n its proposal for the next multi-annual financial framework, the European Commission put forth an idea to create a new Digital Europe program with an overall budget of Euro 9.2 billion to shape and support the digital transformation of Europe’s society and economy. Among the five priorities of the proposal, Euro 2.5 billion over seven years is planned to help spread AI across the economy and society. I read this fact with interest towards the end of this extensively-researched and action-provoking 136-page report authored by Michel Servoz in his former capacity as Senior Policy Advisor to the President of the European Commission. The title, “The Future of Work? Work of the Future”! is a fitting lead-in to the report’s in-depth examination of how artificial intelligence, robotics, and automation are transforming jobs and the economy in Europe.
Because the report covered tremendous ground on several interconnected topics influencing the future, it can be curated from many different perspectives and has much to offer business people, educators, thought leadership conveners, and policymakers as well as citizens who wish to better grapple with the technology-driven realities that will shape the future. In my summary, I have chosen to extract the questions whose timely solutions will be particularly relevant to the success of emerging AI companies trying to establish and grow in the region. If I were the CEO of such a company, what should I know about the space in Europe and what should I worry about? What should I leverage quickly? The tone of this report is hopeful and optimistic because it approaches automation outcomes as determinable by choices we make and the actions we take. Embracing educational systems, commercial life, governments, and social partners, the report has numerous illustrations of what can be possible as well as actual case studies. It sparks new ideas and presses the need for new frameworks within which to examine and prepare for the future.
My personal take-aways for emerging companies building and growing their presence in Europe are in the form of several questions they should ask themselves periodically- How does your offering increase productivity and lower costs? What is the pulse of the market (current) and what are the trends (future)? Do you have a community which will use, boost, and scale your offering? Who else can your offering serve? Ok, who else? What capabilities are you enabling for your customers’ customers? What have you learned from your dialog with prospects? How does your offering support data privacy, security and pull-technologies? Do you have anything which can enable smaller customers to benefit from powerful algorithms, benefit from insights drawn across public-private data pools? Are you reducing mistake-prone, boring or repetitive work and creating opportunities for upskilling of the workforce your offering serves? Does your product help lower costs in the next quarter? Are you promoting human-machine complementarity? What can you tell your customers about using your offering as a springboard to diversify their activities and operate in sectors where they were not present before?
But, I see the present time also an opportunity for corporates to look closely and think bravely on how they can diversify their AI driven capabilities by buying as well as building in-house. As tempting as it might be to say, we can build our own predictive capabilities, it’s not the core business of most sectors and data science professionals are expensive. The right mix of tools can help corporates scale like it’s boom time and setting aside budgets to explore, try and buy from many external sources is a sure-fire way of building complementarity with in-house development.
Complex transitions will be unavoidable, as the losses and gains occur in completely different sectors of the economy. It is critical to invest in and nurture transversality and uncommon connections.
Soft skills will play a more prominent role, as the level of AI development cannot yet match humans in these skills- general cognitive skills AI cannot yet outperform human thinking.
Hubs and the ecosystems around them are well established in Europe offering an instant point of land and expand as well an opportunity-rich ecosystem for emerging companies. The core of the hubs are the University-Research-Financial support systems which are major enablers of Public Private Partnerships (PPPs), which are welcomed throughout Europe.
An interesting aside—the EU single market creates a homogeneity of business experience, but funnily enough, a recent study found that the biggest beneficiary of the European single market is a city which is not in the EU—Zürich.
Europe can gain decisive competitive advantages internationally if it is capable of generating a wave of bottom up digital innovations involving all industrial sectors. The potential benefits to productivity are manifold. They come from improving efficiency, optimizing business processes, and reducing the amount of time necessary to complete a task.
While the growth of the platform economy continues, Europe’s platform companies make up just 3% of its value. The absence of a strategic industrial policy puts our continent at a disadvantage.
The development of standards is another key area that European industries should reap benefits in emerging market segments, data formats, and standards for metadata, to name a few. Five priority areas currently to modernize the standardization system- 5G, cloud computing, IoT, data technologies and cybersecurity.
The recovery from the financial crisis has been characterized by a job-rich but productivity-weak recovery. Industry take up of AI is very important for Europe. In this light, the renewed EU industrial policy strategy launched in 2017 is a useful step forward.
Manufacturing, construction, automobiles, and pharma sectors are all areas that should be supported via an EU industrial policy.
However, SMEs represent the backbone of the EU economy and are its main engine for growth and employment. Member states have varying degrees of digital intensity, with Denmark at 40.6%.
There is a divide between the front-runner companies and the rest, because of the lack of access to high quality and quantity of data, high cost of transition to AI, including a paucity of capable technical staff. Open question, how do we democratize the access to good quality data sets? There is an increasing need to provide SMEs with access to algorithms which in most cases, they cannot develop on their own. The commission proposal in the Digital Europe program to develop common European libraries of algorithms that would be accessible to all is a welcome first step in this regard. Open data pools fed by companies and public institutions should be created to overcome data monopolies.
Many public institutions are careful about making use of AI because of concerns over bias, privacy, accountability, and transparency. Governments cannot use black-box algorithms that are increasingly characterizing industry-deployed AI. The public sector is one of the most data-intensive sectors. The free flow of data means the freedom to process and store data in an electronic format anywhere in the EU.
The AI sector in Europe could also benefit from the completion of the single market, establishing favorable conditions for business people to work across borders without high regulatory costs or barriers. The Commission intends to support the creation of a common European data space.
Transition costs into AI or Robotics can be substantial for companies. Productivity growth is also limited by the availability of digital infrastructures.
In Europe’s five largest economies, France, Germany, Italy, Spain, and the UK, McKinsey estimates about USD 2T in wages and 62 million workers are associated with technically automatable activities.
Global robotization, use of AI and automation continues to grow, with the worldwide AI market forecasted to grow to nearly $60B by 2025. Further estimates on the Internet of Things future indicate that humanity will be dealing with some 30 billion IoT devices by 2020…evenly distributed, that’s nearly four devices for every single human on this planet. As Michel’s report points out, there will clearly be major societal shifts and transitions to accommodate humankind’s evolving reality and future. It should be on all of our minds how to prepare for such a future, how to democratize the access to technology and the benefits of it, and how to thrive while preserving those things which make our communities unique and rich. In my opinion, this is the kind of report every region should be researching, writing, and acting upon the recommendations.
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Destination Europe for the Emerging Company
February 12, 2020
I
n its proposal for the next multi-annual financial framework, the European Commission put forth an idea to create a new Digital Europe program with an overall budget of Euro 9.2 billion to shape and support the digital transformation of Europe’s society and economy. Among the five priorities of the proposal, Euro 2.5 billion over seven years is planned to help spread AI across the economy and society. I read this fact with interest towards the end of this extensively-researched and action-provoking 136-page report authored by Michel Servoz in his former capacity as Senior Policy Advisor to the President of the European Commission. The title, “The Future of Work? Work of the Future”! is a fitting lead-in to the report’s in-depth examination of how artificial intelligence, robotics, and automation are transforming jobs and the economy in Europe.
Because the report covered tremendous ground on several interconnected topics influencing the future, it can be curated from many different perspectives and has much to offer business people, educators, thought leadership conveners, and policymakers as well as citizens who wish to better grapple with the technology-driven realities that will shape the future. In my summary, I have chosen to extract the questions whose timely solutions will be particularly relevant to the success of emerging AI companies trying to establish and grow in the region. If I were the CEO of such a company, what should I know about the space in Europe and what should I worry about? What should I leverage quickly? The tone of this report is hopeful and optimistic because it approaches automation outcomes as determinable by choices we make and the actions we take. Embracing educational systems, commercial life, governments, and social partners, the report has numerous illustrations of what can be possible as well as actual case studies. It sparks new ideas and presses the need for new frameworks within which to examine and prepare for the future.
My personal take-aways for emerging companies building and growing their presence in Europe are in the form of several questions they should ask themselves periodically- How does your offering increase productivity and lower costs? What is the pulse of the market (current) and what are the trends (future)? Do you have a community which will use, boost, and scale your offering? Who else can your offering serve? Ok, who else? What capabilities are you enabling for your customers’ customers? What have you learned from your dialog with prospects? How does your offering support data privacy, security and pull-technologies? Do you have anything which can enable smaller customers to benefit from powerful algorithms, benefit from insights drawn across public-private data pools? Are you reducing mistake-prone, boring or repetitive work and creating opportunities for upskilling of the workforce your offering serves? Does your product help lower costs in the next quarter? Are you promoting human-machine complementarity? What can you tell your customers about using your offering as a springboard to diversify their activities and operate in sectors where they were not present before?
But, I see the present time also an opportunity for corporates to look closely and think bravely on how they can diversify their AI driven capabilities by buying as well as building in-house. As tempting as it might be to say, we can build our own predictive capabilities, it’s not the core business of most sectors and data science professionals are expensive. The right mix of tools can help corporates scale like it’s boom time and setting aside budgets to explore, try and buy from many external sources is a sure-fire way of building complementarity with in-house development.
Complex transitions will be unavoidable, as the losses and gains occur in completely different sectors of the economy. It is critical to invest in and nurture transversality and uncommon connections.
Soft skills will play a more prominent role, as the level of AI development cannot yet match humans in these skills- general cognitive skills AI cannot yet outperform human thinking.
Hubs and the ecosystems around them are well established in Europe offering an instant point of land and expand as well an opportunity-rich ecosystem for emerging companies. The core of the hubs are the University-Research-Financial support systems which are major enablers of Public Private Partnerships (PPPs), which are welcomed throughout Europe.
An interesting aside—the EU single market creates a homogeneity of business experience, but funnily enough, a recent study found that the biggest beneficiary of the European single market is a city which is not in the EU—Zürich.
Europe can gain decisive competitive advantages internationally if it is capable of generating a wave of bottom up digital innovations involving all industrial sectors. The potential benefits to productivity are manifold. They come from improving efficiency, optimizing business processes, and reducing the amount of time necessary to complete a task.
While the growth of the platform economy continues, Europe’s platform companies make up just 3% of its value. The absence of a strategic industrial policy puts our continent at a disadvantage.
The development of standards is another key area that European industries should reap benefits in emerging market segments, data formats, and standards for metadata, to name a few. Five priority areas currently to modernize the standardization system- 5G, cloud computing, IoT, data technologies and cybersecurity.
The recovery from the financial crisis has been characterized by a job-rich but productivity-weak recovery. Industry take up of AI is very important for Europe. In this light, the renewed EU industrial policy strategy launched in 2017 is a useful step forward.
Manufacturing, construction, automobiles, and pharma sectors are all areas that should be supported via an EU industrial policy.
However, SMEs represent the backbone of the EU economy and are its main engine for growth and employment. Member states have varying degrees of digital intensity, with Denmark at 40.6%.
There is a divide between the front-runner companies and the rest, because of the lack of access to high quality and quantity of data, high cost of transition to AI, including a paucity of capable technical staff. Open question, how do we democratize the access to good quality data sets? There is an increasing need to provide SMEs with access to algorithms which in most cases, they cannot develop on their own. The commission proposal in the Digital Europe program to develop common European libraries of algorithms that would be accessible to all is a welcome first step in this regard. Open data pools fed by companies and public institutions should be created to overcome data monopolies.
Many public institutions are careful about making use of AI because of concerns over bias, privacy, accountability, and transparency. Governments cannot use black-box algorithms that are increasingly characterizing industry-deployed AI. The public sector is one of the most data-intensive sectors. The free flow of data means the freedom to process and store data in an electronic format anywhere in the EU.
The AI sector in Europe could also benefit from the completion of the single market, establishing favorable conditions for business people to work across borders without high regulatory costs or barriers. The Commission intends to support the creation of a common European data space.
Transition costs into AI or Robotics can be substantial for companies. Productivity growth is also limited by the availability of digital infrastructures.
In Europe’s five largest economies, France, Germany, Italy, Spain, and the UK, McKinsey estimates about USD 2T in wages and 62 million workers are associated with technically automatable activities.
Global robotization, use of AI and automation continues to grow, with the worldwide AI market forecasted to grow to nearly $60B by 2025. Further estimates on the Internet of Things future indicate that humanity will be dealing with some 30 billion IoT devices by 2020…evenly distributed, that’s nearly four devices for every single human on this planet. As Michel’s report points out, there will clearly be major societal shifts and transitions to accommodate humankind’s evolving reality and future. It should be on all of our minds how to prepare for such a future, how to democratize the access to technology and the benefits of it, and how to thrive while preserving those things which make our communities unique and rich. In my opinion, this is the kind of report every region should be researching, writing, and acting upon the recommendations.
