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genioux Fact post by Fernando Machuca and ChatGPT
Introduction by Fernando and ChatGPT
Welcome to our latest genioux Fact post, "g-f(2)2665 AI and Innovation: Finding the Right Fit for Your Company." In the rapidly evolving g-f New World, where technological advancements and market dynamics are in constant flux, leveraging AI for innovation is a critical component of winning the g-f Transformation Game (g-f TG). This post delves into the strategic application of AI in the innovation process, highlighting when and how AI can be most effective for your company.
The g-f New World presents unprecedented challenges and opportunities, making it essential for companies to harness the power of AI to stay competitive. "g-f(2)2665 AI and Innovation: Finding the Right Fit for Your Company" offers valuable insights into how organizations can strategically deploy AI to drive meaningful innovation. By understanding the specific contexts in which AI excels, companies can enhance their innovation efforts, improve productivity, and maintain a competitive edge. Join us as we explore the key findings and practical applications of AI in the innovation landscape, ensuring your company is well-equipped to thrive in the g-f Transformation Game.
Introduction
In their insightful article "Can AI Help Your Company Innovate? It Depends," published by Harvard Business Review on July 25, 2024, Lynn Wu and Sam Ransbotham explore the nuanced role of artificial intelligence (AI) in driving corporate innovation. As companies strive to innovate quickly, cheaply, and productively, many wonder how AI can contribute to these efforts. Wu and Ransbotham delve into how AI can be a powerful tool for certain types of innovation while emphasizing that its effectiveness depends on how organizations deploy these tools. Through their research, they uncover key insights into the conditions under which AI can truly enhance innovation.
genioux GK Nugget
"AI can significantly enhance innovation by facilitating process improvements and the recombination of diverse technologies, but its effectiveness depends on the strategic application aligned with the company's innovation goals." — Fernando Machuca and ChatGPT, July 26, 2024
genioux Foundational Fact
The role of AI in innovation is highly contingent on the type of innovation a company is pursuing. AI excels in enhancing process improvements and fostering innovation through the recombination of diverse technological elements. However, its benefits are limited for incremental and radical innovations, highlighting the need for strategic application tailored to specific innovation objectives.
The 10 Most Relevant genioux Facts
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- Strategic Application: AI is most beneficial for process innovation and recombination of diverse technologies, rather than for incremental or radical innovation.
- Enhanced Productivity: Firms utilizing AI for diverse recombination see productivity boosts of 3 to 7% compared to those that do not.
- Patent Boost: Companies with dispersed existing knowledge using advanced AI capabilities can achieve approximately three more new patents annually.
- Data-Driven Decisions: AI helps manage vast amounts of information, enabling companies to overcome information overload and make more informed decisions.
- Recombination Success: AI aids in combining existing technological elements in new ways, leading to innovative products and solutions.
- Process Improvements: AI analytics complement process improvements by expanding the search space of existing knowledge to innovate new technologies.
- Contextual Adaptation: AI is effective in adapting products to changing business contexts, such as modifying materials for new market demands.
- Follow-Up Projects: While AI may not drive radical innovation directly, it can significantly enhance follow-up projects by leveraging initial breakthroughs.
- Human Creativity: Radical innovations often require human creativity and small data interpretation, areas where AI is less effective.
- Guarding Innovations: Companies should safeguard their innovations when using AI to prevent competitors from quickly building on or combining their advancements.
Conclusion
"Can AI Help Your Company Innovate? It Depends" by Lynn Wu and Sam Ransbotham provides a comprehensive analysis of AI's role in corporate innovation. The article underscores that AI can be a powerful tool for enhancing process improvements and driving innovation through the recombination of diverse technologies. However, its effectiveness is contingent on the strategic application aligned with specific innovation goals. Companies must understand the types of innovation AI can support and deploy these tools thoughtfully to realize their full potential. By doing so, organizations can navigate the complexities of modern innovation landscapes and achieve sustained competitive advantages.
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REFERENCES
The g-f GK Context
Lynn Wu and Sam Ransbotham, Can AI Help Your Company Innovate? It Depends, Harvard Business Review, July 25, 2024.
ABOUT THE AUTHORS
Lynn Wu is an associate professor at the Wharton School. She teaches and researches use and impact of emerging technologies on business.
Sam Ransbotham is a Professor of Business Analytics at the Boston College Carroll School of Management. He co-hosts the “Me, Myself, and AI” podcast.
Classical Summary of the Article
In their article "Can AI Help Your Company Innovate? It Depends," published in Harvard Business Review on July 25, 2024, Lynn Wu and Sam Ransbotham explore the role of artificial intelligence (AI) in driving corporate innovation. As businesses face the challenge of innovating quickly, efficiently, and productively, many look to AI as a potential solution. The authors investigate how AI can support innovation by conducting two studies: a survey of 331 firms focusing on process improvement and new technology development, and an archival analysis of patent data from over 2,000 publicly traded firms.
The findings suggest that AI is most effective in enhancing process innovation and facilitating the recombination of diverse technologies. Firms utilizing AI for these purposes see significant benefits, including productivity increases of 3 to 7% and approximately three additional new patents per year. AI helps manage information overload and supports decision-making by synthesizing vast amounts of data, which is particularly useful in complex and fast-changing environments.
However, the effectiveness of AI is contingent on the type of innovation being pursued. While AI excels in process improvements and diverse recombinations, its benefits are limited for incremental innovations and almost negligible for radical innovations. Radical innovations often require human creativity and the ability to interpret small data, areas where AI is less effective. Additionally, using AI for ill-suited problems can lead to wasted resources and potentially hurt firm performance.
Wu and Ransbotham conclude that AI is a powerful tool for certain types of innovation, but its success depends on strategic application. Companies should understand the specific innovation goals AI can support and deploy these tools thoughtfully to realize their full potential. By doing so, organizations can navigate the complexities of modern innovation landscapes and achieve sustained competitive advantages.
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Lynn Wu
Lynn Wu is an esteemed associate professor at the Wharton School¹²³⁴. She is known for her expertise in the use and impact of emerging technologies on business, which she imparts to MBA, undergraduate, and PhD students¹²³⁴.
Her research primarily examines how emerging information technologies, such as artificial intelligence and analytics, affect innovation, business strategy, and productivity¹²³⁴. Her work is divided into three streams:
- She studies how data analytics and artificial intelligence impact firm innovation, business strategy, labor outcomes, and productivity for both large firms and startups¹².
- She explores how enterprise social media and online platforms influence work performance, career trajectories, entrepreneurship success, and the formation of new types of biases that arise from using technologies¹².
- She leverages fine-grained nanodata available through online digital traces to predict economic indicators such as real estate trends, labor trends, and product adoption¹².
Lynn Wu's work has been published in economics, management, and computer science journals¹². Her research has been widely covered by media outlets, including NPR, the Wall Street Journal, Businessweek, New York Times, Forbes, and The Economist¹². She has received numerous awards such as Early Career awards from INFORMS and AIS, best paper awards from Information System Research, AIS, ICIS, HICSS, CHITA, and Kauffman¹². She has also won the Dean’s teaching award¹².
She holds undergraduate degrees in Finance and Computer Science, a master's degree in Computer Science, and a Ph.D. in Management Science, all from MIT¹². Prior to academia, she was a software engineer and a research scientist at MIT's AI lab and IBM¹². She has experiences working with a variety of firms in the technology industry (e.g., IBM, SAP, Google, Facebook), government agencies, and think tanks (e.g., the World Bank, the Russell Sage Foundation)¹². She has also consulted and advised several startups¹².
Source: Conversation with Copilot, 7/26/2024
(1) Lynn Wu – Operations, Information and Decisions Department. https://oid.wharton.upenn.edu/profile/wulynn/.
(2) Lynn Wu - Wharton Executive Education. https://executiveeducation.wharton.upenn.edu/faculty/lynn-wu/.
(3) Lynn Wu | Stanford HAI. https://hai.stanford.edu/people/lynn-wu.
(4) Lynn Wu, Instructor | Coursera. https://www.coursera.org/instructor/~89232929.
Sam Ransbotham
Sam Ransbotham is a distinguished Professor of Business Analytics at the Boston College Carroll School of Management¹². He is known for his expertise in the field of analytics, and he teaches courses such as "Analytics in Practice" and "Machine Learning and Artificial Intelligence"¹².
Ransbotham's research primarily focuses on how emerging information technologies affect innovation, business strategy, and productivity¹². His work has been published in prestigious academic journals and has been widely recognized in the field².
Before joining academia, Ransbotham founded a software company with a globally diverse client list, including the United Nations IAEA (Vienna), FAO (Rome), WHO (Geneva), and WMO (London)¹². He has also served as a senior editor at Information Systems Research, an associate editor at Management Science, and an academic contributing editor at MIT Sloan Management Review¹².
Ransbotham holds a bachelor’s degree in chemical engineering, an MBA, and a doctorate, all from the Georgia Institute of Technology¹²⁴. His contributions to the field have been recognized with several awards, including the INFORMS ISS Sandy Slaughter Early Career Award and the National Science Foundation CAREER Award².
In addition to his academic work, Ransbotham is also a guest editor for MIT Sloan Management Review’s Artificial Intelligence and Business Strategy Big Ideas initiative³⁴. He co-hosts the "Me, Myself, and AI" podcast about using artificial intelligence in business¹.
Ransbotham's work is not only influential in the academic world but also has a significant impact on business practices. His insights into the role of analytics in business strategy and innovation continue to shape the way organizations operate in the digital age¹².
Source: Conversation with Copilot, 7/26/2024
(1) Sam Ransbotham - Carroll School of Management - Boston College. https://www.bc.edu/bc-web/schools/carroll-school/faculty-research/faculty-directory/sam-ransbotham.html.
(2) Sam Ransbotham - CV. https://www.samransbotham.com/cv.
(3) Sam Ransbotham, Guest Editor - MIT Sloan Management Review. https://sloanreview.mit.edu/sam-ransbotham/.
(4) Sam Ransbotham - Speaking. https://www.samransbotham.com/speaking.
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