Advanced & in Real Estate 2021 Prepared by Investa 2 3

Contents

Part 1: Foundations 4 Part 3: Challenges and risks 17 Property is the largest Introduction 5 What are the challenges with Artificial Intelligence? 18 What is Artificial Intelligence (AI)? 6 a. Demonstrating a return asset class in the world on investment 18 What is (ML)? 6 b. Scarcity of technical skills 18 c. Data quality and quantity 19 and the time is now What is Deep Learning (DL)? 6 d. Integration 19 What are the different types What are the risks of Artificial for Investa to bring of Artificial Intelligence? 6 Intelligence? 20 a. Narrow (or weak) AI 6 a. Cybersecurity 20 b. Artificial General Intelligence b. Legal responsibilities 20 advanced analytics and (AGI) or strong AI 7 c. Failure 20 d. Regulatory non-compliance 20 What is the history of Artificial e. Reputation 20 artificial intelligence Intelligence? 8 Part 4: Applications and use cases 21 Why is Artificial Intelligence into the value chain popular now? 9 What are the applications of Artificial Intelligence? 22 What are the benefits of a. Real estate 22 Artificial Intelligence? 9 b. Commercial real estate 24 a. Reduced “human error” 10 b. Less risk 10 Artificial Intelligence as a c. 24/7 10 Service (AIaaS) 25 d. Repetitive tasks 10 e. Digital assistants 10 What is the future of Artificial f. Faster decision making 10 Intelligence? 25 a. The AI-enhanced organisation 26 Part 2: Force multipliers 11 b. Autonomous everything 26 c. Pervasive knowledge 26 Force multipliers of decision d. Enhancing the human intelligence 12 experience 26 Six force multipliers 12 Conclusion 27 a. Explore 12 b. Evaluate 12 c. Experiment 15 d. Engage 15 e. Execute 16 f. Expand 16

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Introduction thereby provide a better user As our models and data sets experience for tenants, investors become more sophisticated over Big data, Artificial Intelligence and customers – or risk being time, we will see increasing levels (AI), proptech and digital left behind. of return on the investment in this transformation get a lot of capability. attention and rightly so. At Investa, we are actively investing in data and decision Part 1 of this article defines AI, Data from Google shows that all intelligence. We believe that it Machine Learning (ML) and Deep of these terms have experienced is first about asking the right Learning (DL) and looks back at its significant growth over the past questions, then having the right history, how we got here and how five years in particular. people, data and technology to we can benefit. Using just the lens of the property find the answers. Part 2 looks at six force multipliers industry, it’s clear that many Investa believes that organisations that businesses use to drive a ROI organisations in property are will derive a real competitive from data and AI. sitting on vast, ever-growing, advantage by building decision quantities of data. Part 3 focuses on some of the intelligence capability, and challenges and risks that come But it’s not just about data. that the opportunity is “now.” with AI. In the next few years, data will Forward-thinking property Part 4 outlines some specific become increasingly available. companies will progressively real estate use cases of AI. Leaders in the real estate industry be able to see and realise value will need to evolve quickly to that the general property market unlock meaningful insights and cannot see.

Part 1: Foundations

Source: https://trends.google.com/trends/?geo=US

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What is Artificial What is Machine a Narrow (or weak) AI Intelligence (AI)? Learning (ML)? Narrow or weak AI operates AI refers to the wide-ranging Understanding the difference within certain limitations and is a simulation of human intelligence between AI, machine learning, and simulation of human intelligence. by machines. deep learning can be confusing. It’s often focused on executing a single (or narrow) task really well. The goal of AI is to solve the kind of Venture capitalist Frank Chen problems or perform the types of made this distinction: Much of narrow AI is powered tasks that are usually completed by machine learning and deep “AI is a set of algorithms and by humans, with our natural learning. This AI can often intelligence to try to mimic human intelligence. outperform humans in a specific intelligence. Machine learning is niche task – especially if the There are two main types of AI: one of them, and deep learning task relies on historical knowledge The first is “Weak AI” or Artificial is one of those machine learning and data. Narrow Intelligence; and the techniques.” second is “Strong AI” or Artificial Some examples of narrow AI ML feeds a machine (computer) General Intelligence. include technology that is broadly data and uses statistical used: Google, Siri, Alexa, self- AI will typically demonstrate some techniques to help it learn how driving cars, chatbots, translators, of the following characteristics: to progressively get better at social network recommendations. planning, learning, reasoning, a specific task. ML consists of The most famous example here is problem solving, perception, both supervised learning and IBM’s Watson. motion, manipulation and to a unsupervised learning. lesser extent, social intelligence At Investa, we have been using and . What is Deep Learning (DL)? AI/ML in our business for years. For example, we use cybersecurity According to Artificial Intelligence Deep Learning (DL) is a type of AI software to detect potential : A Modern Approach, by Stuart machine learning that runs data threats, and search engine AI Russell and Peter Norvig, AI can through brain-inspired neural across our internal files and be defined by four fundamental network architecture. The neural emails. approaches: networks allow the machine to go deep in its knowledge-base, In addition to these baseline use 1 Thinking humanly making connections and cases, we are focused on narrow 2 AI use cases that make an impact Thinking rationally weighting data. b Strong AI systems tend to be on our business, customers, Artificial General Intelligence 3 more complicated and are often Acting humanly investors and employees. (AGI) or strong AI What are the different types the subject of science fiction. We 4 Artificial General Intelligence is Acting rationally of AI? For example, identifying new the creation of a machine with are not yet deploying AGI into our development sites to acquire, businesses, but it is definitely on The first two approaches centre AI falls typically under two human-like intelligence that can or what tenants are the best fit our radar for the future. around thought processes and categories: Narrow (or weak) AI be applied to any task. It seeks to to occupy our buildings. This reasoning, the latter two focus and Artificial General Intelligence replicate the cognitive abilities of application of narrow AI allows us on behaviour. (AGI) or strong AI. the human brain. to augment what we do as humans and remove some of the repetitive When presented with an unfamiliar tasks in our business. task, a strong AI system should be able to apply knowledge from another domain or task to find a solution autonomously.

Investa Advanced Analytics & Artificial Intelligence in Real Estate 8 1 Foundations 9 istory of Artificial Intelligence 143 14

Warren McCullough and Walter Pitts Donald Hebb publishes the book, publish A Logical Calculus of Ideas The Organization of Behavior: Immanent in Nervous Activity. The A Neuropsychological Theory. The book paper proposed the first mathematic proposes the theory that neural model for building an artificial neural pathways are created from Artificial intelligence had its start in antiquity network. experiences and that connections by mathematicians and Greek philosophers. between neurons become stronger But when we think of artificial intelligence in the more frequently they're used. Why is AI popular now? modern-day terms, its history spans less “Investa understands the benefits that than a century. Here is a timeline of some of the key milestones in AI. Increased computer power has been a significant driver for AI, can be derived by leveraging both the especially infrastructure speed, intelligence in our data, as well as availability and scale. What used 1 14 12 10 to be run in specialised labs with in our people, to ultimately drive access to supercomputers, can The "Dartmouth Summer Research The Georgetown-IBM machine Arthur Samuel wrote the first Alan Turing publishes Computing now be deployed on the cloud at business value.” Project on Artificial Intelligence" at translation experiment automatically game-playing program for checkers Machinery and Intelligence, proposing Dartmouth College is organised by translates 60 carefully selected with sufficient skill to challenge a what is now known as the Turing Test, a fraction of the cost. Allen Newell (CMU), Herbert Simon Russian sentences into English. human player. a method for determining if a machine Jonathan Callaghan, CEO, Investa (CMU), John McCarthy (MIT), Marvin is intelligent. Minsky (MIT) and Arthur Samuel (IBM). The term "Artificial Intelligence" Harvard undergraduates Marvin Minsky Thanks to critical mass and the was coined by John McCarthy. This and Dean Edmonds build SNARC, the conference is considered the birth of first neural network computer. awareness of natural language artificial intelligence. Claude Shannon publishes the personal assistants, like Siri “Before Empirical CRE entered human to compute. Humans excel paper "Programming a Computer for Playing Chess." and Alexa, AI has also become the market (commercial real at creativity and ambiguity – using Isaac Asimov publishes the "Three mainstream. Large players are estate), data providers focused on the insights from AI to support Laws of Robotics." investing heavily in it and AI has limited groups of properties using decision making and negotiation. fuelled an explosion of AI-based the basket approach, which in Investa has partnered with start-ups across industries such turn provided a limited picture of cutting-edge AI platform provider as healthcare, finance, insurance, certain datasets without access to 1 1 1410 11 SparkBeyond, to accelerate and real estate and many more. real-time or frequent captures amplify the way in which the John McCarthy develops the AI Allen Newell, Herbert Simon and J.C. The Lighthill report by Professor Sir Digital Equipment Corporation of trends. programming language Lisp and Shaw develop the General Problem James Lighthill gives a mostly develops R1 (also known as XCON), the Big data is another driver for AI business collects, organises, publishes the paper Programs with Solver (GPS), a program designed to adverse verdict on AI research in first successful commercial expert Common Sense. The paper proposed a imitate human problem-solving. Great Britain and the United States, system. Designed to configure orders complete AI system with the ability to leading both British and U.S. for new computer systems, R1 kicks off in recent times. The increase in Empirical CRE’s objective is to analyses and draws insights learn from experience as effectively Herbert Gelernter and Nathan governments to discontinue support an investment boom in expert systems as humans do. Rochester develop the Geometry for AI research. This period is known that will last for much of the decade, data has created a strong demand track all properties regardless of from data. Theorem Prover program. as the "First AI Winter." effectively ending the first "AI Winter." R1 saves the company $40 million a for solutions that go beyond size, geography, or type across Arthur Samuel coins the term year by 1986. “Using AI to generate data- "machine learning" while at IBM. simple data analysis and instead all major metro areas to provide driven insights to inform decision John McCarthy and Marvin Minsky promise deep, new insights and landlords, agencies, and their establish the MIT Artificial Intelligence intelligence is a cultural shift Project. intelligence. Data is the fuel for research teams a platform with for many organisations. In our AI, and as data sets become more standardised content to aid experience, doing it well requires accessible, higher quality and critical decision making in one strong collaboration across the cost less, the barrier to entry of the highest value real estate organisation to allow AI and for building effective AI models markets in the world,” said Doug 200 200 2002 1 humans to play to their strengths. decreases. Curry, Empirical CRE. Google launches an app on the new Blue Brain is born, a project to iRobot creates Roomba, the first IBM's Deep Blue chess machine It has been a pleasure to work Apple iPhone with speech recognition. simulate the brain at molecular detail. commercially successful robot for the beats world chess champion, home. It autonomously vacuums the Gary Kasparov. As real estate is the largest asset As the data in real estate matures, closely with the Investa team to floor while navigating and avoiding obstacles. class in the world, there is a large an increasing number of property support them through this cultural amount of data that we can use companies will be able to access shift and we’re excited to see for our use cases at Investa. This and derive value from these data this translate into real business data is becoming better, but is sets, which will allow them to value.” Katherine Leong, Impact still disparate, incomplete, hard to leverage AI/ML even further. Strategist, SparkBeyond. access and difficult to structure. What are the benefits of AI? The benefits of AI complement 2011 2014 201 201 Investa partners with data rather than replace humans. Here providers such as Empirical CRE to Humans and AI work like a are some of the benefits of AI. IBM's Watson computer defeats Google makes the first self-driving car Google DeepMind's AlphaGo defeats Alibaba developed an artificial television game show Jeopardy to pass a state driving test. world champion Go player Lee Sedol. intelligence model that scored better build robust data sets, but there is partnership. champions, Brad Rutter and Ken The complexity of the ancient Chinese than humans in a Stanford University Jennings by a significant margin. game was seen as a significant hurdle reading and comprehension test, a large amount of work, creativity This victory went viral and was hailed to clear in AI. scoring 82.44 on a set of 100,000 AI excels at complexity and finding as a triumph for AI because Watson questions. and knowledge required to hunt had to answer riddles and complex patterns in vast quantities of data questions, using a range of AI and structure the data we need. techniques. – which would be impossible for a

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“It has been a pleasure to work closely with the Investa team to support them through the cultural shift - using AI to generate data driven insights to inform decision intelligence - and we’re excited to see this translate into real business value.” Katherine Leong, Impact Strategist, SparkBeyond

a Reduced human error d Repetitive tasks f Faster decision making Humans as we know aren’t perfect As part of life, humans perform Thanks to the sheer amount of and we make errors. many repetitive jobs. Think of data points that AI can process Using AI, computers can avoid manually inputting data into Excel and analyse, AI can enable faster (or reduce) making these human , replying to emails decision making. or verifying documents. errors, providing greater accuracy For example in September 2019, and precision. This has the effect With deep learning and machine Investa partnered with AI-platform of increasing productivity in the learning, AI can become smarter provider, SparkBeyond. economy and driving growth. over time. It can take care of The purpose of the partnership repetitive tasks and increase was to accelerate and amplify b Less risk business efficiency. how Investa collects, organises, Reducing the risk to human life In the property industry, AI can be analyses and draws insights is one of the most significant used to analyse tenant requests from data, at a scale not advantages of AI. and anticipate what types of previously possible. requests will be logged (and Robots driven by AI can be used AI enables Investa to harness when). This allows organisations to on Mars, to defuse a bomb and previously untapped insights from better predict tenant issues and even for natural disasters. hundreds of internal, external enables them to provide better, and open-source data points, From a business perspective, proactive customer service. AI can remove risks by flagging enabling unprecedented decision anomalies like fraudulent intelligence across a range of e Digital assistants transactions, it can monitor core business areas including equipment and it can even suggest In the realm of sales, marketing acquisitions, tenant attraction and preventative maintenance. and customer service, AI can retention, pre-emptive building be used to augment human operations, optimal deployment of interaction. capital and aligning investors with c 24/7 the right opportunity at scale. Another benefit of AI is the sheer For example, chatbots can be used workload it can carry. on a website and social media to engage with users and pre-qualify Where the average human can them with questions that can Part 2: work for 8 hours a day, including better direct their enquiry within some breaks, AI machines can the business. Chatbots can also be operational 24/7 and without operate 24/7, allowing users in Force any downtime. different time zones to chat with a For the property industry, there business at a time that suits them. is a benefit for use cases that At Investa, we are starting to multipliers require constant monitoring – experiment with a digital concierge like optimising energy usage service, which can provide in a building for example. service at our buildings outside of standard business hours.

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“At Investa, we are multiplying and amplifying the talents, “Applying Decision Thinking to sources, providing a clear picture innovation, capability gaps or any Data, AI/ML and Insights use of the value (and value for money) other area they want to go after, experience and creativity of our people through data & AI.” cases gives senior executives each option would deliver against while understanding the value the confidence and clarity they the things the leadership really trade-offs between options,” Joanna Marsh, General Manager, Innovation & Advanced Analytics, Investa need to make decisions on care about. Most importantly, said Paul Gordon, CEO Catalyze. where to focus attention to win. the creation of bespoke decision A properly structured decision criteria and adoption of a rigorous Force multipliers of discuss the business problems insufficient and can lead to issues process enables clear comparison decision method mean that decision intelligence and the impact that solving downstream. between options, even when there organisations can deliberately these problems would have is disparate data and information gear their decisions toward Data, AI/ML and insights are force More detail is required to on our strategy and business multipliers. They are tools to adequately understand the performance. potential benefits and also the solve business problems and they Below is a tornado chart showing how we prioritise data and analytics use cases against the cumulative An output of this workshop may be risks of embarking on each allow organisations to leverage weighted value of each. This allows us to clearly see which problems if solved, will deliver the largest ROI a long list of [50+] use cases that use case. people, systems and resources to against our strategic criteria. would make a difference. maximise impact. At Investa, we use decision For example, Google is a force For example, in commercial thinking in partnership with multiplier that amplifies the property, one potential problem Catalyze Consulting – a company Total Risk Adjusted AI Use Case Value information historically held in could be difficulty in accessing that enables structured books and articles. the required volume or type of decision making. Use Case 1 Use Case 2 properties or development sites Use Case 3 It’s much easier to type a keyword In collaboration with Catalyze, we to achieve growth. Use Case 4 into a search bar, than it is to have built a Multicriteria Decision Use Case 5 Use Case 6 physically sift through the library So when thinking about that Analysis (MCDA) tool to support Use Case 7 stacks for information. problem in this explore phase, our decision making and to Use Case 8 Use Case 9 we would generate a use case or evaluate our decision intelligence Use Case 10 potential solution to that problem. use cases. Use Case 11 Six force multipliers of Use Case 12 decision intelligence Use Case 13 At Investa, one solution for us, In addition to financial return, Use Case 14 was creating an AI-powered we have criteria that underpin Use Case 15 a Explore Use Case 16 decision intelligence model that the four pillars of Investa’s Use Case 17 When we first talk about data, allows us to find and evaluate business strategy. Use Case 18 insights and AI, it can be tempting Use Case 19 off-market opportunities so that Use Case 20 We also consider impact over to see AI as something that will we can broaden our asset and Use Case 21 solve all of our business problems. time, fit to data, probability of Use Case 22 development pipeline. Use Case 23 success and time to return. This Use Case 24 And while AI can make a massive sophisticated model allows us to Use Case 25 impact on any business, the key to b Evaluate Use Case 26 prioritise which use cases to build Use Case 27 successfully growing an analytics The next phase is to prioritise first and helps us communicate to Use Case 28 and insight capability is to focus and evaluate these use cases stakeholders. It is also essential and prioritise. against the business strategy to talk about the conditions for 0 1000 2000 3000 4000 5000 6000 7000 8000 The first step is to explore which and also against the feasibility of launch (e.g. alignment to business’ Criteria 1 Criteria 2 Criteria 3 Criteria 4 business problems – if solved – successfully being able to execute. strategy, senior sponsors, funding, Criteria 5 Criteria 6 Criteria 6 would help execute the business’ Most AI use cases are evaluated and resources to deliver the desired outcomes). strategy. against a simple 2 x 2 matrix *All criteria and use case details removed for confidentiality reasons Practically, this can look like a of impact vs. feasibility. From workshop, with key stakeholders our experience, we have found across the business, where we that this approach can be

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c Experiment d Engage At Investa, innovation, data and AI is championed by our CEO and CIO, The third phase involves Combining Artificial and Human and the entire executive team is empowering your teams to be Intelligence to validate, learn behind the effort. creative with the data. and engage with the data is an essential part of phase four. “Innovation is a key strategic pillar In the property industry, there isn’t of our strategy. We are prioritising much precedent around data and Humans are vital in the AI- investments in innovation AI – it’s basically pure innovation. feedback loop and by using human projects and ventures, focused Here at Investa, we’re building intelligence, we can help AI models on leveraging new technology and solutions in an agile, creative to learn, but more importantly, we data,” said Peter Menegazzo, Chief manner – not following a well- can build products that deliver Investment Officer, Investa. tested roadmap. on the impact promised to the business. “We have invested heavily in This means that teams have growing an innovation culture to experiment with data. Data At Investa, we have built an AI- within the business, encouraging is the lifeblood of AI and the powered decision intelligence tool our people to look at problems data typically available in the which evaluates and monitors all and opportunities differently, to property industry is often sparse, properties in a given market that be data driven, to question things incomplete, expensive or non- match our investment criteria. and trial different ideas, in order existent. Businesses in these We also include our capital to reach the optimal, customer- types of industries need to transactions team in the AI- centric outcomes.” think differently. feedback loop and collectively This support gives much-needed At Investa, we are partnering with assess the results of the air to the effort of building models data providers to co-create data modelling. and provides the impetus for sets to benefit both parties. We The data then provides guidance stakeholders across the business are building our own structured us to why specific target to engage. data sets from external and public properties are a “yes” or a “no” data and feeding those into our Without the engagement of the and tell us where to look next models. Often we find a signal business and senior leadership, “ Imagine, in just a few short years, we – be that new asset classes, in data that initially appears to the risk is that AI and data gets humans will be working hand in hand new geographical markets or have no value. It is about finding siloed and has less impact. something else. with machines. Organisational charts creative solutions and continually will be reinvented. We will leverage following the thread. We are While AI is exceptional at our strengths as people – creativity, always data hunting. completing large amounts of the “janitorial” tasks of working “We are delighted that our connection and leadership. The machines through and cleaning the data, platform has been able to deliver will do the heavy lifting with complexity humans excel at the nuances and such impressive results to creativity of the deal negotiation – and will alert us to things that we humans Investa, who have shown great together, the impact is realised. can’t see. The future looks bright in what foresight to develop a strong, To set up AI for success in an will be a perfect partnership, driving data-driven culture internally. AI-driven decision intelligence organisation, it really is imperative ultimate business performance.” is empowering Investa with to have the support of the C-suite strong and actionable insights and the senior leadership team. Joanna Marsh, General Manager, for sustainable growth and Innovation & Advanced Analytics, Investa measurable impact,” Amir Haramaty, Chief Commercial Officer, SparkBeyond.

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“The Innovation Institute is an industry leading initiative that provides participants with the opportunity to gain unique and tailored insights that align with the changing nature of their roles and allows Investa to deliver superior client outcomes, while achieving the organisation’s strategic goals.” Lorna Nolan, National Marketing & Communications Manager, Investa

e Execute f Expand “We have flexed our Once a new innovation product Once a use case has been has been placed into the business completed, it can be tempting creative muscles (into the wild), it is vital to support to move on to the next business to come up with people to leverage the tools and problem, however it’s vital to engage. This is where we realise manage the ongoing optimisation a highly agile the ROI of the use case and where and use of the models in the Innovation Institute the business benefits. business in order to yield maximum value. At Investa, we are very conscious course for 2020/21, of supporting our people in this At Investa, we focus on continuous that caters to all journey. improvement of our models, incorporating new data sets, levels. Ensuring An example of how we embed sharpening the tools and making knowledge and learnings across that Investa’s sure our people are still getting the business is the creation of value. From there, we leverage our company-wide skills training employees will be that work into the next set of program, the Innovation Institute. use cases, so we are continually at the forefront Now in its second year, the initial evolving our tools. when it comes Innovation Institute program “Our internal and external focused on educating participants investment in innovation projects to application of on the Thinking innovation and ventures is focused on process. This year’s curriculum core concepts and leveraging new technology and has moved to a focus on Data data to do our core business adoption of new Literacy. As part of this, we are better, improve the operation educating our people in all things technologies.” and performance of our buildings data, insights and AI/ML. and expand our capability to grow Anna Bland, Innovation Part 3: in areas that are aligned with Program Manager, Investa the strategic direction of the business,” said Emily Challenges Lee-Waldao, Group Executive, Brand & Innovation, Investa. and risks

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“It’s the creativity of combining the business requirements, with the industry knowledge and technical ability that sets you up to deliver the ‘aha’ moment at the end of the project. It all begins with the data.” Billy O’Neill, Digital Manager, Data & Insights

What are the challenges issues, integrating AI into the are only as valuable as the with AI? company’s roles and functions business outcomes they drive,” and data issues. said Joanna Marsh, General a Demonstrating a clear Manager, Innovation & Advanced In a 2018 McKinsey Global Survey return on investment Analytics, Investa. of AI, most respondents whose One of the main challenges of AI is companies have deployed AI in a not primarily technical, but rather b specific function report achieving Scarcity of technical skills how to accurately predict and moderate or significant value from Given that AI is still an emerging then achieve ROI from the that use, but only 21 percent of technology, there are a limited investment in AI. respondents report embedding amount of people who have the According to a 2019 MIT Sloan AI into multiple business units required technical and business Management Review and Boston or functions. acumen to work with it. Consulting Group report, seven out At Investa, we have recognised this Many small to medium sized of 10 companies surveyed report challenge and have addressed it businesses don’t have the budgets minimal or no impact from AI so through effective prioritisation of available to hire in-house Data far. Among the 90% of companies our use cases, clearly identifying Scientists or other specialist roles that have made some investment baseline statistics such as required to work on the AI. in AI, fewer than 2 out of 5 report time spent and cost, so we can business gains from AI in the At Investa, we believe strongly effectively estimate the ROI of past three years. This number in the power of partnerships each use case. improves to 3 out of 5 when we to access world-class talent. include companies that have We then measure that ROI as we Through our partnership with SparkBeyond, we have created made significant investments in go and again once the product has business problems through AI and General Manager, Innovation & the Investa team to spend more a team of experts with niche AI. Even so, this means 40% of been in use within the business. machine learning, allows us to Advanced Analytics, Investa. time focusing on the findings to skills such as natural language organisations making significant This is an ongoing process and make better decisions. create innovative, new ways to processing, that we can apply to “Utilising AI platforms like investments in AI do not report we keep this front of mind as solve key business problems,” our use cases. As we move into the future, we SparkBeyond enables small business gains from AI. a standing agenda item at our said Will Cosby, Senior Data will be able to leverage these teams of industry specialists to quarterly Innovation Investment “In a time of great transformation, Scientist, SparkBeyond. According to a 2018 report by insights to uncover opportunities outsource the labour-intensive Committee meetings. many companies are struggling to Deloitte, State of Enterprise AI - that are not yet articulated clearly tasks of data processing, innovate in a way that drives real the top three challenges “The final objective is always to or adequately serviced in our formatting and analysis, to the AL/ business impact. Being able to see with AI were implementation link back to business strategy. industry,” said Joanna Marsh, ML platform provider. This enables Advanced analytics and insights patterns, derive insights and solve

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c Data quality and quantity importantly, analysing different data assets to understand its Data is the lifeblood of AI. The value. This is where thinking quality of any platform, algorithm creatively about the problem or insights relies on the data and its relationship to what the that it’s using, and AI needs a data is telling us is imperative in considerable amount of data to delivering a unique solution to learn and identify meaningful drive competitive advantage. patterns. The better the data, the better Developing a high volume, varied the applications of AI and and incongruous foundation machine learning. of data that can be blended and ingested into our AI/ML In the property industry, we are modelling is the secret sauce. In working in a data-constrained true innovation style, the data environment. We have access asset development never ends, to niche data sets in each as each use case presents a set market, but these data sets of challenges that can often be vary enormously between solved with better information.” different markets. Billy O’Neill, Digital Manager, For example, we have Data & Insights. partnered with Empirical CRE, a data provider that entered the d Integration Australian market two years ago. Fully integrating AI into your Empirical have built a detailed organisation, is a lot more data set for office and industrial complicated than adding a plug-in properties across different to your website or an extension to geographical markets. your browser. The entire interface This data set is key to many of our and workflow have to be set up to use cases because it includes reflect your unique business goals. data about tenants, rents, lease Data infrastructure, data expiry dates and building profiles storage, data labelling, testing – as well as sales history. This and a feedback loop also need level of data is extremely useful, to be considered as part of the but in other markets there are integration. challenges in obtaining data with Part 4: the same level of granularity. As a To do this, a strong partnership result, we are having to create our with your Chief Information Officer own data sets through a variety of (CIO) is vital. At Investa, we have Applications mining techniques. tightly aligned our information technology team and our data, “The property industry is coming innovation and analytics team, up the data maturity curve fast, so that we can innovate and and use however the majority of time is really create value. still spent collecting, cleaning and cases

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What are the applications of AI?

a Real estate Based on our findings, we believe that the real estate industry is poised for an industry-wide data and AI transformation. The property industry has lagged other industries in investing and adopting AI but is starting to recognise the value of these capabilities. AI-generated proptech startups will continue to grow over the coming years, as startups leverage AI to improve an industry starving for innovation.

Acuisitions iestents

apita auations Inestors AI in the Property aue hain “Investa is at a pivotal point in its journey. We’re looking at all ustoers ustoer Tenants erice core business activities through an innovation and technology lens.” uidin perations Emily Lee-Waldao, Group Executive, Brand & Innovation, Investa

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“Elevating the way tenants are able to interact with our As the commercial property AI without needing to employ What is the future of AI? market transforms, commercial technical developers and data There’s no doubt that AI is property owners and managers scientists upfront. buildings and with our teams, enables us to deliver a highly impacting the future of virtually that can use and leverage building A final benefit of AIaaS is the every industry. user-centred experience. This has always been central to data and mine it for insights with ability to scale. As companies AI will have a distinct competitive AI has also been a primary driver become more comfortable with AI, the way we think about integrating technology into our advantage. for emerging technologies like they can expand the use case of AI big data, robotics and the Internet buildings and services.” throughout the organisation. They Artificial Intelligence as a of Things (IoT). With tech giants can also see what works before Sally Franklin, Group Executive Real Estate Services & Business Operations, Investa Service (AIaaS) like Google, Amazon, Apple and having to commit to a particular Microsoft, universities and the Following in the footsteps of AI solution. military, all spending billions of b obtained from siloed systems, timeline view of the building. Infrastructure as a Service (IaaS), Commercial real estate Well-known types of AIaaS dollars on AI, there is no downturn but it can be expensive and These features offer incredible Software as a Service (SaaS) and Commercial real estate is an ideal include: in sight. complicated. Another option is new management capabilities, Platform as a Service (PaaS), AI as candidate for data, insights and to focus on high-value data sets specifically across commercial a Service (AIaaS) is the third party – Bots and digital assistance However, there is debate and even AI – primarily due to changing and prioritise those that will real estate, and outsourcing of AI. concern around exactly how AI will demand for space from tenants. – Cognitive computing APIs deliver impact. insurance industries.” AI cloud offerings including impact life as we know it. For example, the co-working trend – Machine learning frameworks “Sixty Martin Place is a project Investa has also developed a SparkBeyond, Amazon Machine The uncertainty about the or working from home through that pushed traditional boundaries proprietary tenant engagement Learning, Microsoft Cognitive – Fully-managed machine future of AI was compounded by COVID-19 will shape the way that and challenged the industry by app called, Insite, a technology Services and Google Cloud learning services billionaire entrepreneur Elon Musk people want to work in the future. integrating technology into the solution that has been invaluable Machine Learning as well as start- when he said, “AI is a fundamental We can evaluate the data as the Unlike other technology, AIaaS is heart of the development brief, so for connecting building occupants ups like Dataiku, BigML, Forecast risk to the existence of human market demand shifts and be able not as easy as plug and play. it was an easy decision for Investa with the latest building news, This, can help organisations civilisation.” to respond to that shift. The success of AIaaS lies in a to participate in this endeavour. services and events. to understand what might be strong data capability internally, Brad Smith, President of Microsoft For example, Investa has created possible with their data. Harnessing the combined power The advent of the COVID-19 as well as strong leadership to said, “Information technology a product called Fast Lease that of digital twins and augmented pandemic saw more people than AI as a Service allows individuals champion the program. raises issues that go to the heart allows tenants to sign a simplified, reality allows us to provide a ever logging onto the app. and companies to experiment of fundamental human rights short-term lease and quickly move It also takes significant time and previously unexplored user with AI for at a fraction of the cost. protections, like privacy and into the space. “We have really seen a dynamic resource investment to really experience through an interactive Before AIaaS, companies had freedom of expression. These shift in the behaviour of our understand and use the software. From a data perspective, 3D model of Sixty Martin Place. to budget for not only the large issues heighten responsibility users. We received amazingly Those companies that can build commercial buildings vary widely This ensures owners, tenants and initial investment but also the for tech companies that create positive feedback from our this capability have a strong in the amount of accessible data all users who interface with the ongoing upkeep of physical and these products. In our view, Digital Wellbeing programs and competitive advantage in the that is available. building can enjoy a superior level digital equipment. AIaaS allows they also call for thoughtful competitions. property industry. We will continue companies to harness the power Investa’s newer buildings of service and interaction with to see companies outperform that government regulation and for Insite has really bridged the gap of AI at significantly lower costs. (e.g. Sixty Martin Place), has state- their environment,” said Shen Chiu invest in this area. the development of norms around between the workplace and the of-the-art sensors and technology National Development Director, Another benefit of AIaaS is acceptable uses.” home. Now, we can still connect Through Investa’s partnership that allow us real-time access to Investa and Project Director for the usability. Unlike traditional AI with our occupants on a day-to- with SparkBeyond – an AI/ML building data. Sixty Martin Place development. options, which can be open-source day basis, we can re-create the software platform – we are “Utilising the open data available and complex, AIaaS provides We can use this data in our AI workplace virtually and keep achieving strong results, thanks to in the building, a range of features plug and play type usability. This models to develop insights into that sense of connectivity our strong internal resources and are currently operational within allows companies to start utilising optimal building operations and alive,” said Sally Franklin, Group leadership support. the AR environment, including preventive maintenance. Executive Real Estate Services & a BIM Overlay, IoT data, live Business Operations, Investa. Older buildings can be retrofitted temperature sensors and a with sensors and data can be

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The future of AI can be b Autonomous everything consolidated into four Autonomous robots, cars, drones Conclusion essential parts: and systems are some of the most visible and discussed elements a The AI-enhanced organisation of AI. Autonomous systems can AI will continue to provide influence retail, health care, organisations with tremendous journalism and even infrastructure. advances in productivity, At Investa, we are currently It is no longer possible to continue efficiency, insight, processes investigating a range of potential with the status quo. Companies that and value. business applications for Drones, leverage data, insights, AI, ML and which is an exciting opportunity. At Investa, building strong automation technologies, will have an capability in the use of AI “The market and usage of drones technologies is our current s growing quickly, due to the cost increasingly large competitive pathway and goal. We believe the efficiencies they can provide. advantage moving forward. skills needed to excel in this area We’re keenly exploring how we can be learnt and we are applying could use drones to add value At Investa, we believe that this the technology and resulting data at Investa, notably in building technology is the future team member visualisation dashboards across operations and optimising our a range of business problems, space utilisation,” said Anna that will handle the complexity of large functions and roles. Bland, Innovation Project Manager, data sets – allowing us humans to focus Investa. Organisations that fail to adopt on what we do best, being creative and AI and innovate will struggle to c thriving in an environment of ambiguity. survive and compete in the future. Pervasive knowledge As AI pushes up the Data- Cognilytica an AI, Research The future is a partnership between Information-Knowledge-Wisdom Advisory and education firm (DIKW) Pyramid, society will humans and machines, where we believes that AI will enable or demand more from governments, will be able to deliver better service, augment (rather than replace) companies and each other. People work done by humans. better places and better outcomes, as will expect things to be available Another predicted future AI trend instantly. Information will need we leverage the power of data, AI and will be mass-customisation and to be accurate and complete and advanced analytics. personalisation at scale. AI will everyone will be connected all of allow companies to deliver a the time. much more personalised, unique experience for customers. This d Enhancing the human will enhance marketing, sales experience and customer service functions. Using augmented intelligence, Finally, AI will allow companies to AI can enhance and further the be “always-on” and move beyond creative capabilities of humanity. standard 9-5 opening hours. AI also can enable humans to communicate with another person in any language and be easily understood – and even address local customs and etiquette.

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This document has been prepared by Investa for informational and educational purposes only. While reasonable care has been taken in the preparation of this document, Investa makes no representation or warranty (express or implied) in respect of this document, including as to the accuracy or completeness of any statement in it including, without limitation, any forecasts. In preparing this document, Investa may use and rely upon information from sources generally regarded as authoritative and reputable, but the information obtained from these sources may not have been independently verified by Investa. The information contained in this document is also based on present circumstances, market conditions and beliefs, which may change. It is not intended to provide, and should not be relied upon for investment, financial, accounting or legal advice. To the maximum extent permitted by law, Investa accepts no responsibility or liability whatsoever for any expense, loss or damage arising out of or in any way connected with the use of all or part of this document, nor will Investa bear any responsibility or liability as to the fairness, accuracy, adequacy, completeness or correctness of the information in this document or provided in connection with it.