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The Impact of Artificial
Intelligence on the Built
Environment
Chris Hoar
AIinFM
www.aiinfm.com
@AIinFM
#AIinFM
Join us on LinkedIn
Scope of this presentation
• Background:
• Existing challenges facing the facilities management industry
• Artificial intelligence (AI) – a global and socio-economic perspective.
• AI in the FM industry:
• Current examples
• Results of a recent survey.
• Impact on the FM industry:
• The future for service providers
• Concluding remarks.
Background
Existing challenges
• The image of the FM industry – one of low esteem and a mismatch
between self-perception and that of wider industry and the public.
• No ambassadors to grab the headlines or create role models.
• Few trust-based relationships.
• Intelligent client function (ICF) not well developed.
• Difficulty in attracting and retaining talent – limited career pathways.
• Low barriers to entry and low profit margins.
• Dependency on cash flow by service providers – few fixed assets.
Like this?
Or like this?
Or even…
…this?
From this…
to this…
Role
models?
And now another challenge…
• Artificial intelligence (AI) has already made inroads into all
sectors even if we fail to recognise it (e.g. Siri and Cortana).
• A definition:
A field of computer science dedicated to the study of
computer software making intelligent decisions,
reasoning and problem solving.
What is Artificial Intelligence?
Human Intelligence
• Intuition, common sense,
judgement, creativity, beliefs
etc.
• The ability to demonstrate
intelligence by effective
communication
• Plausible reasoning.
Artificial Intelligence
• Ability to simulate human
behaviour and cognitive
processes.
• Capture and preserve human
expertise.
• Fast response – the ability to
comprehend large amounts of
data quickly.
Recent media headlines
• “Robots set to replace workforce as AI to ‘eliminate’ all
human work by 2040” – robots and artificial intelligence will have
almost entirely replaced human workers within just 20 years, a world-
leading expert on the subject has claimed.
• According to Gartner, “Machine learning is a top strategic trend for
2016” and “autonomous agents and things will continue to be a huge
trend”.
Socio-political impacts of AI
• Employment/unemployment – large-scale lay-offs from more
advanced automation and robots.
• Health, safety and security – increased protection from harm for
workers, pedestrians and vehicle drivers.
• Healthcare – more and more routine surgical procedures performed
by robots, reducing waiting lists.
• Education – reduced need for university teachers and administrators.
• Transportation – more driverless cars, trucks, buses and trains.
• Crime and punishment/rehabilitation – greater security and safety.
• Military!?
AI in the FM industry
Current examples
Floor cleaners
Cleaning and
waste disposal
Service delivery
How will the face of FM Change?
• Security
How will the face of FM Change?
• M&E
How will the face of FM Change?
• Fabric Maintenance
How will the face of FM Change?
• Catering
Catering
How will the face of FM Change?
• Catering
How will the face of FM Change?
• Catering
How will the face of FM Change?
• Reception and Helpdesk
How will the face of FM Change?
• Reception and Helpdesk
Actroids
at your
service
Are we comfortable?
Software and smart apps
• Smart apps are capable of searching and matching information, problems
and solutions and can explain their reasoning.
• They can learn and, in time, out-perform a human because they have
acquired more knowledge.
• Many repetitive managerial decisions will be replaced by smart apps
within a few years.
• Example apps include deciding on the optimal strategy for managing
facilities, maintenance regimes and manpower deployment.
• Users will put their questions in plain language and receive a response in
a similar manner.
Results of a recent survey
Impact of AI
4%
38%
46%
12%
Impact of AI
(5 years from now)
Negligible
Some
Significant
Transformational
15%
35%
50%
Impact of AI
(10 years from now)
Some
Significant
Transformational
4%
69%
27%
Nature of impact
5 years from now
More negative
than positive
More positive
than negative
All positive or
mostly positive
12%
19%
65%
4%
AI is an opportunity
to increase profit margins
Disagree
Neither disagree
nor agree
Agree
Totally agree
42%
23%
23%
12%
Responsibility for monitoring and
acting upon developments in AI
Top management (e.g.
CEO, CIO or CTO)
Senior manager - business
development
AI-supported workplace –
FutureOffice
Service
Area
Individual
Service
AI
Solution
Design
Change
CAPEX Impact Operational
Change
OPEX
Impact
Cleaning Floors Autonomous guided vehicles
(AGVs), supplemented by
unmanned aerial vehicles (drones)
for external window cleaning
Design to take account of
mobility for AGVs and the
need to enclose cubicles
Low Occupants need to adopt
the discipline of a tidy
office
Significant cost
savingHorizontal surfaces
Windows – internal
Windows – external
Toilets/showers
Waste Disposal Food stuffs Autonomous guided vehicles
(AGVs)
Waste collection points and
services for transfer to
disposal site
Low-medium Create centralised
collection and disposal
points
Moderate cost
savingPaper
Other recyclable
Non-recyclable
Security Intrusion detection Smart apps, UHD and thermal
imaging cameras, drones,
autonomous guided vehicles
(AGVs) and actroids
Increased use of sensors,
cameras and high-speed
communications
Medium Awareness training for
personnel
Significant cost
saving and
reduction of risks
for personnel
Remote diagnosis
Patrolling/detection
Guard
M&E Services
Maintenance
Measurement Smart apps, thermal imaging
cameras, actroids, autonomous
guided vehicles (AGVs) and 3D
printing of parts
Easier access to fittings and
equipment for spare parts
replacement
Medium Greater need for
maintenance
management, especially
PPM
Moderate cost
savingOptimization
Fault diagnosis
Parts replacement
Catering Food preparation Actroids/robots and autonomous
guided vehicles (AGVs)
Dedicated spaces for food
pre-serve and eating
Medium Occupants encouraged to
use centralized catering
Cost saving
Pre-serve
Serving/dispensing
Clearing/washing
Reception & Helpdesk Front of house Actroids and smart apps None Low None Significant cost
savingBack office
Condition Survey Façade and roof Unmanned aerial vehicles
(drones) with thermal imaging
cameras
None Low None Minor cost saving
and reduction of
risks for inspection
personnel
Structural frame
Logistical Support Deliveries Autonomous guided vehicles
(AGVs) and actroids
None Low None Significant cost
saving and
reduction of risks
for personnel
Porterage
Concluding remarks
Timescales
Stephen Hawking’s view
What does this mean for service providers?
• Labour-intensive services are among the easy targets for AI, because
they are based on operations that can be replaced by machines with
sufficient intelligence for the job in hand.
• Cleaners and maintenance engineers are unlikely to disappear, but
they will not be required to the same extent as now.
• Where is the moral dilemma for owners/clients deciding to move
from a labour-intensive to a machine-intensive workforce that never
takes holidays or sick leave?
Some questions for owners/clients
• What is the extent of core business processes currently supported by
some form of AI-based solution?
• To what extent is any change in the boundary between core and non-
core business likely as a result of AI?
• What is the extent of work or services currently supporting the core
business that utilise some form of AI?
• To what extent could AI-based solutions be introduced in substitution
of, or complementary to, existing labour-intensive service delivery?
Some thoughts for this audience
• What is going to be left of the FM industry if what we have heard
comes true?
• Are there some specific actions that your organisation could take to
capitalise on the opportunities (or threats) of AI?
• Are there some actions that the Government should take in terms of
a policy on the use of robots, especially actroids, in the workplace?
Thank you!
Visit us at: www.aiinfm.com
@AIinFM
#AIinFM
Join us on LinkedIn

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The Impact of Artificial Intelligence on the Built Environment

  • 1. The Impact of Artificial Intelligence on the Built Environment Chris Hoar AIinFM www.aiinfm.com @AIinFM #AIinFM Join us on LinkedIn
  • 2. Scope of this presentation • Background: • Existing challenges facing the facilities management industry • Artificial intelligence (AI) – a global and socio-economic perspective. • AI in the FM industry: • Current examples • Results of a recent survey. • Impact on the FM industry: • The future for service providers • Concluding remarks.
  • 4. Existing challenges • The image of the FM industry – one of low esteem and a mismatch between self-perception and that of wider industry and the public. • No ambassadors to grab the headlines or create role models. • Few trust-based relationships. • Intelligent client function (ICF) not well developed. • Difficulty in attracting and retaining talent – limited career pathways. • Low barriers to entry and low profit margins. • Dependency on cash flow by service providers – few fixed assets.
  • 10. And now another challenge… • Artificial intelligence (AI) has already made inroads into all sectors even if we fail to recognise it (e.g. Siri and Cortana). • A definition: A field of computer science dedicated to the study of computer software making intelligent decisions, reasoning and problem solving.
  • 11. What is Artificial Intelligence? Human Intelligence • Intuition, common sense, judgement, creativity, beliefs etc. • The ability to demonstrate intelligence by effective communication • Plausible reasoning. Artificial Intelligence • Ability to simulate human behaviour and cognitive processes. • Capture and preserve human expertise. • Fast response – the ability to comprehend large amounts of data quickly.
  • 12. Recent media headlines • “Robots set to replace workforce as AI to ‘eliminate’ all human work by 2040” – robots and artificial intelligence will have almost entirely replaced human workers within just 20 years, a world- leading expert on the subject has claimed. • According to Gartner, “Machine learning is a top strategic trend for 2016” and “autonomous agents and things will continue to be a huge trend”.
  • 13. Socio-political impacts of AI • Employment/unemployment – large-scale lay-offs from more advanced automation and robots. • Health, safety and security – increased protection from harm for workers, pedestrians and vehicle drivers. • Healthcare – more and more routine surgical procedures performed by robots, reducing waiting lists. • Education – reduced need for university teachers and administrators. • Transportation – more driverless cars, trucks, buses and trains. • Crime and punishment/rehabilitation – greater security and safety. • Military!?
  • 14.
  • 15. AI in the FM industry
  • 20. How will the face of FM Change? • Security
  • 21. How will the face of FM Change? • M&E
  • 22. How will the face of FM Change? • Fabric Maintenance
  • 23. How will the face of FM Change? • Catering
  • 25. How will the face of FM Change? • Catering
  • 26. How will the face of FM Change? • Catering
  • 27. How will the face of FM Change? • Reception and Helpdesk
  • 28. How will the face of FM Change? • Reception and Helpdesk
  • 31.
  • 32. Software and smart apps • Smart apps are capable of searching and matching information, problems and solutions and can explain their reasoning. • They can learn and, in time, out-perform a human because they have acquired more knowledge. • Many repetitive managerial decisions will be replaced by smart apps within a few years. • Example apps include deciding on the optimal strategy for managing facilities, maintenance regimes and manpower deployment. • Users will put their questions in plain language and receive a response in a similar manner.
  • 33. Results of a recent survey
  • 34. Impact of AI 4% 38% 46% 12% Impact of AI (5 years from now) Negligible Some Significant Transformational
  • 35. 15% 35% 50% Impact of AI (10 years from now) Some Significant Transformational
  • 36. 4% 69% 27% Nature of impact 5 years from now More negative than positive More positive than negative All positive or mostly positive
  • 37. 12% 19% 65% 4% AI is an opportunity to increase profit margins Disagree Neither disagree nor agree Agree Totally agree
  • 38. 42% 23% 23% 12% Responsibility for monitoring and acting upon developments in AI Top management (e.g. CEO, CIO or CTO) Senior manager - business development
  • 40. Service Area Individual Service AI Solution Design Change CAPEX Impact Operational Change OPEX Impact Cleaning Floors Autonomous guided vehicles (AGVs), supplemented by unmanned aerial vehicles (drones) for external window cleaning Design to take account of mobility for AGVs and the need to enclose cubicles Low Occupants need to adopt the discipline of a tidy office Significant cost savingHorizontal surfaces Windows – internal Windows – external Toilets/showers Waste Disposal Food stuffs Autonomous guided vehicles (AGVs) Waste collection points and services for transfer to disposal site Low-medium Create centralised collection and disposal points Moderate cost savingPaper Other recyclable Non-recyclable Security Intrusion detection Smart apps, UHD and thermal imaging cameras, drones, autonomous guided vehicles (AGVs) and actroids Increased use of sensors, cameras and high-speed communications Medium Awareness training for personnel Significant cost saving and reduction of risks for personnel Remote diagnosis Patrolling/detection Guard M&E Services Maintenance Measurement Smart apps, thermal imaging cameras, actroids, autonomous guided vehicles (AGVs) and 3D printing of parts Easier access to fittings and equipment for spare parts replacement Medium Greater need for maintenance management, especially PPM Moderate cost savingOptimization Fault diagnosis Parts replacement Catering Food preparation Actroids/robots and autonomous guided vehicles (AGVs) Dedicated spaces for food pre-serve and eating Medium Occupants encouraged to use centralized catering Cost saving Pre-serve Serving/dispensing Clearing/washing Reception & Helpdesk Front of house Actroids and smart apps None Low None Significant cost savingBack office Condition Survey Façade and roof Unmanned aerial vehicles (drones) with thermal imaging cameras None Low None Minor cost saving and reduction of risks for inspection personnel Structural frame Logistical Support Deliveries Autonomous guided vehicles (AGVs) and actroids None Low None Significant cost saving and reduction of risks for personnel Porterage
  • 44. What does this mean for service providers? • Labour-intensive services are among the easy targets for AI, because they are based on operations that can be replaced by machines with sufficient intelligence for the job in hand. • Cleaners and maintenance engineers are unlikely to disappear, but they will not be required to the same extent as now. • Where is the moral dilemma for owners/clients deciding to move from a labour-intensive to a machine-intensive workforce that never takes holidays or sick leave?
  • 45. Some questions for owners/clients • What is the extent of core business processes currently supported by some form of AI-based solution? • To what extent is any change in the boundary between core and non- core business likely as a result of AI? • What is the extent of work or services currently supporting the core business that utilise some form of AI? • To what extent could AI-based solutions be introduced in substitution of, or complementary to, existing labour-intensive service delivery?
  • 46. Some thoughts for this audience • What is going to be left of the FM industry if what we have heard comes true? • Are there some specific actions that your organisation could take to capitalise on the opportunities (or threats) of AI? • Are there some actions that the Government should take in terms of a policy on the use of robots, especially actroids, in the workplace?
  • 47. Thank you! Visit us at: www.aiinfm.com @AIinFM #AIinFM Join us on LinkedIn