The 5 Areas of Focus for AI The 17 Target Areas for AI in Real Estate Target Applications within those 17 Areas Competitive Advantage through AI AI at Large; Crossing the Chasm Action Steps

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2. Artificial Intelligence in Real Estate
Building a Better Built Environment

3. AI in Real Estate
Contents
1. The 5 Areas of Focus for AI
2. The 17 Target Areas for AI in Real Estate
3. Target Applications within those 17 Areas
4. Competitive Advantage through AI
5. AI at Large; Crossing the Chasm
6. Action Steps

4. AI in Real Estate
Since inception of ‘AI’ at Dartmouth College in 1956 there have been 5 areas of
focus:
1. Knowledge about the World
2. Reasoning: Deductive, Inductive and Abductive
3. Planning: setting goals and how to achieve them
4. Communication: Understanding written and spoken language
5. Perception: Understanding imagery, sounds and other sensory inputs

5. AI in Real Estate
These five areas of focus are generic across the business world
● Knowledge about the World
○ Information Synthesis, Consumer/Customer Targeting, Marketing/Advertising
● Reasoning: Deductive, Inductive and Abductive
○ Asset Management, Compliance, Document Analysis, Application Processing
● Planning: setting goals and how to achieve them
○ Logistics, Predictive Maintenance, Demand Forecasting

6. AI in Real Estate
These five areas of focus are generic across the business world
● Communication: Understanding written and spoken language
○ Voice Control, Intelligent Agents, Customer Support, Client Service
● Perception: Understanding imagery, sounds and other sensory inputs
○ Authentication/Security, Spatial awareness

7. AI in Real Estate
Leading to 17 Target Areas within Real
Estate
❖ Investment strategy
❖ Portfolio construction
❖ Risk management
❖ Client service
❖ Asset Monitoring
❖ Discovery & due diligence
❖ Compliance
❖ Predictive maintenance
❖ Asset performance
❖ Customer segmentation
❖ Content personalisation
❖ Price optimisation
❖ Churn prediction
❖ Infrastructure optimisation
❖ Demand optimisation
❖ Security
❖ Customer experience

8. AI in Real Estate
Target Applications within Real Estate
❖ Investment strategy
➢ Synthesising research and data
➢ Incorporating disparate data sources
➢ Processing and analysing unstructured data (emails, voice, imagery)
➢ Powerful pattern recognition
➢ More flexibility and insight than rules based systems

9. AI in Real Estate
Target Applications within Real Estate
❖ Portfolio Construction
➢ Analyse client goals
➢ Personalised
➢ Optimised
➢ ‘Robo-advisors’
➢ Low cost
➢ High speed

10. AI in Real Estate
Target Applications within Real Estate
❖ Risk Management
➢ Analysis of broad data sets
➢ Process unstructured data
➢ Apply large cognitive processing
➢ ‘Read’ widely via natural language processing (NLP)
➢ Algorithms using deep learning are effective for image analysis
➢ Bayesian (probability-based) AI is useful for predicting settlement costs
➢ Deep Learning allows for highly granular, confident pattern matching

11. AI in Real Estate
This is just the start of a 40 slide presentation, covering the
future of AI in the real estate industry.
Please get in touch if you are interested in an in person walk
through of possibly the most important technology of the
next 10 years.
Visit us at www.propai.co.uk

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