The Impact of Artificial Intelligence on the Facilities Management Industry

Transcription

1 The Impact of Artificial Intelligence on the Facilities Management Industry Chris Hoar, Katie King and Brian Atkin 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.

3 Background

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.

5 Like this?

6 Or like this?

7 Or even this?

8 From this to this

9 Role models?

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 worldleading 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 in manufacturing 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.

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15 AI in the FM industry

16 Current examples

17 Floor cleaners

18 Cleaning and waste disposal

19 Service delivery 1

20 Service delivery 2

21 Catering

22 Actroids at your service

23 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.

24 Results of a recent survey

25 Impact of AI 12% 4% Impact of AI (5 years from now) 38% Negligible Some 46% Significant Transformational

26 50% 15% 35% Impact of AI (10 years from now) Some Significant Transformational

27 4% Nature of impact 5 years from now 27% 69% More negative than positive More positive than negative All positive or mostly positive

28 4% AI is an opportunity to increase profit margins 12% Disagree 65% 19% Neither disagree nor agree Agree Totally agree

29 Responsibility for monitoring and acting upon developments in AI 23% 12% 42% Top management (e.g. CEO, CIO or CTO) 23% Senior manager - business development

30 AI-supported workplace FutureOffice

31 Service Area Individual Service AI Solution Cleaning Floors Horizontal surfaces Windows internal Windows external Autonomous guided vehicles (AGVs), supplemented by unmanned aerial vehicles (drones) for external window cleaning Toilets/showers Waste Disposal Food stuffs Autonomous guided vehicles Paper (AGVs) Other recyclable Non-recyclable Security Intrusion detection Remote diagnosis Patrolling/detection Guard Smart apps, UHD and thermal imaging cameras, drones, autonomous guided vehicles (AGVs) and actroids M&E Services Maintenance Measurement Optimization Fault diagnosis Parts replacement Smart apps, thermal imaging cameras, actroids, autonomous guided vehicles (AGVs) and 3D printing of parts Catering Food preparation Actroids/robots and autonomous Pre-serve guided vehicles (AGVs) Serving/dispensing Clearing/washing Design Change Design to take account of mobility for AGVs and the need to enclose cubicles Waste collection points and services for transfer to disposal site Increased use of sensors, cameras and high-speed communications Easier access to fittings and equipment for spare parts replacement Dedicated spaces for food pre-serve and eating CAPEX Impact Low Low-medium Medium Medium Medium Operational Change Occupants need to adopt the discipline of a tidy office Create centralised collection and disposal points Awareness training for personnel Greater need for maintenance management, especially PPM Occupants encouraged to use centralized catering OPEX Impact Significant cost saving Moderate cost saving Significant cost saving and reduction of risks for personnel Moderate cost saving Cost saving Reception & Helpdesk Front of house Actroids and smart apps None Low None Significant cost Back office saving Condition Survey Façade and roof Unmanned aerial vehicles Structural frame (drones) with thermal imaging cameras None Low None Minor cost saving and reduction of risks for inspection personnel Logistical Support Deliveries Autonomous guided vehicles Porterage (AGVs) and actroids None Low None Significant cost saving and reduction of risks for personnel

32 Concluding remarks

33 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?

34 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 noncore 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?

35 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?

36 Q&A

37 Thank you! Visit us at: #AIinFM Join us on LinkedIn