%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