience through giving faster and more accurate movie recommendations, and increase sales conversion rate .
- What they did: Custom-built machine learning recommendation engine, replacing the work of a human editor updating recommendation lists.
- Outcome: 25% reduction in average number of movies scrolled past before purchasing. Customised recommendations to every single customer, ensuring personalised experience.
- Hiring the right AI talent: AI talent is currently scarce across the industry. What’s more, there are very few AI or data scientists with real estate experience, so hiring from the best universities and training the best talent in the industry, could be an option.
- Clear AI strategy: Don’t go into AI blind – AI requires a clear strategy and roadmap that has executive sponsorship in order to prove concepts and ultimately sustainable return on investment.
- Cost of deploying AI: The cost of deploying AI can vary depending on your strategy. Outsourcing can be more cost efficient but may not yield sustainable results. Developing in-house can be more expensive in the long-run but can ultimately embed value in your business processes.
- Government collaboration: AI is still in its infancy and could potentially have a massive impact on the development of the modern economy and politics. As AI develops, collaboration with public bodies and even other companies could be crucial to its enduring success.
- Changing role of the CIO: The CIO or the CTO will no longer be a pure service function but will be a pivotal C-suite role driving the long-term vision of companies.
- Collaboration with other business departments: Likewise, with the CIO, AI projects will only drive long-term business value if there is true collaboration between CRE functions, IT, HR and business units. Siloed activity will not lead to success.
- Educating existing workforce: As AI initiatives become increasingly embedded in business activity, educating the existing workforce will become more important, particularly as AI skills are currently scarce.
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- Will the future AI/Human relationship lead to an “AI Winter?” FT, 2018
- The Death of the CIO and the rise of HR uk, 2019
- Changing skills, not the death of jobs McKinsey, 2018
- Shrinking jobs is a myth McKinsey, 2018
- How do sectors and countries vary in AI deployment? McKinsey, 2019
- Where in your business should you deploy AI? McKinsey, 2018
- The future of work McKinsey, 2018
- Monetizing AI, PWC, 2018
- AI and smart building controls, In-building tech, 2019