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11. March 2019

Insights from AI-enabled Tech Foresight Summit

Did you miss the AI-enabled Tech Foresight Summit on February 20 in Berlin?

We hosted more than 60 participants, including renowned AI and foresight speakers, startup founders, innovation experts, heads of innovation and foresight departments from companies such as Intel, adidas, BASF, Daimler, SAP, etc.

AI enabled Tech Foresight Summit pictures

Here are some insights from each keynote presentation that we would like to share with you:

Knowledge Analytics for Technology & Innovation with Watson

Speaker: Dr. Marcus John, Senior Scientist, Fraunhofer INT

Combining years of experience in data-driven technology foresight at Fraunhofer INT, Dr. Marcus John and his team run the KATI project as a unique 360° technology scanning and monitoring service. Dr. John calls it a “science observatory”. KATI aims to unlock the vast amount of information available, including scientific publications, patents and internet sources for technology foresight. The software tool is developed based on IBM’s Watson and integrates many new features and significantly improves the analytics capabilities within the dedicated use case. The project is designed to explore the application of cognitive computing and machine learning in technology foresight. Dr. John explained how Fraunhofer INT makes use of their comprehensive graph database to scan more than 2 million scientific publications per year. The summit participants had the chance to take a deeper look into KATI during our open session in the afternoon.

AI-based Patent Valuation

Speaker: Dr. Tim Pohlmann, CEO, IPlytics GmbH

In his presentation, Tim talked about humans having valuable domain knowledge but not the capacity of searching a million documents in a few minutes. AI algorithms leverage human input to provide very fast output close to a human’s research that would take significantly more time. Deriving insights from multiple data sources is quite a resource consuming manual process for corporates, which spend a lot of time searching, understanding and updating even a single dataset.

Automated estimation of patent portfolio value is possible by using litigation, usage and interest data. Patent value indicators help corporates to process millions of documents efficiently. The summit participants had the chance to take a deeper look into the IPlytics platform during our open session in the afternoon.

Insights and Analytics at Intel: TrendScape

Speaker: John Miranda, Market Insights Manager, Intel Corporation

John’s presentation about “Global insights and analytics – TrendScape – Intel’s early warning system for emerging trends” provided great insights how Intel created a market and technology foresight system (based on ITONICS Trend Radar) and what the current challenges and benefits are. AI tools are mostly used to validate trend and technology data in terms of “is this trend picking up in speed/ relevance” or “why is this technology relevant to us”. Specifically connecting the dots to identify primary forces that shape computing over the horizon is where the value for strategy, business units, and planning is created.

Aside from the methodology and software tools used, John focused on how to drive action with leadership based on the generated insights. The presented engagement model and case example was a great starting point for discussion with the audience.


AI in Precision Medicine

Speaker: Prof. Dr. Magnus Boman, Professor in Intelligent Software Services, Royal Institute of Technology (KTH)

In previous decades, the healthcare focused on working out general solutions that treat the largest amount of patients with similar symptoms. Due to disruptive technologies and the rise of digital health solutions, healthcare has been going through sweeping changes. For example, artificial intelligence laid the foundations for precision medicine development.

Professor Boman explained that he teaches how to program learning machines and not machine learning. According to him, learning machines will allow breakthroughs in precision medicine. In the end, he added ‘’How do you learn to learn? If we have to foresight, we have to step on whatever we know until now”.

Leveraging Foresight, collaborative Innovation and customer Insights in an integrated Corporate Ecosystem

Dr. Frank Ruff, Senior Manager, PIONEERING NeXt, Daimler AG

According to Frank Ruff, we are in the 7th Wave of Innovation at the moment – the age of crowdsourcing and AI in innovation. The waves before were focusing on e. g. Technology Push and Market Pull, integrated business processes, the rise of VC or open innovation.

Dr. Ruff presented Daimler’s perspective on the evolution of corporate innovation ecosystems and how Daimler uses technology insights to provide transparency for long-term technological developments. Partnerships in the exploration of Quantum Computing are one outcome of this exercise.

Startups, as part of the external innovation ecosystem, matter to Daimler a lot. Dr. Ruff explained how the company runs an effective startup relationship management program called STARTUP AUTOBAHN aiming to find out over the course of 100 days corporate-startup pilot projects.

As a closing example Dr. Ruff mentioned how fast the Mercedes brand was able to integrate what3words into their cars.

Summing it up

The use of artificial intelligence might allow finding correlations between variables that humans fail to detect. Plus it will speed up and even automate the research phase and allow humans to focus on the interpretation and sense-making rather the pure research. This slide from John Miranda’s presentation supports the underlying idea:

AI-driven foresight has an immense potential to provide precise insights, covering political, technological, social, and economic aspects. Technology foresight helps industry experts understand how frontier technology will shape their industry and which technologies will soon become ubiquitous. The tipping point could be predicted with much higher precision, potential disruptions could be identified much earlier. This will shape decision making and strategic planning as well as managing innovation portfolios.

The correlation of successful organizations and their foresight maturity was proven e. g. by Rohrbeck and Kum. Therefore, the early experimentation with AI in foresight is crucial to stay ahead of the competition and lead by a sustainable strategy and innovation function.

Still, there is no best practice available at the moment, many startups are working on various approaches as well as established tech companies. We will continuously report on developments we detect and share our learnings and insights!