by Oliver Gottfried
Funding is one of the most crucial criteria for AI-driven start-ups to realize their business ideas. Nevertheless, the German Venture Capital market is in contrast to the US and China still developing. Therefore, it is rather difficult to receive Venture Capital funding for German AI start-ups.
The second Transatlantic AI eXchange event on June 22nd 2021 covered this topic by analysing & debating the challenges and opportunities of Venture Capital funding for AI start-ups in the US and Germany. Renowned experts from the VC industry (i.e. Robert Bosch Venture Capital, M12, B Capital) as well as successful entrepreneurs joined the webinar session to shed light on this topic.
Yvonne Lutsch, Investment Principal from Robert Bosch Venture Capital (RBVC) stated that RBVC has about 50 investments in their active portfolio, with in total 700 million USD AUM and furthermore is currently raising another fund with a target size of about 300 million USD. When it comes to investing in start-ups, Yvonne suggested that German entrepreneurs should be more bullish and think big as founders in the US do.
Samir Kumar, GM and Managing Director from M12 mentioned that the core of M12 is enterprise SAAS and close to half of their portfolio companies have a strong AI component. He also pointed out that M12 is looking to do more deals in Germany with particular focus on AI driven companies. In terms of investment criteria Samir emphasized that the team is crucial and that the best founders demonstrate a level of self-awareness where they can complement their team.
Rashmi Gopinath, General Partner at B Capital highlighted that AI has been one of the underlying pinnings of B Capitals Enterprise Investment. In regard to investment criteria Rashmi emphasized that growth margins are very important.
Mark Maloney, Consul at the US Consulate General in Hamburg argued that the US State Department is paying a lot of attention to the AI market and that currently German AI companies are undervalued compared to US AI companies. These dynamics illustrate that there is opportunity in the AI field in Europe and particularly in Germany.
Cyriac Roeding, CEO & Co-Founder of Earli inc., is convinced that exclusive access to data is only a short-term advantage and is not the future of AI. According to Cyriac, the right way to build an AI driven company is to create a concept that generates more and more data with an increasing amount of users. Finally, building a complementary team is of major importance to ensure the success of the company.
Ragnar Kruse, the co-founder of AI.HAMBURG and AI.FUND complemented this by clearly outlining the importance for German AI startups to go international to achieve a reasonable growth rate.
German AI start-ups should take these suggestions into consideration in order to increase their chances to secure sufficient funding for their business operations. The discussion outlined that there are great chances for German AI startups to obtain funding and become global players when they keep certain factors in mind.
View the entire event here: Transatlantic AI eXchange Event Video Archive
Decision points in building an AI-centered organization
by Tobias Straube
The COVID-19 pandemic has triggered a digital transformation at light speed, with AI increasingly taking center stage. According to some estimates, AI is promising to add US$ 4.3 trillion in value to businesses worldwide until 2025.1 And yet, while the potential of AI is widely acknowledged, only half of respondents in a global survey said their organizations have adopted AI in at least one function.2 Other studies suggest that the contrast is even greater in Germany. Although 79% of companies in Germany now consider AI to be very important or critical to their success,3 very few are using AI – 8% to be exact.4 Barriers to higher adoption rates are related to lack of workforce skills, availability of data, identifying and understanding use cases, privacy and cybersecurity implications, and defining vendor strategies.5 And those companies that manage to successfully develop pilots and demonstrate how the use of artificial intelligence will improve their business, often struggle to get beyond the proof of concept stage.6
Meanwhile, the consideration and study of AI ethics, long the subject of discussion in international academic bodies and think tanks, is increasingly finding its way onto the agendas of board rooms. This is not only due to compliance concerns but also strategy-related questions around the company’s values and market positioning in the context of AI. While AI is becoming increasingly important, trust in the digital economy is dwindling. Therefore, the responsible and truly human centred use of AI becomes more important than ever. This is exemplified by the competition between the business models of Apple and Google or Facebook and LinkedIn. On the one hand we see a business model that charges for access to its services in exchange for privacy and the responsible use of tech – think of Apple’s iPhone or LinkedIn’s premium account, and on the other a business model that offers things for free and makes other companies pay for access to their product: The consumer’s behavioural data, see Google or Facebook.
All of this shows that companies that want to get serious about AI need to do more than upgrade their IT departments with data scientists or buy turnkey AI solutions. Harnessing the potential of AI means embarking on a transformation process towards AI-centric organizations. This process involves balancing business and product innovation, aligning business strategies with technology strategies, creating governance regimes, recruiting and developing staff, investing in data availability, accessibility and quality, rethinking the company’s IT architecture and much more.
Join the Show About Strategic decision points for AI in Business w/ Sanjay Srivastava, Chief digital officer at Genpact.
*This show will be post-poned. Please watch this space for an update*
Do you want to find out how to make smart decisions about the best use of AI in your business? Then join the show on (the show has bee post-poned. New date will be announced shortly). The show will be in cooperation with Blockchance Live and we will stream live on YouTube and LinkedIn Live. Be part of the discussion by sending us your questions via Telegram or in the live chat. Find out more about the event here.
AI is an advantageous technology playing an increasingly major role in our community. Especially in the focus areas, such as healthcare, agriculture, mobility, and climate change AI has turned out to be very beneficial. Moreover, the AI bus cannot be driven without its fuel called data. Concerns about the distribution of data are rising for ethical reasons on the consumer’s side and because of its sub-optimal allocation amongst participants who want to create digital value. Prof. Olaf Groth from Cambrian LLC will discuss how the future of data marketplaces will look like, how AI will use data in the future, and how this affects data protection and the monetization of your data.
About 90% of 1,000 consumers surveyed in the U.S. think it is entirely unethical for their data to be shared without consent. A study by Insights Network found that 79% of consumers said they want compensation when their data is shared. Firstly it would be interesting to know the actual value of our data. When asked about the price internet users put on their “loss of privacy”, they ascribe $36 to their identifiable data. The truth may seem rather sobering. Data brokers trade general information about a person such as age, gender, and GPS location for about $0.0005 per person. Meanwhile, entrepreneurs are identifying a growing number of business cases for data marketplaces to bridge the gap between the actual and assigned value of data. Such data marketplaces could be online businesses or platforms where users can purchase data sets or gain access to real-time data streams. This innovation would tap into a massive revenue opportunity.
Research from Stanford University suggests that the allocation of data in today’s digital economy is not optimal. With only a few large platforms having access to meaningful data pools, non-digital platforms and smaller actors are limited in their ability to participate in digital value creation. Some estimates indicate that 99.5 percent of the data we produce is not accessible as it remains in organizational, application, or industry silos. Therefore, while trust in the digital economy is deteriorating, the inaccessibility of data limits human and economic growth. With data marketplaces, all users could gain access to valuable data for prices that are fair for all parties, leveraging the utilization of AI. There also are other approaches to improve the accessibility of data, such as data taxes or dividends to share the value of data more evenly between those that create and those that use data. Moreover, Jaron Lanier from Microsoft has championed so-called data unions that would negotiate the value of data on behalf of the data creators. In our show, Prof. Olaf Groth will give his assessment of the advantages and disadvantages of data marketplaces in comparison to open data approaches, data unions, or data dividends.
Olaf has 25 years of experience as an executive and adviser building strategies, capabilities, programs, and ventures across over 35 countries with multinationals (e.g. AirTouch, Boeing, Chevron, Qualcomm, Q-Cells, Vodafone, etc.), consultancies, startups, VCs, foundations, governments, and academia. He is the founding CEO of advisory think tank Cambrian Futures and concept development firm Cambrian Designs. He serves as Professor Of Practice for strategy, innovation, economics & futures at Hult International Business School, where he teaches across campuses in the US, Europe, Middle East, and China. He is a member of the Global Expert Network at the World Economic Forum for the 4th industrial revolution and positive AI economy futures, Visiting Scholar at UC Berkeley’s Roundtable on the International Economy (BRIE) and its program Working with Intelligent Tools & Systems (WITS). Olaf also served on the Innovation Policy Committee for the Biden/Harris campaign. He is co-author of the AI book Solomon’s Code: Humanity in a World of Thinking Machines with Dr Mark Nitzberg, and of the prospectively forthcoming book The Great Remobilization: Designing A Smarter Future with Drs. Mark Esposito and Terence Tse. All in all, Olaf is an absolute expert in his space and a real enrichment for our next BLOCKCHANCE Online LIVE show.
Join the Show About Data Marketplaces & The Future of AI w/ Prof. Olaf Groth
Do you want to find out what the future of AI and data marketplaces will look like? Then join the show on April 28, 2021, starting at 5 pm (CEST) / 3 pm (UTC). The show will be in cooperation with AI.Hamburg and we will stream live on YouTube. Be part of the discussion by sending us your questions via Telegram or in the live chat. Notice the show by adding it to your calendar.