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How can the innovation process be made more efficient and effective through the integration of ml-based artificial intelligence? 

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Best insight from top research papers

The integration of machine learning-based artificial intelligence (AI) can significantly enhance the efficiency and effectiveness of the innovation process. AI, particularly through deep learning methods, serves as a general-purpose method of invention, reshaping the innovation landscape by emphasizing application-oriented learning research . AI also accelerates knowledge creation in knowledge management processes, introducing new technologies and theories while raising social and ethical considerations . Furthermore, AI-based data mining models enable firms to spot emerging trends with minimal manual effort, providing early warnings for technology and innovation management . By leveraging AI subsets like learning and speech recognition, innovation managers can address challenges such as individualized solutions and shorter technology life cycles, optimizing various tasks within the innovation process . Overall, AI integration offers a promising avenue to streamline innovation processes and drive competitive advantage.

Answers from top 5 papers

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Papers (5)Insight
Journal Article•DOI
Artificial Intelligence in Innovation: How to Spot Emerging Trends and Technologies
01 Apr 2022-IEEE Transactions on Engineering Management
20 Citations
The integration of ML-based AI in innovation processes enhances efficiency by automating trend spotting, data analysis, and updating, leading to early identification of emerging technologies for strategic advantage.
Proceedings Article•DOI
Boosting Innovation by Artificial Intelligence (AI): Effects and Potentials of AI in the Process of Innovating
01 Aug 2022
By utilizing subsets of AI like learning and speech recognition, innovation managers can enhance efficiency in various phases of the innovation process, as outlined in the study.
Open access•Journal Article•DOI
The Impact of Artificial Intelligence on Innovation
Miss. Tehreen Khot, Mr. Shailesh Sutar 
30 Jan 2023-International Journal of Advanced Research in Science, Communication and Technology
1 Citations
The integration of ML-based artificial intelligence can enhance the innovation process by enabling the use of improved prediction algorithms and large datasets, leading to more efficient and effective research.
Book Chapter•DOI
Artificial Intelligence-Enabled Knowledge Management
28 Mar 2022
ML-based AI integration accelerates knowledge creation in KM, enhancing innovation efficiency. It introduces social and ethical considerations, driving new phenomena, technologies, and theories in KM processes.
Proceedings Article•DOI
Boosting Innovation by Artificial Intelligence (AI): Effects and Potentials of AI in the Process of Innovating
Lukas Keicher, Antonino Ardilio, G. Nawroth 
01 Aug 2022
By utilizing subsets of AI like learning and speech recognition, innovation managers can enhance efficiency and effectiveness in various phases of the innovation process, as outlined in the study.

Related Questions

How does the implementation of AI impact organizational innovation?5 answersThe implementation of AI significantly impacts organizational innovation by serving as a versatile "method of invention" that reshapes the innovation process and R&D organization. AI's introduction leads to sustainable development, affecting economic, social, and political aspects, emphasizing its importance for organizational growth and profitability. Businesses, both established and startups, are increasingly leveraging AI for improved efficiency, marketing strategies, and global market presence, with a focus on big data utilization and innovative business models. The shift towards AI-driven research and the acquisition of large datasets and algorithms create a competitive landscape, driving organizations to master this new method of research for commercial success. Policies promoting transparency and data sharing between public and private entities are seen as essential for enhancing research productivity and fostering innovation-oriented competition in the future.
What factors influence the integration of AI into innovative products or services?5 answersThe integration of AI into innovative products or services is influenced by various factors identified in the research papers. Factors such as trust-building, transparency, explainability, and certification play a crucial role in increasing overall trust in AI products. Additionally, the availability of resources, relative advantage, top management support, and AI strategic alignment positively influence the intention to adopt AI-based technologies at the organizational level. Understanding the concept of AI and the level of AI investment are identified as critical success factors for integrating AI with sustainable frugal innovation, which can enhance business competitiveness sustainably during disruptions. Moreover, consumer perceptions of AI design, including curiosity and willingness to pay, also impact the integration of AI into products, with high consumer knowledge attenuating curiosity regarding AI design.
What is the role of AI in innovation?5 answersAI plays a significant role in innovation by serving as both an originator and facilitator of innovation. It has the potential to transform various sectors and industries, such as higher education, fashion, and the arts, by enabling innovative solutions and advancements. AI can be used in different ways, including as a technology push, market pull, and contributor to new product development, thereby enhancing the traditional innovation process. The use of AI technologies is associated with higher product and process innovation results, particularly for world-first innovation, and applying AI broadly increases innovation output. In the Front End of Innovation (FEI), AI can support managers and play a key role in identifying opportunities, analyzing opportunities, and generating and enriching ideas. However, the ethical behavior of managers, enforcement of laws and regulations, education, and international cooperation are crucial for harnessing the benefits of AI and addressing its challenges.
How does the implementation of AI impact the efficiency and effectiveness of technical knowledge management processes?4 answersThe implementation of AI has a significant impact on the efficiency and effectiveness of technical knowledge management processes. AI can fill the gaps in current procedures and transform how knowledge is handled. It can improve the efficiency of knowledge creation and accelerate the KM process through the introduction of algorithms. AI-based systems can optimize task assignment, enlarge the team knowledge base, and support the process with data-driven approaches. Additionally, AI technology in knowledge management systems, such as knowledge-based expert systems, neural networks, and case-based reasoning systems, can improve the efficiency of knowledge management and provide exploration ideas for AI system research. Overall, AI enhances the efficiency and effectiveness of technical knowledge management processes by leveraging advanced algorithms, optimizing task assignment, and improving the overall knowledge management system.
How does AI integration influence employees' innovation?5 answersAI integration in the workplace can have both positive and negative influences on employees' innovation. On one hand, AI can enhance HR functions, attract and motivate employees, and contribute to a better work environment, thus potentially improving innovation. On the other hand, negative perceptions of AI taking over jobs can lead to job insecurity and psychological distress, which in turn can influence employees' career exploration behaviors and potentially hinder innovation. Additionally, employees' pre-adoptive appraisals of AI, based on their own knowledge and personal use, can influence their attitudes and behavioral responses towards AI, which can impact an organization's ability to leverage AI successfully. Therefore, organizations need to effectively communicate with employees about AI integration, address their concerns, and create a culture of trust and commitment to ensure that AI is seen as a tool for innovation rather than a threat.
What would be the impact of AI on Innovation management and Innovation process?5 answersAI has the potential to significantly impact innovation management and the innovation process. It can serve as a facilitator and originator of innovation, transforming the traditional innovation process and the front end of innovation perspective. Easy-to-use generative AI, such as large language models, can augment the early phases of innovation, including exploration, ideation, and digital prototyping. AI can enable new opportunities for innovation management and reshape innovation practice in organizations. Successful AI innovation management involves building ecosystems that are fruitful, cutting-edge, and sustainable. Additionally, AI technologies, such as robotics, big data, and business analytics, can lead to new forms of human-machine interaction and organizational management improvement. Overall, AI has the potential to enhance efficiency, decision-making processes, and organizational performance in innovation management.

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