A FUTURE THAT WORKS: the impact of automation in Denmark

A FUTURE THAT WORKS: the impact of automation in Denmark Bjarne Corydon Director I McKinsey Center for Government JUNE 8 017 1

Examples of automation technologies Artificial intelligence Robotics Autonomous vehicles Smart workflows Technologies such as machine learning that exhibit intelligence Design, construction, and operation of robots Vehicles operating without a human driver Integration of tasks performed by humans and machines

Robots are excelling at some activities - but not all Robots are excelling at... Robots are challenged by... Recognizing known patterns Optimization and planning Information retrieval Social and emotional capabilities Generating novel patterns Creativity and critical thinking

Evaluating automation potential at task level Danish workforce is broken 1 down into occupations... Occupations ~400 in total 1 Retail sales persons Food and beverage service workers... which each contain a number of tasks... >000 tasks across occupations Greet customers Answer questions about products...which each require a set of technical capabilities Technical capability assessment, 18 factors Sensory perception Natural language understanding 4 Building backwards, each occupation has a fraction of work hours that can be automated Teachers... Clean and maintain work areas... Social and emotional sensing 4 Fishermen and hunters Process sales and transactions Fine motor skills/dexterity Registry data on ~.7m Danish employees 4

Automation will happen no matter what! questions becomes pivotal 1 How will automation impact the Danish society? How will automation impact the Danish workforce across occupations, sectors, and wage levels? What this report brings: Fact based and detailed activity level perspective for Danish automation potential Key considerations for how Denmark should address opportunities and challenges over the coming years How can Denmark reap the full benefits of automation while overcoming societal challenges? 5

1 How will automation impact the Danish society? How will automation impact the Danish workforce across occupations, sectors, and wage levels? How can Denmark reap the full benefits of automation while overcoming societal challenges? 6

Automation is first and foremost a major opportunity Opportunities Economic gains for society - boost productivity, create new industries, companies, and jobs Free up human resources New solutions to societal problems Key findings Re-deploy up to 40% of work hours in high value add activities Raise GDP growth by 0.8 PP 1.4 PP All occupations will be affected Workforce transition Challenges Risk of growing inequality 7

40 percent of Danish working hours can be automated 100% 40% 60% Total working hours Automatable working hours Non-automatable working hours 8

Danish workforce transitions in recent times Sectors Business and financial services, ICT and Pharma Manufacturing and other industry Increase from 1970-015, FTEs (% increase) -00,000 (-55%) 00,000 (150%) Public 400,000 (90%) Trade, Transportation, hotel and restaurants 50,000 (6%) Construction -100,000 (-5%) Primary -00,000 (-80%) Total 150,000 9

Seven granular insights 1 4 5 6 7 40 percent of working hours in Denmark are automatable based on current technologies Occupations with a higher share of predictable job tasks are more prone to automation Less educated workers face higher degree of automation Middle-income jobs are more exposed to automation than both low- and highincome jobs Significant differences in automation potential across sectors Automation impacts the entire country, both rural and urban areas Danish potential slightly lower than the global average 11

Automation potential across salary levels Degree of automation, % of work hours Automatable 4% 5% % 8% % 40% Non-automatable 57% 47% 67% 7% 77% 60% Annual salary levels, DKK thousands < 75 75-50 50-400 400-600 >600 Total 1 We define automation potential by the work activities that can be automated by adapting currently demonstrated technology Calculated as sumproduct of automatable potential and share of employees 1

Automation potential across sectors Selected sectors Industry Degree of automation, % of work hours Non-automatable 7% Automatable 6% Trade 44% 56% Transportation 46% 54% Construction 46% 54% Business services 66% 4% Public 7% 7% Average 60% 40% 1 We define automation potential by the work activities that can be automated by adapting currently demonstrated technology Calculated as sumproduct of automatable potential and share of employees. Also include other sectors (e.g., raw materials) 1

10 Policy considerations Objective Considerations 1 Increase opportunities for reskilling and lifelong learning A Promote a smooth workforce transition Reorient educational systems toward future essential skills Ensure continuous support for those in transition 4 Support early technology development and deployment B Support the private sector and lead by example in the public sector 5 6 Rethink needlessly obstructive regulation, while protecting societal concerns Lead by example in the public sector 7 Ensure a level playing field for entrants and incumbent firms C Ensure gains from automation are broadly distributed 8 9 10 Reconfigure tax system to prepare for shifts in future value creation Strengthen core educational institutions to ensure relative skill equality Ensure the viability of the redistribution system and the social contract 15

Danish perspective International perspective 16