The global AI market is expected to grow from $8.1B (2018) to $105.8B (2025). 42.CX tracks more than 11.000 AI companies worldwide and identifies the greatest Artificial Intelligence opportunities determined by an international team of scientists and experts.
42 provides research and advice in public and private AI companies accross all industries to financial institutions, private equity funds, venture capital funds, investment managers, family offices and qualified investors.
Our customers can be anyone who is quick to adapt to change and embrace an emerging industry to hedging their bets through portfolio diversification and wants to become one of the early investors in what is likely to be the greatest commercial opportunity of our generation.
As appealing as the global AI growth rates look like, the AI market environment is also becoming more and more scattered. According to recent studies, more than 40% of companies claiming to be "AI companies" actually don't even have any AI competence. It is becoming challenging to identify and distinguish betweem them, because a high degree of technical expertise is required. We track more than 11.000 AI companies worldwide and are able to identify the greatest Artificial Intelligence opportunities with a combined quantitative and qualitative approach. With our AI Market Intelligence Platform we have the ability and know how to provide the insight and research on the biggest database of AI companies that are shaping the future of AI, whether you are looking for a single company or a portfolio of companies, we have the insights for you in the publicly traded companies market and in the privately owned venture capital and private equity companies market. For each company, an individual score card is being generated.
Combined Quantitative & Qualitative Analytics
We typically work with financial institutions, investment and asset managers, family offices, HNWI and qualified investors to provide them independent in-depth market intelligence to identify single investments or to create an entire product portfolio. These can bei either public companies with AI expertise or venture capital or private equity backed private companies from any geographic area in the world.
The Dow Jones Industrial Average (DJIA) is a stock market index that shows how 30 large, publicly owned companies based in the United States have traded during a standard trading session in the stock market. It is one of the most important financial indicators worldwide. S&P500 and NASDAQ are tracking technology companies in general. We believe that ongoing AI revolution required a dedicated index.
Consequently, and given the rise of Artificial Intelligence, we have introduced the AI42X INDEX for publicly traded companies and AI42 INDEX for Private Companies. The AI42X INDEX is a world wide capitalization weighted market index based on the market opportunities of the 42 greatest Artificial Intelligence opportunities public companies, while the AI42 INDEX is the same but for private companies.
The AI ANALYST is our market analyst application and provides financial advisors deep insights into the AI ecosystem. It also serves the purpose of simulating and tracking investment decisions. Financial instruments - such as stocks or ETF's - all from the AI investment ecosystem, have been compiled and can be added to portfolios. For each instrument, multiple indicators are showing our expert ratings. This provides predictive intelligence into the health of AI companies and helps identifying the best future performers. Our indicators are used by clients to identify, prioritize and nurture opportunities, to see fast-growing markets and industries before others to inform strategic decisions or to pinpoint fast-growing public companies to understand their strengths in AI, products and technology.
Our report provides a comprehensive overview of the Artificial Intelligence Market and its investment opportunities. It disusses the AI business ecosystem, provides insights in AI application technologies and views the vision of possibilities.
Over the years we hand picked a team of experts, each of them a renowned expert in his field. Each expert is contributing to our AI market intelligence platform by providing insight, analysis and scoring. Propiertary formulas are weighting these expert driven inputs and adds a layer of intelligence to the companies we are tracking.
Accomplished international speaker on the subjects of sustainable management, social innovation and the future of work.
Technology entrepreneur. HF trading at UBS London, coFounder of last.FM, CTO of Jumio and CEO of Snapscreen.
Marketing and PR Expert. Former Jajah, Jumio and founder of Creatix. Received multiple awards.
Google Zurich, London, Moscow and Tel Aviv. Expert for innovation and user experience.
Chair for Information Management in Engineering at KIT, Director for Intelligent Systems at FZI.
Serial Internet entrepreneur. International speaker. Book author.
SVP UniCredit, expert for strategic communication and digital readiness, speaker and moderator, initiator HVB Women´s Council
CEO & Co-Founder dataflag, Data Compliance & Univ. Lect. i.Economics Webster Univ. & Supervis.Board Memb Raiff. Bank Int.
Key Researcher with the Fuzzy Logic Laboratorium. Author of 170+ publications
Creative expert and entrepreneur. Expert for graphic and design and Ui/Ux.
Entrepreneur and experienced operations manager at international scale.
Art- and Creative Director, expert for global brand strategies and new business operations.
Internationally awarded scientist. Founding Chairman of RISC; Founding Head of Softwarepark Hagenberg
Market trend analyst and expert for Thomson Reuters, Capilis and GFG Group.
Expert for international corporate finance, mergers and acquisition and taxes.
Professor of the Russian Academy of Sciences. Invented IBM Kaissa.
So there seems to be trouble in Paradise. The globe is facing massive challenges like climate change, cyber-crime, shortage of available resources, political instability and the potential of massive job loss because everything that can be automated will be. At the same time, we are seeing unprecedented opportunities like we have never before. Algorithms help us to better diagnose, predict and prevent diseases, they revolutionize the education sector by treating each student as an individual, and they free us from many repetitive and often cumbersome tasks.
These new AI technologies disrupt our personal and our professional lives. Platform based services address more and more of our needs as they deliver tailor made personalized experiences to us like shopping recommendations, driving assistance, even recognizing our mood just to provide us with music that matches our state of mind. Simply amazing. It is happening all around us and yet it seems that many of us do not understand that we are transforming from an old world with established rules to a new world that lacks definitions and witnesses constantly evolving business models. This new world is changing at exponential speed and no stone remains unturned.
Industry experts argue that we are currently in a two-horse race between China and the US when it comes to AI and how it is changing the world. Europe is a distant third and yet so far behind that it does not even matter who is actually in third or fourth place. This begs the question how we can better prepare the people in Europe and anywhere else in the world to successfully compete in a space that requires new skills and competencies, new forms of collaborations and most importantly new mindsets?
Education would seem a natural answer. But not in the traditional sense. When we hear the word education we tend to think about primary, secondary and tertiary learning institutions like elementary school, high school, college or university. We have to rethink the concept however. Education in the future will be all about lifelong learning – about constantly assessing what skills we need for future jobs and identifying the best learning platforms to get them. So what are these skills and how can we get trained? In their report Skill Shift Automation and the Future of the Workforce consultancy company McKinsey reports that the biggest change will take place in technological skills, both in advanced skills such as programming and advanced data analysis, and also in more basic digital skills relating to the increasing presence of digital technologies in all workplaces.
While not everybody is capable of programming algorithms or advanced data analytics, the broader population should be exposed to the basics of Artificial Intelligence and its impact on our daily lives as well as the Future of Work. The Finish government has recognized this need and set itself an ambitious goal. In collaboration with the University of Helsinki it designed a course to introduce 1% of its population to the basics of Artificial Intelligence. Citizens and interested individuals anywhere can go online and take the course which offers in total six modules; (1) what is AI, (2) solving problems with AI, (3) real world AI, (4) machine learning, (5) neural networks, and (6) implications. The course provides an introductory level overview of the technology and enables the students to engage in the discussion about a future shaped by Artificial Intelligence. Also, it encourages them to get deeper into the subject matter if they are interested in more technical careers.
Interested stakeholders can also turn to the more established Massive Open Online Courses (MOOCs) like edX, Udacity, Coursera, or Udemy to gain a more in-depth understanding of Artificial Intelligence and Machine Learning. Access to Education has been democratized and the opportunities to learn are endless. It takes however great willpower and motivation for people to sign up and more importantly finish these courses on their own. A good way to improve the odds of completing a course is by creating a study group with like minded friends or colleagues. Setting a common goal and helping each other to achieve the mutual objective is a recipe for success. To get started I recommend the following website: DIYGENIUS. Here you will find plenty of relevant information about the future of work and how to best prepare for it.
The future is not what it used to be. Let´s make the most of it and help shape this exciting era that is ahead of us. We need to engage in the discussion about Man versus Machine now and raise our voice to help actively shape the ethical principles that will guide the future development of this technology. To get this right we need to involve the broad population, get them trained and agree on a set of values and principles that will be the foundation on which future developments in AI will be built.Gabriele Zedlmayer
In the last years, technology has gradually become invisible and digital ubiquity is arising in our daily work and private lives. This is also true for artificial intelligence and its impact for companies to succeed in the digital age. Organizations must foster their digital readiness, which decides about their future business model and which encompasses a range of aspects: it comprises the capability of companies to obtain the benefits which arise from information technology, including their successful transformation into truly digital enterprises and using innovative technologies like artificial intelligence, and people’s individual preparedness to embrace and use the new digital technologies for their jobs. Although there is substantial evidence that digital readiness positively influences company outcome in the digital world and employees have to be ready, studies show, that the associated capabilities are only rarely in place. This goes along with a perceived lack of digitally skilled and experienced managers, who do not have enough knowledge about innovation and major digital trends and who are not yet able to fasten reaction speed and to foster an innovation culture of their firms, which is seen as one of the most important innovation barriers by many employees.
In times, where innovation decides about a company´s wealth and autonomous innovation is a future outlook, this matters even more: Possibly in the future roboters and machines will support innovation processes in fields like scouting, idea generation, but also in areas like innovation team set ups in form of performance predictions and emotion tracking. There might be people-roboter innovation teams collaborating to succeed. This implies even more, that companies have to be prepared and have to enlarge their digital readiness by far. Managers do play a major role in the course of this and new leadership skills are becoming a necessary precondition in the digital world. So what should managers do? In a nutshell, the author proposes three core measures to be taken to succeed: First, the advancing of the own digital readiness of managers matters, as leaders are perceived as role models for the employees.
Having digital knowledge – e.g. on important digital trend topics like blockchain, artificial intelligence or digital ubiquity – and digital skills on their own, and not leaving this over to digital experts, enables managers to better develop a digital strategy, rate digital innovation ideas, define the right problems to be solved and bring business forward in this respect or act as game changers in their industry branch. Dealing with ambidextry - exploiting core business and exploring new business models at the same time - requires digitally enabled mangers on a broader scale. Second, managers should foster life long learning of their employees and enable employees to become more digitally mature, according to the motto from “knowing it all” to “learning it all”. This needs a growth mindset, that empowers people to outgrow themselves. Third, on an organizational level, managers should foster shared beliefs and an open innovation culture. With this goes along, that management communication therefore has to be adjusted accordingly.
To sum up, artificial intelligence can be seen as a great chance for individuals and organizations as well, and managers do play an important role to make the best use out of it for their business to succeed. Nevertheless, in times of artificial intelligence also humans and their skills, that machines can´t learn – like creativity at the first place – will get relevant even more.Anne Gfrerer
We live in exciting times. Artificial Intelligence (AI) is fundamentally transforming the world with all its facets. Even if it has been around for a while in science and technology, aiming to create machines with some form of human intelligence, over time AI has become an inseparable part of our daily lives, personal as well as professional. Online searching engines, financial transactions, digital personal assistants, image and voice recognition are just a small selection of the most popular applications of AI today.
Unlike the current mainstream, i.e. in the media, communication and financial sectors just dealing with data, the AI of tomorrow will be more about perceptible presence, based on the fusion of contents. Based on current market research and own insights the main trends for 2019 clearly indicate the transition of data analytics towards augmented analytics, called also an analytics of behavior.
Due to the rapid development of human-centered platforms, social networks and AI applications in daily live the AI refocuses the way of consideration from the "object" (machine, computer) to the "subject" (human being). People's roles are getting more and more important. Furthermore, people are developing an "AI mindset" in direct communication with other people, but also with machines and computers. The term still sounds like a buzzword, but we're already linking our personal attitude to AI, the way we think, act or feel. It is also about our human skills, competences and experiences in dealing with AI, which belong together and are reciprocal.
To understand the matter of which a human being, a physical or an artificial thing consists and how they behave requires the analysis in context. A mash up of AI and business technologies, such as Internet of Things (IoT), Cyber-Physical Systems and Automation will begin to make a significant impact on AI market in 2019. Edge and Fog Computing, Mesh Wi-Fi, Beacons, Blockchain, 5G, Immersive Experience and Quantum Computing - the list of technological trendsetters for future AI is long. However, it is not the technologies that drive changes, but the acceptance, the way people perceive and use technology. Thus, it is already possible today to recognize relationships and interactions that can be symbolically captured in a four-dimensional "all-in-one" behavior space characterized by intelligence, immersion, infrastructure and real-time capability.
The boundary between "online and offline" disappears influencing the way people imagine reality in space and in time. Material and immaterial worlds merge. Real-time applications, supported by realistic visualization technologies make invisible phenomena visible and understandable to humans in order, for example, to realize new product features and functions. Numerous examples of the use of AI, such as intelligent voice assistants and in-store beacons, show that the mass markets will rely on technologies that are available, affordable and intuitive to use, enhancing experiences of customers and evaluating their data in context. At the same time, the immersion level of people's perceptions is increasing as both Bluetooth headsets and speakers and other peripherals such as VR/AR headsets, smart watches and glasses are becoming more prevalent.
Furthermore, it is also about digital business, education and qualification. As a result, prejudice, traditions and physical constraints (including availability and local presence) become less important. Networked thinking skills, with a sense for the big picture, are in demand as never before. Life is analogue, but communication is getting more and more digital. This trend offers unimaginable potential for new professions, qualifications and business models.
Today, companies from a very wide range of industries express their extreme commitment to bringing AI into the core of their business and plans for growth. The most important thing is to get rid of the stereotypes that are outdated and to look forward with the courage to disrupt. Due to the transition of AI to more behavioral analytics not just Silicon Valley companies are on the trend anymore. Indeed, companies driven by engineering innovations, i.e. Digital Twins, take the chances to create new AI markets making analytics to come alive, driving actions and delivering value.
The notion of a Digital Twin is now being widely adopted. It is rapidly becoming the technology of choice for virtualizing the physical and digital worlds. As versatile and powerful as AI may be the original purpose of the Digital Twin remains unchanged: to enable people to perceive realities, study problems more easily, get to the point, understand, decide and proceed pragmatically and rapidly. Digital Twins strengthen the “human front-end” of all we do, making it more dynamic, faster learning, and also highly interactive. Furthermore, they offer excellent opportunities to investigate the unexpected and discover the very best solutions – true to the motto “It is not the technology that changes the world but the way people use it”.
But, what is the Digital Twin exactly? Similar to the evolution of AI, the notion of Digital Twin began around 60 years ago, in the pioneering era of the space exploration. At that time, the US National Aeronautics and Space Administration (NASA) was grappling with the challenge of designing objects that could travel so far away they would be beyond the human ability to see, monitor or modify them directly. NASA's innovation was the “digital twin” of a physical system – a comprehensive digital double which people could use to operate, simulate and analyze an underlying system led by physics.
Fundamentally, the Digital Twin is a virtual representation, an embodiment of an asset of any type, material or non-material – including everything from power turbines, plants and buildings to services and maintenance. The Digital Twin is described by the structure and behavior of connected “things” generating real-time data. That data is stored usually in the cloud or edge and analyzed with relation to the running environment around it. It is then presented to users from different perspectives and in a variety of roles, so they can remotely understand its status, its history, its needs, and interact with it to do their jobs.
The interfaces to external systems and validation environments with consideration of all relevant resources and processes ensure high-level connectivity and are the key for success. For example, using the Digital Twin, it is possible to validate operational concepts for production systems in real-time, for manual as well as automatic operations, and for configuration via intuitive man-machine interfaces (e.g. web surface, haptic interaction devices). This makes it easier to take decisions based on up-to-date, transparent information. Thus, by merging real and virtual environments, intelligent commissioning of production can be used to generate forecasts based on real-time data from the shop floor.
How Digital Twins work? A ready-to-use solution at the Industry 4.0 Collaboration Lab at the Karlsruhe Institute of Technology (KIT), Germany, offers a good example. The use case of a Digital Twin of a milling machine used for process optimization and networking in virtual reality, while taking account of resource flows, demonstrates the practical advantages of the proposed solution by increasing productivity more than 20 percent. Systems which make it easier to gain a unique, deep knowledge of assets and their behaviors throughout the life cycle will pave the road to achieving new levels of optimization and business transformation. For example, we want the physical build to return data to its Digital Twin through sensors so the Digital Twin contains all the behavioral information we would have if we inspected the physical build itself.
According to the German Association for Information Technology, Telecommunications and New Media (BITKOM), Digital Twins in manufacturing industry will have a combined economic potential of more than € 78 bn by 2025. However, this potential can only be achieved if Digital Twins are implemented in a comprehensive and self-optimizing manner which enables them to adapt to future changes. Current studies show that mature and widespread implementation has not yet taken place. There are three main weak points to be discussed: model semantics of Digital Twins is mostly geometry driven, data analytics is aligned but not embedded into the model and simulation and user-interaction take place offline, due to the huge model complexity and the lack of computational power. To overcome current limitations, the following three conditions must be fulfilled: model semantics must be usage driven and adaptive for changes, analytics should be embedded into behavior and working in runtime, and the implementation should go along with experiments and experiences.
Implementing Digital Twins demands that we put real problems “into the sandpit“ of business units, think, try out, create “all-in-one“, apply emerging AI technologies playfully and quickly, test new solutions in runtime to gain experience fast and transform knowledge into actions and skills. The time to act is now! We invite you to join us in establishing “AI Twinning” as a trademark.Jivka Ovtcharova
Artificial Intelligence is one of the leading technologies of the fourth industrial revolution and it is already impacting our daily lives. 42.cx has recognized that and built a great team to play ahead of the game.Steve Rogers
The AI-42 Index reflects an enriching symbiosis of human intelligence and artificial intelligence. We are adding another layer - a smart layer - to something which is actually a commodity.Thomas Willomitzer
The commercialization of Artificial Intelligence is a fast-forward process and will change the way we do business. Our mission is to discover the most promising players in this field within the 42-AI Index.Martin Drexler