%0 Journal Article %J Technology Innovation Management Review %D 2020 %T AI-Driven Digital Platform Innovation %A Sergey A. Yablonsky %K Advanced Analytics %K AI maturity %K AI value chain %K AI-driven platform innovation %K Artificial Intelligence (AI) %K big data %K enterprise platform %X Artificial Intelligence (AI) innovation becomes useful today when it enriches decision-making that is enhanced by applications of big data (BD), advanced analytics (AA), and some element of human interaction using digital platforms. This research aims to investigate the potential combination of AI, BD and AA for digital business platforms. In doing so, it develops a multi-dimensional AI-driven platform innovation framework with AI/BD/AA innovation value chain and related levels of AI maturity improvement. The framework can be used with a focus on the data-driven human-machine relationship and the application of AI at different levels of an AI-driven digital platform technology stack. %B Technology Innovation Management Review %I Talent First Network %C Ottawa %V 10 %P 4-15 %8 10/2020 %G eng %U timreview.ca/article/1392 %N 10 %1 St. Petersburg State University Sergey Yablonsky, PhD in computer science, is an Associate Professor at Graduate School of Management, St. Petersburg State University in St. Petersburg, Russia. Author of more than 200 publications. Co-creator of the Russian WordNet and the Russicon language processor and linguistic resources licensed by Adobe Systems Incorporated, Phoenix Int. (USA), Franklin Electronic Publishers (USA) etc. Engaged in 35 national and international research projects in Russia, and across Europe. Research interests include Digital Economy, Digital Business and Entrepreneurship; Multisided Platforms and Markets; Artificial Intelligence, Digital marketing; Big Data Governance; Computer linguistics and text mining; Semantic and Social Web. Courses taught: Data Governance (Bachelor Program); Digital Marketing & Digital Commerce (Bachelor programs); Digital Business (Master program); Smart Business Transformation in the Digital Age (CEMS Block Seminar); Multi-Sided Platforms and Innovation in a Global Era (CEMS Block Seminar); Digital Economy (EMBA). Visiting professor at WU (Vienna University of Economics and Business) in Austria, Stockholm Business School, Stockholm university in Sweden, Aalto University in Finland, Lappeenranta University of Technology in Finland, Hame University of Applied Sciences in Finland. %& 4 %R http://doi.org/10.22215/timreview/1392 %0 Journal Article %J Technology Innovation Management Review %D 2020 %T Integrated AI and Innovation Management: The Beginning of a Beautiful Friendship %A Nina Bozic Yams %A Valerie Richardson %A Galina Esther Shubina %A Sandor Albrecht %A Daniel Gillblad %K AI innovation %K AI maturity %K artificial intelligence %K IMS ISO 56002 %K Innovation management %K maturity model %X There is a growing consensus around the transformative and innovative power of Artificial Intelligence (AI) technology. AI will transform which products are launched and how new business models will be developed to support them. Despite this, little research exists today that systematically explores how AI will change and support various aspects of innovation management. To address this question, this article proposes a holistic, multi-dimensional AI maturity model that describes the essential conditions and capabilities necessary to integrate AI into current systems, and guides organisations on their journey to AI maturity. It explores how various elements of the innovation management system can be enabled by AI at different maturity stages. Two key experimentation stages are identified, 1) an initial stage that focuses on optimisation and incremental innovation, and 2) a higher maturity stage where AI becomes an enabler of radical innovation. We conclude that AI technologies can be applied to democratise and distribute innovation across organisations. %B Technology Innovation Management Review %I Talent First Network %C Ottawa %V 10 %P 5-18 %8 11/2020 %G eng %U timreview.ca/article/1399 %N 11 %1 Research Institutes of Sweden (RISE) Nina is a Senior Researcher in Innovation Management and the Future of Work at RISE. She has a PhD in Innovation Management and 16 years of experience working as an innovation enabler and explorer, both in companies and public sector organizations. After starting her career as a management consultant at Deloitte and building an entrepreneurship centre CEED Slovenia, she moved to Sweden where she continued her work as an innovation consultant and participatory action researcher, working with organizations, such as Nacka, Eskilstuna and Västerås municipalities, ABB, Electrolux, Ericsson, GodEl and others. In the last two years she has been researching the future of work, and how we can integrate innovation management with other disciplines, such as AI, new models of organizing, and future studies to prepare organizations for the future in a more holistic way. %2 Gradient Descent Valerie is an AI Strategist & Partner at Gradient Descent. She is an experienced leader and advisor in digital disruption and transformation with over 20 years at Google and General Electric, helping companies in multiple industries solve strategic and operational problems in an integrated way across multiple technology domains. Her expertise includes defining digital strategies and developing digital operating models with a focus on providing practical solutions to complex technology challenges for executives. She has a specific interest in emergent technologies, including AI and IoT. Valerie most recently led a digital division of General Electric, advising large industrial operations on how to implement cloud-based enterprise IoT software, data analytics, machine learning and AI to increase productivity, reduce costs and improve competitiveness. %3 Gradient Descent Galina is an AI Technologist & Partner at Gradient Descent. She spent 16 years in the tech industry, over a decade of it at Google as a software engineer, data scientist and manager working on everything from ML-based advertising products to highly scalable distributed systems (four years in Silicon Valley). She spent the last 6 years working on AI strategy: alternating between building her own data and AI teams and strategy consulting on how to integrate data and AI into companies. In her last corporate job, she built the software and AI team for the electrical battery start-up, Northvolt. She is the founder of Women in Data Science - Sweden, a community of 700+ women in the field of data science, machine learning, AI and data analytics. %4 Research Institute of Sweden (RISE) & WALP Sandor, PhD, is a community ecosystem builder and change driver. He is passionate about innovation and technology incubation. Currently, he is at the Knut and Alice Wallenberg Foundation and RISE Computer Science, working with people that explore new ways of connecting human beings, industries and technologies, all in the pursuit of making it more secure and enjoyable to work and live in a sustainable world. He worked at Ericsson for twenty years in Hungary and Sweden as a leader in product development and corporate research. He was the founder and head of Ericsson Garage, Ericsson’s global innovation and incubation platform. He received his Master of Science in Electrical Engineering from Budapest University of Technology and Economics in 1993, and his PhD from the same institution in 2004. He also holds a Master of Applied Science from the University of British Columbia in Canada and a Master of Business Administration from Central European University Business School, Budapest, Hungary. %# Research Institutes of Sweden (RISE) and AI Sweden Daniel is Director of AI Research at RISE, Research Institutes of Sweden and co-director for Scientific Vision of AI Sweden. He has a background in AI, machine learning, data analytics and their practical applications, and has for many years been working with digital- and research strategies in industry and academia. He holds a PhD in Machine Learning and a MSc in Electrical Engineering, both from KTH, Royal Institute of Technology in Stockholm, and has lead research projects, groups and laboratories for almost 15 years. Daniel is an appointed member of the Swedish government advisory board on Digitalization, and has initiated, coordinated and co-edited the Swedish AI agenda. %& 5 %R http://doi.org/10.22215/timreview/1399 %0 Journal Article %J Technology Innovation Management Review %D 2019 %T Multidimensional Data-Driven Artificial Intelligence Innovation %A Sergey A. Yablonsky %K Advanced Analytics %K AI maturity %K AI value chain %K Artificial Intelligence (AI) %K big data %K enterprise platform %K innovation %X This is a critical time for the development and adoption of Artificial Intelligence (AI). The field has existed since the 1950s and is only now emerging as viable for commercial markets. Many enterprises are placing bets on AI that will determine their future. Today AI innovation becomes useful when it enriches decision-making that is enhanced by applying Big Data (BD) and Advanced Analytics (AA), with some element of human interaction using digital platforms. This research investigates an opportunity for cross-fertilization between AI, BD, and AA with related disciplines. The paper aims to investigate the potential relationship of AI, BD, and AA with digital business platforms. In doing so, it develops a multidimensional BD-driven AI innovation taxonomy framework with an AA/BD/AA innovation value chain, related levels of BD, and analytics maturity improvement. This framework can be used with a focus on data-driven human-machine relationships, and applying AI at different levels of data driven automation maturity. %B Technology Innovation Management Review %I Talent First Network %C Ottawa %V 9 %P 16-28 %8 12/2019 %G eng %U timreview.ca/article/1288 %N 12 %1 St. Petersburg State University Sergey Yablonsky, PhD in computer science, is an Associate Professor at the Graduate School of Management, St. Petersburg State University in St. Petersburg, Russia. Author of more than 200+ publications. Co-creator of the Russian WordNet and the Russicon language processor, and linguistic resources licensed by Adobe Systems Incorporated, Phoenix Int. (USA), Franklin Electronic Publishers (USA) etc. Engaged in 35 national and international research projects in Russia, and across Europe. Research interests include Digital Economy, Digital Business and Entrepreneurship; Multisided Platforms and Markets; Artificial Intelligence, Digital marketing; Big Data Governance; Computer linguistics and text mining; Semantic and Social Web. Courses taught: Data Governance (Bachelor Program); Digital marketing (Bachelor Program); Digital Commerce (Bachelor Program); Digital Business (Master Program); Smart Business Transformation in the Digital Age (CEMS Block Seminar); Multi-Sided Platforms and Innovation in a Global Era (CEMS Block Seminar); Digital Economy (EMBA). Visiting professor at WU (Vienna University of Economics and Business) in Austria, Stockholm Business School, Stockholm university in Sweden, Aalto University in Finland, Lappeenranta University of Technology in Finland, Hame University of Applied Sciences in Finland. %& 16 %R http://doi.org/10.22215/timreview/1288