Artificial Intelligence in Europe - Outlook for 2019 and Beyond - How 277 Major Companies Benefit from AI - Microsoft Pulse
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Artificial Intelligence in Europe Outlook for 2019 and Beyond How 277 Major Companies Benefit from AI R E P O R T CO M M I S S I O N E D BY M I C R O S O F T A N D CO N D U C T E D BY E Y
Contents
Preface
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 06
Executive Summary - ‘At a Glance’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 08
Setting the Scene
About this Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Rich Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Executive Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Participating Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Bits & Bytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Follow the Money . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Experts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Role of AI in European Business
A Strategic Agenda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Among Friends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Push or Pull . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Ready, Set... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
AI Maturity Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
State Your Business . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Business Benefits and Risks
Another World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
AI Here, There, Everywhere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Use it or Lose it . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Making AI simple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Sector Benefits Landscape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Risky Business . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Learn from the Leaders
Capabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
AI Competency Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Advanced Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Data Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
AI Leadership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Open Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Emerging Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Disclaimer Agile Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
This report has been prepared by Ernst & Young LLP in accordance with This report does not constitute a recommendation or endorsement by Ernst External Alliances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
an engagement agreement for professional services with Microsoft. Ernst & Young LLP or Microsoft to invest in, sell, or otherwise use any of the mar- Emotional Intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
& Young LLP’s obligations to Microsoft are governed by that engagement kets or companies referred to in it. To the fullest extent permitted by law,
agreement. This disclaimer applies to all other parties. Microsoft and Ernst & Young LLP and its members, employees and agents, do Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
not accept or assume any responsibility or liability in respect of this report, or
This report has been prepared for general informational purposes only and decisions based on it, to any reader of the report. Should such readers choose What’s next for you?
is not intended to be relied upon as accounting, tax, or other professional to rely on this report, then they do so at their own risk.
advice. Refer to your advisors for specific advice. Ernst & Young LLP and Mi- How to Get Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
crosoft accept no responsibility to update this report in light of subsequent ©2018 EY LLP Limited All Rights Reserved. Who to Contact from Microsoft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
events or for any other reason. Contributors from EY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
2 3AI will be useful wherever intelligence is
useful, helping us to be more productive in
nearly every field of human endeavor and
leading to economic growth.
— Harry Shum, Executive Vice President of
Microsoft AI and Research Group &
Brad Smith, President and Chief Legal
Officer at Microsoft
4 5Preface Preface
Foreword
Human Ingenuity
The printing press, the automobile & the Internet are just a few technolog-
ical achievements that have advanced our world. All were driven by human
ingenuity: our innate creativity that inspires us to learn, imagine & explore.
This spirit is what pushes us to challenge the boundaries of the possible to
go ever forward.
Today, AI is helping to amplify our human ingenuity, opening up exciting
new possibilities for how intelligent technology can shape our world. At
Microsoft, our goal is to democratize access to AI for everyone through in-
novative & powerful platforms, & above all, we’re focused on ensuring that
our AI tools & technologies are deployed responsibly & earn people’s trust.
And yet, we realize that AI is one of the lesser understood modern tech-
nological break-throughs. Many questions remain. How are companies
applying this technology to empower employees, engage with customers,
transform their business and optimize their operations? Where are they
seeing benefits, and what are their blockers?
To provide answers, Microsoft commissioned this study to understand the
AI strategy of major companies across 7 sectors & 15 countries in Europe.
It examines these companies’ readiness to adopt AI, how they rate the im-
pact and benefits from AI implementations, and what they perceive as risks
& keys to success.
We hope you find these insights inspirational for your own journey toward
adopting AI & realizing its benefits for amplifying human ingenuity.
Vahé Torossian
President, Microsoft Western Europe
6 7Preface Preface
At a Glance
Noticeable potential for AI in many 8 key capabilities that are most transformation by articulating a vision,
corporate functions important ‘to get AI right’ setting goals and securing broad buy-
The most widely reported adoption When asking the respondents to rank in across the organization.
of AI (47%) was in the IT/Technolo- the importance of 8 capabilities to en-
gy function, followed by R&D with able AI in their businesses, ‘advanced To summarize, the challenge ahead
36%, and customer service with 24%. analytics’ and ‘data management’ appears to be as much about culture
Interestingly, several functions are emerged as the most important. ‘AI and leadership as it is about data,
hardly using AI at all; most notably, leadership’ and having an ‘open cul- analytics, and technology.
While the hype of artificial intelligence Most impact expected from ‘opti- is almost as much as AI is expected to
the procurement function, where only ture’ followed.
(AI) and its potential role as a driver of mizing operations’, with ‘engaging impact the core of these companies’ cur-
4% of the companies currently use AI,
transformational change to businesses customers’ as a close second rent business with 65% expecting AI to
followed by HR with 7% and product When self-assessing the capabilities
and industries is pervasive, there are 89% of the respondents expect AI to have a high or a very high impact on the
management with 9%. This is perhaps where the companies are least com-
limited insights into what companies generate business benefits by optimiz- core business. With AI presumably push-
surprising, given the many use cases petent, they point to emotional intel-
are actually doing to reap its benefits. ing their companies’ operations in the ing companies into totally new domains
and applicable solutions in these func- ligence and AI leadership - defined
This report aims at getting a deeper future. This is followed by 74% that ex- in the future, it is perhaps not surprising
tional areas. as the (lack of) ability to lead an AI
understanding of how companies cur- pect AI to be key to engaging custom- that AI is receiving attention as a key
rently manage their AI activities, and ers by enhancing the user experience, topic for executive management.
how they address the current challeng- tailoring content, increasing response
es and opportunities ahead. speed, adding sentiment, creating Very few of the 277 companies con-
experiences, anticipating needs, etc. sider themselves “advanced” with AI
To get to the heart of this agenda, we
What sets the most ‘AI mature’ companies apart?
Despite the apparent sizable impact that
received input from AI leaders in 277 C-suite respondents scored ‘engaging companies expect from AI, only a very
companies, across 7 sectors and 15 customers’ highest of the AI benefit small proportion of companies, consti-
countries in Europe, via surveys and/or areas. Noticeably, 100% of the most ad- tuting 4% of the total sample, self-re- They expect AI will be beneficial in ‘empowering employees’ (76% of ‘more mature’ companies vs. 42% of ‘less
interviews. Below is the brief summary vanced* companies expect AI will help port that AI is actively contributing to mature’ companies)*.
of what they had to say. them engage customers, compared to ‘many processes in the company and
only 63% of the less mature companies. enabling quite advanced tasks today’ They report using a combination of structured and unstructured data for AI (65% of ‘more mature’ companies vs.
AI is a “hot topic” - but more so on Using AI to ‘transform products and (referred to as ‘most advanced’ in this 15% of ‘less mature’ companies), and data from both internal and external sources (68% of ‘more mature’ compa-
C-level than in daily operations services’ comes out slightly lower with report). nies vs. 16% of ‘less mature’ companies).
71% of the companies respond that 65%, and ‘empowering employees’
AI is considered an important topic the lowest with 60% of the companies Another 28% are in the ‘released’ stage They expect AI will help them ‘engage customers’ (85% of ‘more mature’ companies vs.
on the executive management level. expecting AI-generated benefits in where they have put AI selectively to ac- 59% of ‘less mature’ companies).
This is significantly higher than on that area. tive use in one or a few processes in the
the non-managerial / employee level company. The majority, 51% of compa- They see AI predominately being driven from a combination of technology push and business pull (61% of ‘more
where AI is only considered an impor- AI is expected to impact entirely nies, are still only planning for AI or are mature’ companies vs. 32% of ‘less mature’ companies).
tant topic in 28% of the companies. new business areas in the future in early stage pilots. 7% of companies
Interestingly, Board of Directors also 57% of the companies expect AI to are self-rated as least mature, indicating * ‘More mature’ defined as companies that self-ranked as 4 or 5 on the maturity 5-scale, and ‘less mature’
came out lower with ‘only’ 38% of have a high impact or a very high im- that they are not yet thinking about AI at defined as companies that self-ranked as 1 or 2.
respondees reporting that AI is impor- pact on business areas that are “entirely this stage.
tant to their board. unknown to the company today”. This
Only 4%
Percentage of companies
that are still only in the
planning or piloting stages:
71%
of the companies
57%
of the companies
Share of companies that use
acquisitions as a way to 80%
of the most mature
obtain AI capabilities:
61% 10%
of the companies are actively respond that AI is considered expect AI to have a high impact companies expect that AI
using AI in ‘many processes ‘an important topic’ on the on ‘business areas that are will be beneficial by
and to enable advanced tasks’ executive management level entirely unknown today’ only ‘empowering employees’
8 9Setting the Scene Setting the Scene
About this Report
What’s new?
Artificial Intelligence (AI) is not new. in AI, what they are investing in, and efit areas, how mature companies are Straight from the executives Contributions from open-minded
It has existed for decades: processing how they are managing the compli- in terms of adoption, and examining and collaborative companies
Where this report and extensive da-
voice to text or language translation; cated process of adopting this new self-reported competence levels re- taset adds new insights is primarily We are extremely thankful for the time
During the past few years, we
real-time traffic navigation; dynami- technology and deriving value across garding the capabilities required to into how leading companies are ap- and effort the many executives have
cally serving targeted advertisements business opportunities. succeed when implementing AI. put into participating in interviews and have learnt what is easy, what
proaching AI on a very practical level.
based on personal data and browsing We hear straight from executives how providing data for this study. We’re par- is hard, what is realistic and
history; predicting trends and guiding Perspectives, experiences, self- From the aggregate dataset we have their companies are addressing cur- ticularly appreciative of their willing- what is only hype.
investment decisions in financial in- assessment, and benchmarks been able to determine some bench- rent challenges, and how they apply AI ness to openly share experiences and
stitutions. The current developments From new surveys, interviews and case marks across the covered markets, to unlock new value pockets. provide their perspectives on where
have been fueled by an exponential which we compare the individual the future is heading within AI. — DNA
studies gathered from approximately
rise in computing power, increasing country with throughout the report. Telecommunications
277 companies, we provide a snapshot Based on the many interviews con-
accessibility and sophistication of pow- of the current state of AI in 15 European The report also covers a full spectrum ducted, this report reveals some clear While this indicate a general interest in
erful algorithms, and an explosion in markets. This includes analyzing AI’s of industry groups which tend to reveal excitement and immense potential for the AI topic, it also speaks to the in-
the volume and detail of data available relative importance on the strategic interesting insights. using AI to bring new, improved prod- creasingly collaborative approach
to feed AI’s capabilities. agenda, its expected impact and ben- ucts and services to market, create many leading companies are taking
exceptional experiences for customers when entering new technology do-
Reality vs. hype and employees, and create ways to mains and embarking on journeys
operate that enhance performance into unknown territories.
Only recently started to see more
widespread, scaled adoption of AI across the board.
across sectors, value chains and eco-
systems. Yet AI technology is quickly We learned that regardless of which
approaching a point where it is be- use cases the companies pursue and
coming a critical element in enabling the role that AI currently has, taking a
companies across sectors to drive strategic outlook to assess the implica-
revenue, increase profits and remain tions for the business and responding
One of the key challenges is meeting the accordingly are increasingly seen as
competitive.
high expectations from the organization crucial for any executive agenda.
We hear many people in numerous - AI is not magic, but takes considerable
companies talk about AI. While the effort to successfully implement.
hype is pervasive, not a lot of people
fully understand its technological
potential, where it can create value or — H.Lundbeck
how to get started. This report aims at Pharmaceuticals
providing a practical understanding of
why European companies are investing
10 11Artificial intelligence in Europe Setting the Scene
Rich Data
Which sources of information is the study based on?
When working with AI initiatives, it is
important to focus on key business issues This report combines multiple sources
of data to answer the questions of why,
We also present case studies of specific
companies from different countries to
Recognizing and mitigating
potential survey and interview bias
that benefit the whole and not just doing sub- where and how AI is currently being used
in business. It provides an inside view
provide an understanding of what they
are doing with AI and why, drawing
In terms of methodology, this report
follows robust research design and
optimization at small scale.
across markets and sectors. It provides on lessons learned and obstacles to protocol. Doing so minimizes potential
a pan-European view, and adds value overcome when putting AI to use for bias, but does not eliminate it, as it
through a quantitative perspective on specific use cases and to derive value is inevitable in market research. One
how advanced companies are with AI, on a strategic level. potential type is social desirability
and a qualitative perspective on how to and conformity bias, as the topic of
Proprietary AI investment data
— Novo Nordisk Pharmaceuticals
develop the skills required to succeed AI receives lots of media and political
with AI. We have received input from We have supplemented the prima- attention. Response bias, including
over 300 people from 277 participating ry source input from the companies extreme responding, cultural bias, and
companies. This has resulted in a range of with acquisition data from numerous acquiescence bias (“yea-saying”), are
interviews and case studies as well as 269 sources, to take the pulse of the AI potential factors as we ask respondents
company responses to our survey. investment market in Europe. These to self-report on their respective com-
insights help provide a picture of the panies’ experience. Therefore, while
Extensive online survey data from wider European AI ecosystem and its this report follows best practices, some
business leaders in 269 companies development. bias is possible.
We have surveyed people with a leading
role in managing the AI agenda in all the AI expert perspectives Nonetheless, with the combination of
companies that have contributed to the With this wider understanding of AI extensive survey data, interview data,
study. This gives us an aggregate dataset start-up acquisitions, partnerships, and investment data, and expert perspec-
that enables a perspective for each mar- investment funding, we outline how tives, we believe the report provides a
ket and each sector, as well as compara- investments in AI are skyrocketing, solid foundation for an indispensable
I don´t see why speaking openly about
tive insights for the respective company where AI investment is taking place view of executive experience with –
types, sectors, and countries in Europe. geographically, and which sectors are and future plans for – AI in business.
our ongoing AI intiatives should be a big
making bets. As we are on the cusp of
Qualitative in-depth interviews with widespread change driven by AI, we
senior business executives also reached out to AI experts from
fuss. What really makes a difference from In addition, we conducted deep-dive
interviews to gain deeper, qualitative
academia for an outlook of AI technol-
ogies going mainstream, and to gain
a competitive perspective is a company´s
insights into how AI is affecting the ex- an understanding of the macro scale
ecutive agenda. Through conversations of business effects that they expect will
with business leaders, we report on materialize when looking into a distant
abilitity to execute. where they expect AI will have an impact,
how important AI is to their current and
future.
future business strategies, what benefits
they hope to realize from implementing
AI, and which capabilities they believe
— PFA Pension & Insurance are key to advance AI maturity in their
companies.
12 13Setting the Scene Setting the Scene
Executive Perspective
Large group of respondents Surveyed companies are well represented across
Who are the respondents that have contributed to the study? with a specific AI/digital role each of the 15 European markets
Organizational function of respondents Number of online surveyed companies per country
in the online survey
The data approach used allows us to Functional diversity A combined annual revenue
identify trends across industries and The respondents cover very different of $2.3 trillion
countries based on input from various functions, of which the most common Participants come from both major
N e th
functional business areas. Consequent- are designated AI/digital department, listed companies, privately held compa- 67
erlan
nd
ly, we have captured a range of in- followed by IT, and strategy/general nies, and in some case relatively small
Ir e l a
sights, learnings, and perspectives from
ds
management functions. This functional companies. In totality, they represent a 60
both strategic and technical points of diversity increases the breadth of the combined revenue of approximately
N
en
or
ed
view.
w
report, with insights and perspectives $2.3 trillion. Despite covering a signifi-
Sw
ay
22
20
covering widely different aspects of AI. cant part of total European business, our 45
Respondents predominantly in selection criteria have also favored more
20
21
D e nm an d
senior level positions ar k ze r l
Surveyed companies span niche oriented companies with extensive 39 Swit
To ensure that these insights and per- multiple sectors AI experience and capabilities. 27
25 20
26
spectives are relevant at the executive
level, we surveyed and interviewed
The participating companies are spread 269
fairly evenly across seven sectors, with online survey
21 20
high-ranking officers with a responsi- the majority of companies belonging companies Italy
Austria in total
bility for driving the AI agenda in their to Industrial Products & Manufactur- 5
respective companies. With 60% of ing, followed by Financial Services, and 22
22
respondents being either part of top Transportation, Energy & Construction.
management or the executive man- Services and Life Science are represented ga
l Fin
15
20
lan
tu
Digital/AI
General Management, Strategy
General IT/Technology
& Business Development
R&D/Product Management
Customer Service & Marketing
Admin & Finance
Other
21
agement team, their input is likely well r d
to a lesser extent. Po
attuned to the general perspective and
Un ce & G
overall strategic direction of the com-
ain
Fra
ite
Sp
panies they represent.
Luxenbourg
Belgium &
n
dK
i n g m a ny
do
er
m,
More than 300 participants Majority hold a top management or executive position
Number of participants interviewed Organisational level of person participating in the study
and/or online surveyed in the study
Seven major sectors covered in the study
Representation of participating companies per sector category
+
C-suite/Executive 27%
9% 21% 17% 7%
Top Management Life Science Industrial Products Finance Services
(non-executive) 33% Pharmaceutical, Healthcare, Manufacturing, Banking, Insurance, Professional Services,
Biotech Materials, Equipment Investments Hospitality, Public Services,
Membership Organization
Management
Level 37% 13% 16% 17%
Employee
(non-managerial level) 3% CPR TMT Infrastructure
Consumer Products Technology, Transportation, Energy,
& Retail Media/Entertainment & Telecom Construction, Real Estate
15 European markets 15 European markets
14 15Setting the Scene Setting the Scene
277 Companies Indie Campers, Intesa Sanpaolo, ISDIN, ISS, Jansen AG, Julius Baer,
Katoen Natie, KBC Group, Kemira, Kingspan Group, KLP Banken,
Komplett, Kongsberg Gruppen, LafargeHolcim, LanguageWire,
LEGO, LEO Pharma, Lerøy Seafood, Liga Portugal, L’Occitane, Lonza,
A.P. Moller - Maersk, Acciona, Adamant-Namiki of Europe, Aegon, L’Oreal, Lusíadas Saúde, Luz Saúde, Länsförsäkringar, MAPFRE,
Aena, Ageas, Agfa-Gevaert, Agrifirm Group, Ahlstrom-Munksjö, Merkur Versicherung, Metall Zug , Metro, Metso, M-Files, Millicom,
AIB, AkzoNobel, Almirall, Alpro, ALSA, Amadeus, AMAG, Ambea, Mota-Engil, Mutua Madrileña Automovilista, Møller Mobility Group,
APM Terminals, Aprila Bank, Arcelor Mittal, Ardagh Group, Neste, NH Hotel Group, Nilfisk, Nokia Corporation, NorgesGruppen,
Arval BNP Paribas Group, Asiakastieto Group, Assa Abloy, Norstat, Novabase, Novartis, Novo Nordisk, Novozymes,
Assicurazioni Generali, Atea, Audi, Austrian Airlines, Austrian Now TV, OBI, Oesterreichische Nationalbank, OP Financial Group,
Federal Computing Centre, Autogrill, BAM Group, Barco, BASF, Opportunity Network, Orion, Paddy Power Betfair, Peltarion,
BAWAG P.S.K, Baxter, BBVA, Besix, Bolloré, BTG, BUWOG, C&C Pernod Ricard,PFA, Philips, Planeta DeAgostini, Poste Italiane,
Group, Campbells International, Capio, Carmeuse, Carnival Posti, PostNord, Proximus, Pöyry, Rabobank, Raiffeisen Software,
UK, CEiiA, Cermaq, Chr. Hansen, Cirsa, City of Amsterdam, Raiffeisen Switzerland, Ramada Investimentos SA, Randstad, Rexel,
Colruyt Group, Com Hem, Combient, Comifar Distribuzione, ROCKWOOL Group, Room Mate Hotels, Royal College of Surgeons in
Constitutional Court of Austria, Coolblue, COOP Nederland, Ireland, S Group, Saipem, Saint Gobain, Sakthi Portugal, Salsa, Saxo Bank,
Cosentino Group, Costa Crociere, Credit Suisse, Crédito Agrícola, Sbanken, SBB Swiss Federal Railways, Schindler, SEB, SGS,
DAF Trucks, Danfoss, Danske Bank, Dawn Meats, DFDS, DNA, Siemens Mobility, SimCorp, Skandia, Solvay, Sonae, Sonae Arauco,
DNB, DSM, DSV, Dümmen Orange, Dynamic ID, DAA, Edison, SpareBank 1 SMN, SpareBank 1 Østlandet, Sportmaster, Statkraft,
EDP - Energias de Portugal, Egmont, EQT, Ericsson, Erste Group Stedin, Steyr Mannlicher, Stora Enso, Styria Marketing Services, Suomen
Bank, ESB, ESIM Chemicals, Esprinet, Europac, Fazer, FDJ, Terveystalo, Swedbank, Swisscom, Taylor Wimpey, TDC, Teamwork,
Federal Office of Meteorology and Climatology MeteoSwiss, Ferrovial, Telefónica, Telekom Austria, Telenor Global Shared Services, Telia,
Fexco, Finnair, Fortum, Galp, Geberit, Genalice, Generali Versicherung, Tesco, Tetra Pak, The Navigator Company, TIM, Tine, Tokmanni ,
GetVisibility, Gjensidige Forsikring, Glen Dimplex Group, Globalia, TomTom, Tryg, TTS Group, TVH, Ubimet, UDG Healthcare, UniCredit,
GN Store Nord, GrandVision, Grupo Antolin, Grupo Ascendum, Unilin, UPM, Vaisala, Valmet, Valora Group, Van Lanschot, Vattenfall,
Grupo Codere Cablecom, Grupo Juliá, Grupo Nabeiro – Delta Cafés, Version 1, Visana, Vodafone Automotive, VodafoneZiggo, Voestalpine
Grupo Pestana, Grupo Visabeira, GSK, GAA, H. Lundbeck, Hafslund, High Performance Metals, WABCO, WALTER GROUP, Western Bulk,
Handelsbanken, Hera, Hostelworld, Husqvarna, IKEA Group, William Demant, Wind Tre, WIT Software, Wolters Kluwer, Zurich
Ilmarinen Mutual Pension Insurance Company, Implenia, Impresa, Airport, Zurich Insurance, Öhman, Ørsted, Österreichische Post.
Note: Of all contributing companies, 14 chose to be anonymous
16 17Setting the Scene Setting the Scene
Bits and Bytes
What technologies and data solutions are within the scope of the study?
AI can be defined as the ability of a not in common use by companies in While companies historically have Companies are using a combination of tions mentioned by many respondents
machine to perform cognitive func- Europe. Companies surveyed are cur- primarily have used internal data for on-premise and cloud solutions are the flexibility to swiftly scale systems
tions which are normally associated rently focused on narrower and more supervised Machine Learning, many Companies are increasingly using cloud- up and down to accommodate changing
with humans. This includes reasoning, specific use-cases that support existing have begun exploring the possibility of based AI solutions for both storage and demand, a variable cost structure, and
learning, problem solving, and in some business. These efforts will undoubt- combining internal and external data- on-demand computing power - 83% of access to larger data sets. However, many
cases even exercising human behavior edly help companies build capabilities sets in order to produce even deeper companies reporting using Cloud tech- companies are still relying on on-premise
such as creativity. that are necessary to deploy more insights. nology to some extent to enable their AI solutions, not least due to existing data
advanced AI solutions in the future. capabilities. Key benefits of cloud solu- infrastructure.
Advanced AI applications are not Machine Learning and Smart Robot-
yet widespread Machine Learning ics were found to be the most useful.
AI holds the potential to transform The most commonly used AI technol- It is not clear from the study if this is
business in a radical way given its wide ogy among the surveyed companies because they are simply the most com- Machine Learning and Companies are using a mix of Data Sources and Storage
variety of use. Quite simply, business is Machine Learning. This is inarguably mon starting points before deploying Smart Robotics found to be Solution: How are you primarily dealing with the computing demands
leaders need to understand AI in order due to its wide-ranging applicabili- more advanced technologies, or if they the most useful needed for AI?
to grasp the opportunities and threats ty, making it relevant for a variety of also longer term hold the most wide Which of the following technologies have Data Source: 1.Are you currently using unstructured or structured data
the technologies pose. use-cases across the value chain. Of the and sigificant application potential. you found to be most useful in your com- types in your AI process? 2.Are you currently using internal or external
different types of Machine Learning, pany’s deployment of AI? data sources in your AI process?
While companies acknowledge the the most common is supervised Ma-
significant potential of broader, more chine Learning, where software is fed
advanced AI technologies such as structured data and finds patterns that Data Source Solution
computer vision, speech recognition, can be used to understand and inter-
and virtual agents, they are currently pret new observations.
77% 44% 40%
A broad definition of technologies are included in this AI definition Machine Smart Natural
Technologies included in the definition of AI used in this study learning robotics language
processing 38% 32% 27%
Internal Structured In Cloud
Text Analysis
Computational analysis of texts,
making it readable by other AI or
Natural Language Processing computer systems. Biometrics
Computer interpretation, under- Analysis of human physical and 39% 39% 26%
standing, and generation of written emotional characteristics – used
natural human language. also for identification and access
control.
Neural Text Virtual
networks and analysis agents
Virtual Agents
Machine Learning deep learning 3% 7% 17%
Computer-generated virtual personas
that can be used to interact with people A computer’s ability to ‘learn’ External Unstructured On premise
in both B2C, C2B, and B2B contexts. from data, either supervised or
non-supervised.
Speech Recognition Neural Networks and Deep Learning
Enables computers to interpret spo- Machines emulating the human brain,
ken language and to transform it into enabling AI models to learn like humans. 21% 20% 6%
written text or to treat it as commands
for a computer.
Computer Vision Speech Computer Biometrics 44% 43%
Gives computers the ability to 56%
recognition vision Both Both
Smart Robotics “see” images similar to how Both
The combination of AI and robots to humans see.
perform advanced tasks compared to
traditional non-intelligent robots.
Affirmative responses, 15 European markets Note: Remaining percent ‘Don’t know’ responses
18 19Setting the Scene Setting the Scene
Follow the Money acquisitions, and is also much in line
with what we’re seeing when compar-
ing with the US and Asia.
TMT most active, behind private
equity and venture capital
Investments into AI companies per sector,
How much is invested in AI in Europe? Finland mUSD (accumulated 2008-2018)*
$24M Investment activity concentrated in
Norway 21 deals major European markets
$30M It comes as no surprise that a lot of
A few big AI transactions 5 deals
influencing the overall picture investment activity is in the UK, France,
Company AI investments in mUSD and and Germany, having attracted 87% of
$254M
transaction volume per market 73 deals investment in AI companies over the
past decade. The UK leads significantly $7,453M
(accumulated 2008-2018) Sweden 1,027 deals
in this regard, with 533 of the total Private Equity /
1,362 AI transactions in Europe. From Venture Capital**
an investment perspective, it is also
$330M*
21 deals worth noting that in April 2018, the EU
committed to a 70% increase in invest-
$7262M Denmark
Ireland ment in European AI by 2020, suggest-
533 deals
The Netherlands ing further growth and potential in the
United Kingdom
$39M region.
$43M
37 deals 45 deals
$110M $520M
14 deals 140 deals
Belgium
Germany
Steady increase in European AI investment
AI companies invested into, transaction volume, Europe (from 2008-2018)** $1,843M
220 deals
$107M TMT
31 deals $75M
17 deals
$1357M Switzerland
165 deals Number of $494M
Austria transactions 17 deals
France Industrial Products
$3M 450
8 deals $368M
398
Portugal $47M 12 deals
29 deals 400 Infrastructure
European $131M Italy
350 327
markets 79 deals
Total $254M
UK bubble size not represenative 300 investment 21 deals
*Universal Robots acquired for $285M $10.5bn Life Science
v
250 228
The acquisition data from numerous alone. This trend is on track to con- tive investors and acquirers of AI than $70M
corporates, accounting for 75% of deal 200 41 deals
sources enabled us to explore the tinue, with an exponential increase Finance
European AI ecosystem and gain in- in interest in AI driving more large volume in the last 10 years. This is an 148
indication that AI companies are in the 150
sights into investment activity. companies to invest in AI or acquire AI
bilities from innovative start-ups. Of early stages of high risk/high growth
100 88 $38M
An exponential increase in AI in- the 15 markets surveyed, some include dynamics. It also indicates that, for 10 deals
64
vestment over the past decade one or two transactions that are signifi- large corporates, acquiring or invest- CPR
ing in external AI businesses in order 50 29 27
Looking at AI transaction activity cantly large deals. 14 11
to obtain AI capabilities is relatively
across Europe, there has been a steep 0 $22M
Majority of investments in AI from limited. This is confirmed by our survey 14 deals
consistent growth trend over the past
private equity and venture capital results where only 10% of companies 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Services
10 years, totaling 1,334 transactions
are seeking to obtain needed AI capa-
involving AI by 2017 – with a six-fold Private equity (PE) and venture capital
bilities through external investment or
increase in activity in the last 5 years (VC) firms are significantly more ac- Europe **Including governmental investment
Note: Several transactions in the dataset did not have publically disclosed deal values, suggesting that actual total values are higher than what’s shown above *For all of Europe, 34 countries (not just the 15 markets focused on in this report)
20 21Artificial intelligence in Europe ( Case Study ) Setting the Scene
Ageas Expert Perspective
What does the future look like according to AI analysts?
Ageas is currently using various forms cars in insurance claims, which frees Ageas is also anticipating going be-
of AI, while also investigating the po- Ageas from having to send investiga- yond pictures, towards AI that can
tential to use even more. For its daily tors to assess the damage. This appli- interpret videos. Furthermore, Natural
operations, AI models are used to cation of AI makes the process signifi- Language Processing (NLP) is being
forecast many aspects of the business. cantly faster and more convenient for applied in call centers and will soon
These forecasts are used by Ageas both the client and Ageas. The appli- play a pivotal role in transforming cus-
employees to make informed tomer service. Ageas is imple-
decisions. Ageas currently has menting Artificial Intelligence We also spoke to a range of leading AI Agile culture enables AI task is to educate and improve un-
over 100 internal predictive in client-facing areas to re-
analytics projects running
Ageas is implementing Artificial In- spond quickly and accurately,
experts from business and academia Culture was a recurring theme as well. derstanding, from C-suite leadership
to gain insights into the kind of change teams to employees at the coal face.
or in the pipeline for the telligence in client-facing areas to while freeing up employees which we are on the cusp, and the
It can either stifle forward momentum
This also ties in with the importance of
in organizations, or be the silver bullet
coming two years, of which respond quickly and accurately, while to focus on the most critical role AI is expected to play as part of a that enables the potential of AI to be partnering to get started and access
more than 10 have already freeing up employees to focus on the aspects of the business. The broader transformational wave. realized from top to bottom. the expertise needed to use AI. While
been implemented into the key problem it faces with
business.
most critical aspects of the business. many AI technologies is their
partnering and collaborating solves
AI is entering the mainstream Some of the experts even argue that the perennial AI challenge concerning
dependence on language. and here to stay the scarcity of talent, the significant
it’s not only technical skills that hold
However, for Ageas the most For example, a successful sys- cost and substantial benefit that can
One thing was clear from the experts up AI projects, it’s also the need for a
interesting aspect of AI lies in its ability cation of image analytics started in the tem implemented in the UK cannot be be gained from AI means that organ-
we spoke to: as far as the peaks and culture of experimentation.
to process unstructured data. Ageas UK and is now being quickly rolled out simply transferred and implemented in izations also need to be cognizant of
troughs of hype and technological
has begun using AI to analyze custom- to its other markets due to its success. Belgium or Portugal. building capabilities in-house for the
leaps surrounding AI go, there is no Companies that are more natively
er photos to estimate the damage of long-term.
doubt that we are living through a digital or have gone down that road
particularly prominent peak, with no understand the value of experimenting
indication that the buzz nor the po- and iterating. They don’t think in tra- Finally, as AI develops, we are also
tential will fade away any time soon. In ditional terms of committing to year- going to see innovation and expertise
spreading outside of the dominant
What next? a world increasingly dominated, dis-
rupted and driven by innovative tech
long projects that need to produce
specific outputs, but rather to explore clusters of the likes of Silicon Valley,
powerhouses, large and small, it is no and test ideas before scaling. as governments, businesses and uni-
Ageas is a Belgium-based insurance company, employing over Going forward, Ageas will expand its AI initiatives to scale early versities increasingly invest in building
understatement to suggest that AI will
50,000 people globally to serve 39 million customers across 15 successful use cases with intelligent automation in the front- knowledge, resources and capabilities.
be a chief protagonist in the change When it comes to AI,
countries, predominantly in Europe and Asia. With over 3 million end and back-end of the business. The goal of this is to further
transcending all elements of business knowledge is power
clients in Belgium, almost 1 in 2 Belgians households are customers automate processes and increase the efficiency of employees
in what has been labelled the Fourth Expert opinion also seemed unani-
of Ageas, making it a market leader in life insurance and number on a large scale by empowering them with AI tools. Ageas is
Industrial Revolution. mous in that most people not directly
2 in non-life. Its revenue in Belgium was over €5 billion in 2017. progressively rolling out an AI-driven system aimed at forecasting
what employees need and pushing it to them. The system will involved with AI must still have quite a
Ageas is also a major player in auto insurance and travel insurance Business-minded people will
also play an important role in systemically mining the knowledge basic understanding of what AI is and
in the UK. drive the transformation
embedded in the company. what it can actually do. Therefore, the
The AI experts confirmed some of the
key ingredients necessary for AI in
organizations: a combination of do-
main and technical expertise, the ap-
propriate technology, the right talent,
and lots and lots of data. While letting
tech-savvy individuals drive innovation Farmers and growers are still reasonably
We believe that AI will bring significant You need experts that truly know the is great for building understanding, conventional, with an average age of 55 years. The
disruptions, such as enabling self-driving cars. true transformation will not come until
technological playing field. You have to work chances are that this will change significantly in the
business people start suggesting prob-
If cars can become self-driving, why would with PhDs that understand both technology future. It could just be that technology companies
lems for AI to solve - not the other way
there be a need for personal insurance? and semantics. These people are hard to find, round. will become the disruptors of our market.
they know they are precious on the market
and they are typically more willing to join — Royal Agrifirm Group
start-ups. Agricultural cooperative
22 23Setting the Scene Setting the Scene
We believe that every organization is going to have to write their
From the Horse’s Mouth* own AI manifesto: what they believe about AI, how they’re going
to use or not use data, how they’re going to publish data, and
*From the highest authority
make the consumers of their products and services aware of that.
The creation of those manifestos is going to become a gateway
to the success of AI.
— Norm Judah, Chief Technology Officer of Worldwide Services
at Microsoft
The full extent of the AI story remains in its early stages. What
we do know is that big data, computing power and connectivity If you have a ton of data, and your problem is one of classifying
are changing the industrial landscape. The opportunity rests in patterns (like speech recognition or object identification), AI may
accelerating the digitization of businesses, making them more well be able to help. But let’s be realistic, too: AI is still nowhere
data driven by building applications that deliver machine-assist- near as flexible and versatile as human beings; if you need a ma-
ed insights. chine to read, or react dynamically, on the fly, to some kind of
ever changing problem, the technology you seek may not yet ex-
— Mona Vernon, CTO, Thomson Reuters Labs ist. Intelligence is a really hard problem.
— Gary Marcus, Founder & CEO, Geometric Intelligence, and
Professor, New York University
In some cases, there is too much hype, but paradoxically, the
potential opportunities and benefits of AI are still, if anything,
under-hyped. Often, the impact of new technologies is overes- AI is a general purpose technology, so will eventually affect all in-
timated in the short term and underestimated in the long term, dustries. However, this impact can be slowed by the lack of data
and while there is a lot of noise regarding AI, there’s been a lack in particular industries. There’s also more innovative cultures
of in-depth discussion and analysis of how it’s actually going to inside different organizations, that can either drive adoption or
transform businesses. prevent it.
— Nigel Duffy, Global AI Innovation Leader, EY — Marc Warner, CEO, ASI Data Science
24 25Artificial intelligence in Europe Role of AI in European Business
A Strategic Agenda
Where is the AI conversation currently taking place?
Role of AI
A good starting point to understand Active C-suite and Board of Direc- Speculating about the reason, it could
how large European companies are tors involvement both pertain to job insecurity and to
handling AI is to look at who in the In 71% of the companies surveyed, AI the fact that AI is still a highly abstract
organization is driving the AI agenda, is already an important topic on the topic for many when it comes to prov-
whether it be the Board, the C-suite, C-suite agenda and across various ing day-to-day business value.
managers, or employees. roles - from cost-focused CFOs looking
for efficiency through automation, to
in European
AI is particularly relevant at CDOs with customer-oriented ambi-
higher organizational levels tions as part of wider digitalization
From driving strategic considerations efforts, to the CTOs who is often still
at the Board level to being a topic of in- responsible for a type of AI Center of
terest or concern at the employee level, Excellence.
the results are clear: AI is important
Business
and resides across all levels at many of Companies more advanced in AI tend
the organizations we interviewed. to have stronger involvement of the
C-suite and the Boards of Directors
Only a few companies stated that AI is than the rest. They focus less on the
not currently an important topic at any technology itself and more on the busi-
level of the organization - while the ness problems that AI can addresses.
vast majority of companies view AI as Relatively speaking, the AI topic seems
generally important regardless of how to not yet having reached the same
advanced they are, or how much AI is level of importance at the non-mana-
being considered for deployment in gerial level (employees) than at the top.
the near future.
There is a lot of hype surrounding AI at the moment, and few
doubt its potential. We examine how important is AI compared to
other digital priorities and where AI fits on the strategic agenda. AI is an important topic on the C-suite level in particular
On what hierarchical levels in your company is AI an important topic? AI is in particular an im-
portant topic at the Execu-
tive Management level
We look at the impact of AI on the company’s core business, as
S T R AT E G I C L E V E L
well as adjacent and new areas of business. Board
of Directors 38%
level
Executive
We also examine the current AI maturity levels across sectors and Management
level
71%
markets, the potential drivers for deploying AI, and where AI is
Managerial 56%
applied within organizations, across customer-facing functions, level
operations, product development, and internal business support. Employee
(non managerial 28%
level)
O P E R AT I O N A L L E V E L
Affirmative responses, 15 European markets
26 27Role of AI in European Business Role of AI in European Business
Among Friends Push or Pull
What is the importance of AI against other digital priorities? How is AI predominately deployed into the organizations?
To understand the drivers behind AI deployed and managed in a balanced way
In a business era driven by innovation The participating companies are gen- the adoption and deployment of AI How would you characterize the way AI is being managed in your com-
and tech-led disruption, AI is obviously erally in the process of understanding in the companies, we took a closer pany? How would you characterize the way AI is being deployed in your
not the sole priority. the potential of existing data, includ- look at how AI is approached in a top company?
ing to what extent it can be used, down-bottom up management con-
AI as a digital priority what it can be used for, and how to text, and from a functional tech- vs.
When asked on a scale of 1 to 5 how capture and leverage it. business driven dynamic.
important AI is to the business relative
to other digital priorities, the majority Furthermore, many of the companies AI driven from a combination of top Top Down Bottom up Both
of respondents told us that it is about are focused on building the appropri- down and bottom up
equal. Very few organizations said it ate data infrastructures or modern- Contributing companies are quite
was their most important digital priori- izing legacy systems as a top digital evenly split across deploying AI as a
ty, or not formalized as a digital priority priority, both being prerequisites top down process, as a bottom up, or
at all, with the spread of responses for introducing AI into the company. as a combination of the two. However,
leaning slightly towards the upper end Considering that AI is heavily reliant when looking at the self-reported most
Deployment Approach
of the importance spectrum. on data as its fuel, this development advanced companies, they are more
suggests that the foundations are top down than bottom up in their ap- 34% 29% 28%
This slant is likely to increase as many being laid for further AI integration in proach. It was clear from speaking with
companies expect AI to become more the years to come. them, that this is partly a result of AI
important, as the technology develops being increasingly important enabler in
and use-cases become more clear to the company, and playing an increas-
Business Pull IT Push Both
companies. ingly significant role in the the overall
strategy.
AI driven from a combination of
technology push and business pull
According to a large part of the com-
panies and despite still being a techni-
cally complex thing that requires many 24% 23% 45%
AI is seen as one of many digital priorities - but rarely the most important
The majority consider specially skilled employees, AI is most
How important is AI relative to your company’s other digital priorities?
AI to be important often deployed as a combination of
business pull and technology push.
This resonates well with one of the 15 European markets
Avg. Score most consistent inputs from the execu-
44% Note: Remaining percent ‘Don’t know’ responses
28% tives on the most sought after AI pro-
9% 12% 3.1 files which centered in on the hybrid
7%
profile that understand the business
needs and the ability to match them to
the technological possibilities.
1 2 3 4 5
Not important Important Most important
AI is not formalised AI is one of many AI is the most important
as a digital priority digital priorities digital priority
15 European markets Note: Remaining percent ‘Don’t know’ responses
28 29Role of AI in European Business Role of AI in European Business
Ready, Set...
TMT sector with largest percentage of companies that are either released or advanced
How would you describe your company’s general AI maturity? Sectors arranged by maturity based on Advanced and Released
What is the maturity of AI in different sectors?
TMT 2% 10% 40% 45% 2%
While working with AI should be con- the structure of existing data, collec- Services 5%
6% 22% 27% 27% 18%
sidered a continuous journey, the AI tion of new data, and data access in
maturity of surveyed companies pro- general. However, the trend is clear:
vides a tangible indication of the level AI maturity is on the rise as adoption of Finance 4% 22% 34% 36% 4%
of advancement of current initiatives. key technologies accelerates and inter-
nal capabilities grow.
Multiple use cases, limited scalabil- Infrastructure 5%
9% 21%
17% 32% 46% 28%
ity and advanced use The vast majority of European busi-
The majority of companies have begun nesses are currently either conducting
exploring use-cases, while some com- pilot projects to test selected use- Industrial Products 4% 21%25% 53%44% 21%
panies have made early investments cases, or have commenced implement-
with the intention of taking a leading ing AI in the business. When talking
position in AI. The levels of advance- with executives, it is evident that many Life Science 4%
7% 25% 45% 49% 34% 17% 4%
ment also vary in that some companies companies are struggling with how to
are focusing on narrow use-cases to integrate pilot projects into daily op-
support their existing business, while erations. CPR 25% 29% 29% 9% 9%
others are taking an explorative ap-
proach. Among the small group of Clear sector patterns, with TMT,
companies with no or only little AI Services, and Finance on top
0% 20% 40% 60% 80% 100%
activity to date, several respond that Companies currently leading the way in
they are planning to drastically ramp terms of AI maturity are in TMT, Servic-
None Planned Piloting Released Advanced
up efforts soon. es & Hospitality, and Financial Services.
Companies in those sectors gravitate
Technology immaturity and internal towards grading their AI maturity as
We have multiple sources
data quality are key obstacles ‘Released’ (AI in active use, though
of ideas for AI. They can selectively or not with very advanced
Many companies that have already This indicates slower technology ‘Advanced’ stage of AI maturity.
come from the business implemented AI initiatives in their tasks), or ‘Advanced’ (AI actively con- adoption lead times in these slight- Several companies in both Consumer
but also from data science businesses are seeing tangible benefits. tributing to many processes and en- ly more conservative sectors. Yet, Products & Retail and Services & Hos-
Consequently, many of them are ex- abling advanced tasks). A logical ex- with 74% of companies being in the pitality cite the challenges of knowing
teams presenting different
ploring more use-cases and structuring planation for the maturity in TMT and ‘Piloting’ or ‘Released’ phases, the what relevant AI technologies are avail-
possibilities in a proactive Finance is their tendency to be digitally
their learnings from previous AI pro- Infrastructure sector also seems to able, utilizing unstructured data, as well
approach, as these are new jects into a modus operandi that can advanced and more savvy with analyt- be evolving onto more advanced AI as affording the payback period where
skills within the company. speed up new initiatives. ics, favoring these companies to pro- maturity. there may be large upfront costs and
gress beyond piloting by having data undetermined returns on investment.
At the end, there has to be
Meanwhile, a substantial number of science capabilities in place to evolve Life science and CPR have fewest
agreement between both towards more advanced AI stages.
companies have intentionally chosen to released projects
groups to sign off on AI take a ‘follower’ position, reporting the Consumer Products & Retail compa-
projects. perceived immaturity of AI technolo- Infrastructure and IP with relatively nies have a broad spread in terms of AI
gies as a key reason. Another reported many projects in ‘piloting’ phase maturity, where 25% state they have
obstacle to rolling out broader AI The Infrastructure and Industrial Prod- no plans at present for how and when
—Tetra Pak ucts sectors both stand out as having
initiatives are rooted in data and data to use AI – much higher than other
Food processing and no companies responding that they are
infrastructure, where companies have sectors – while others in the same
packaging ‘Advanced’ in AI at this stage.
separate projects aimed at improving sector are already at the ‘Released’ or
30 31Role of Ai in European Business Role of Ai in European Business
AI Maturity Curve
Majority of companies are in the ‘Piloting’ or ‘Released’ stage
We asked companies to self-report their current AI maturity level, grading themselves at None,
Planned, Piloting, Released, or Advanced - as defined below.
L E V E L O F M AT U R I T Y
Advanced 10 / 269
(4%)
AI is actively contributing to many
processes in the company and is
enabling quite advanced tasks 74/ 269
(28%)
Released
AI is put to active use in one or
106 / 269
a few processes in the company,
but still quite selectively, and/or
(39%)
not enabling very advanced tasks
Piloting 59 / 269
(22%)
AI is put to active use, but still
only in early stage pilots
20 / 269
(7%)
Planned
AI is being planned, but not yet
put to active use, not even in
early stage pilots
None
Not yet
thinking
about AI
15 European markets
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