Generative AI as a Driver of Organizational Innovation and Knowledge Creation
DOI:
https://doi.org/10.64235/rdfE4s17Keywords:
generative AI, organisational innovation, knowledge creation, creativity, idea convergence, divergent thinkingAbstract
Generative AI (GenAI) tools produce ideas, drafts and analyses on demand, and organisations are adopting them to accelerate innovation. Whether they increase knowledge creation, the production of ideas that are novel, useful and non-redundant, is less clear: GenAI raises the quantity of ideas and lifts the novelty of less skilled users, but its outputs converge across users, which reduces the diversity on which organisational innovation depends. This paper models knowledge creation as the product of idea quantity, novelty, usefulness and non-redundancy, and compares three conditions in a simulation of 300 users with varying skill: unassisted ideation, GenAI-assisted ideation, and GenAI-assisted ideation with divergence prompts that direct the tool toward unconventional directions. GenAI assistance doubles idea quantity and raises novelty for low-skill users from 0.36 to 0.52, but convergence across users rises from 20% to 55%, so that net knowledge creation rises only from 1.33 to 1.50 and falls for high-skill users (2.12 to 1.97). Divergence prompting retains the quantity gain, raises novelty further and limits convergence to 35%, raising knowledge creation to 2.39 overall and benefiting both skill groups. The paper interprets the results through the knowledge-creation and creativity literatures, identifies convergence as the central risk of GenAI for innovation, and proposes practices for using GenAI to expand rather than homogenise an organisation’s idea space.
References
Chatrath, A. (2021). Bias, fairness, and ethics in artificial intelligence: A comprehensive study of algorithmic discrimination, transparency challenges, and governance frameworks. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 4(1). https://doi.org/10.15680/IJMRSET.2021.0401014
Aggarwal, A. (2020). Deployment of multi-factor authentication in cloud-based enterprise applications for preventing credential theft and unauthorized access through adaptive verification layers. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 3(8). https://doi.org/10.15680/IJMRSET.2020.0308009
Gupta, A. (2024). Cloud security in the era of big data: Protecting large-scale storage systems, ensuring query privacy, and safeguarding data lakes against emerging threats. International Journal of Innovative Research in Science, Engineering and Technology, 13(11). https://doi.org/10.15680/IJIRSET.2024.131100217
Khan, S. (2018). The role of zero-trust models in database security: Eliminating implicit trust and enforcing continuous verification in enterprise data access systems. International Journal of Research in Electronics and Computer Engineering, 6(1), 1622–1628.
Jain, Jaishree, Arpit Jain, Saurabh Kumar Srivastava, Chaman Verma, Maria Simona Raboaca, and Zoltán Illés. “Improved security of e-healthcare images using hybridized robust zero-watermarking and hyper-chaotic system along with RSA.” Mathematics 10, no. 7 (2022): 1071.
Ahuja, R. (2022). Application of static application security testing (SAST) in CI/CD pipelines for early detection of insecure coding practices through syntax tree analysis and custom rule sets. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2), 80–87. https://www.ijritcc.org/index.php/ijritcc/article/view/11922
Khan, S. (2017). The role of privacy-preserving techniques in database security: Secure multi-party computation, differential privacy, and homomorphic encryption. The Research Journal, 3(4), 29–35.
Jain, Arpit, Nageswara Rao Moparthi, A. Swathi, Yogesh Kumar Sharma, Nitin Mittal, Ahmed Alhussen, Zamil S. Alzamil, and MohdAnul Haq. “Deep Learning-Based Mask Identification System Using ResNet Transfer Learning Architecture.” Computer Systems Science & Engineering 48, no. 2 (2024): 341.
Khan, S. (2016). A study of data provenance and integrity in database security: Ensuring authenticity, non-repudiation, and accountability in data lifecycle management. International Journal of Research in Electronics and Computer Engineering, 4(3), 180–186.
Bhanushali, B. (2020). Enhancing alert investigation process with feedback loop to increase efficiently and model tuning. International Journal of Innovative Research in Computer and Communication Engineering, 8(8), 3366–3373. https://doi.org/10.15680/IJIRCCE.2020.0808100
Rangappa, A. S. (2023). An analytical study of role-based access control (RBAC) and attribute-based access control (ABAC) in database security for multi-tenant and cloud-based architectures. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 812–819. https://www.ijritcc.org/index.php/ijritcc/article/view/11943
Jadhav, P. V., Krishnan, S. B., Dey, R., & Chakrabarti, P. (2026). Combining deep learning and statistical models: LSTM-ARIMA ensemble for financial forecasting. IAENG International Journal of Computer Science, 53(1), 236–246. https://www.iaeng.org/IJCS/issues_v53/issue_1/IJCS_53_1_24.pdf
Ahuja, R. (2023). Implementation of AI-driven input validation in user interfaces for preventing injection attacks and ensuring data sanitation through adaptive filtering and pattern recognition. International Journal on Recent and Innovation Trends in Computing and Communication, 11(8), 884–891. https://www.ijritcc.org/index.php/ijritcc/article/view/11936
Devulapalli, N. (2024). The role of homomorphic encryption in database security: Enabling confidential query processing, secure data sharing, and privacy-preserving analytics. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 7(8), 14319–14326. https://doi.org/10.15680/IJMRSET.2024.0708082
Ahuja, R. (2023). The role of artificial intelligence and machine learning in DevSecOps: Leveraging predictive analytics, automated threat detection, and anomaly identification for secure software delivery pipelines. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2), 381–389. https://www.ijritcc.org/index.php/ijritcc/article/view/11946
Kumar, Ashok, and Arpit Jain. “Image smog restoration using oblique gradient profile prior and energy minimization.” Frontiers of Computer Science 15, no. 6 (2021): 156706.
Mahadasu, S. S. (2022). Cross-domain service assurance for private 5G networks using streaming telemetry and dependency-aware event correlation. International Journal of Data Science and IoT Management System, 1(3), 51–56. https://doi.org/10.64751/ijdim.2022.v1.n3.1290
Chatrath, A. (2020). DevSecOps for financial services: An in-depth study of secure CI/CD practices, regulatory compliance, and real-time threat monitoring in cloud-based FinTech applications. International Journal of Innovative Research in Science, Engineering and Technology, 9(11). https://doi.org/10.15680/IJIRSET.2020.0911098
Rangappa, A. S. (2024). Generative AI in human-machine collaboration: Exploring co-creation dynamics, shared agency, and the role of human oversight in AI-augmented creative and analytical tasks. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 13(4), 985–992. https://doi.org/10.15662/IJAREEIE.2024.1304077
Bhaskara Raju Rallabandi. (2022). SYNC-ADAPTIVE RESOURCE SCHEDULING IN PRIVATE 5G FOR TIME-CRITICAL APPLICATIONS. International Journal of Data Science and IoT Management System, 1(2), 40–45. https://doi.org/10.64751/ijdim.2022.v1.n2.pp40-45
Jain, A. (2024, December). Energy-Efficient Signal Processing Architectures for IoT Networks Design. In 2024 International Conference on Emerging Technologies and Innovation for Sustainability (EmergIN) (pp. 362–367). IEEE.
Anchala, S. (2019). Database security in e-governance systems: Protecting citizen records, ensuring transparency, and managing public trust in cloud-based platforms. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 2(11), 2268–2276. https://doi.org/10.15680/IJMRSET.2019.0211014
Kaur, M., AlZubi, A. A., Jain, A., Singh, D., Yadav, V., & Alkhayyat, A. (2023). DSCNet: deep skip connections-based dense network for ALL diagnosis using peripheral blood smear images. Diagnostics, 13(17), 2752.
Bhaskara Raju Rallabandi. (2023). CLOSED-LOOP DIGITAL-TWIN MANAGEMENT FOR HYBRID 5G-NTN NETWORKS. American Journal of Management and IOT Medical Computing, 2(3), 30–35. https://doi.org/10.64751/ajmimc.2023.v2.n3.pp30-35
Jain, J., & Jain, A. (2022). Securing e‐Healthcare Images Using an Efficient Image Encryption Model. Scientific Programming, 2022(1), 6438331.
Mahadasu, S. S. (2024). AI-native wireless digital twins for precision agriculture: Edge intelligence and predictive farm operations in 6G ecosystems. International Journal of Data Science and IoT Management System, 3(1), 65–72. https://doi.org/10.64751/ijdim.2024.v3.n1.1287
Gupta, A. (2022). The role of artificial intelligence in transforming healthcare delivery: A critical analysis of machine learning models, predictive diagnostics, and ethical challenges in medical decision-making. NeuroQuantology, 20(3), 1383–1399. https://doi.org/10.48047/nq.2022.20.3.NQ23005
Mahadasu, S. S. (2024). Closed-loop sustainability orchestration for energy-aware RAN, edge, and data-center workloads in 5G-Advanced networks. International Journal of Engineering Research and Science & Technology, 20(2), 1392–1398. https://doi.org/10.62643/ijerst.2024.v20.n2.4407
Jain, Arpit, Adesh Kumar, and Sanjeev Sharma. “Comparative design and analysis of mesh, torus and ring NoC.” Procedia Computer Science 48 (2015): 330–337.
Aggarwal, A. (2019). Application of secure Virtual Private Cloud (VPC) architectures in public cloud infrastructure for strengthening network isolation and segmenting trust zones through fine-tuned routing. International Journal of Multidisciplinary and Scientific Emerging Research, 7(1), 423–431. https://doi.org/10.15662/IJMSERH.2019.0701048
Kumar, S., Jain, A., & Moparthi, N. R. (2022). Enhanced method of object tracing using extended Kalman filter via binary search algorithm.
Mahajan, R., Kanabar, K., Dey, R., Jadhav, P. V., Khan, M., & Ghantasala, G. S. P. (2026). Exploring big tech vulnerabilities: Transparent blockchain harvesting. In A. K. Singh, S. Saxena, & A. K. Haghi (Eds.), Cybernetic shield: Securing the future of machine intelligence (pp. 167–174). CRC Press. https://doi.org/10.1201/9781003567585-15
Anchala, S. (2019). The evolution of DevSecOps in software supply chain security: Addressing dependencies, open-source vulnerabilities, and the prevention of software supply chain attacks. International Journal of Multidisciplinary and Scientific Emerging Research, 7(1), 415–422. https://doi.org/10.15662/IJMSERH.2019.0701047
Kumar, S., Sharma, K., Kumar, P. A., Jain, A., Bhagat, S. K., & Singh, P. (2024, September). An improved particle swarm approach for energy-aware location-aided routing in mobile ad-hoc network. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1119– 1124). IEEE.
Bhanushali, B. (2020). Effective sanctions screening and false positive identification. International Journal of Innovative Research in Science, Engineering and Technology, 9(4), 8306–8313. https://doi.org/10.15680/IJIRSET.2020.0904179
Dwivedi, D. (2023). The technical and ethical challenges of building safe agentic AI systems: Balancing autonomy, predictability, alignment, and human oversight in next-generation AI models. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11), 2024–2031. https://www.ijritcc.org/index.php/ijritcc/article/view/11928
Talasila, D. (2021). A risk-based framework for database security: Identifying, classifying, and prioritizing threats for adaptive security policy enforcement. International Journal on Recent and Innovation Trends in Computing and Communication, 9(1), 54–61. https://www.ijritcc.org/index.php/ijritcc/article/view/11919
Dwivedi, D. (2024). Deployment of AI-based CAPTCHA systems in web applications for preventing automated bot attacks and brute force attempts through adaptive human verification. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 7(7), 13529–13536. https://doi.org/10.15680/IJMRSET.2024.0707292
Talasila, D. (2020). Deployment of shift-left security practices in agile development for embedding security controls early in the lifecycle and reducing technical debt through dev-centric training. Turkish Online Journal of Qualitative Inquiry, 11(1), 643–651. https://doi.org/10.69980/jzqq0t93
Devulapalli, N. (2023). Database security and big data analytics: Protecting large-scale data warehouses, ensuring query privacy, and mitigating emerging threats in real-time analytics systems. International Journal on Recent and Innovation Trends in Computing and Communication, 11(7), 622–629. https://www.ijritcc.org/index.php/ijritcc/article/view/11939
Harshitha, G., Kumar, S., Rani, S., & Jain, A. (2021, November). Cotton disease detection based on deep learning techniques. In 4th Smart Cities Symposium (SCS 2021) (Vol. 2021, pp. 496–501). IET.
Gupta, A. (2024). Containerization, virtualization, and cloud security: Analyzing vulnerabilities in Kubernetes, Docker, and hypervisor-based architectures with mitigation strategies. International Journal of Advanced Research in Education and Technology, 11(3), 1322–1331. https://doi.org/10.15680/IJARETY.2024.1103067
Talasila, D. (2024). Adoption of data loss prevention strategies in SaaS platforms for safeguarding confidential information and preventing unauthorized transfers through real-time content inspection. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 7(7), 13537– 13545. https://doi.org/10.15680/IJMRSET.2024.0707293
Rangappa, A. S. (2022). The use of blockchain for auditable and tamper-proof database security logs: Enhancing transparency and trust in data access monitoring. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 254–261. https://www.ijritcc.org/index.php/ijritcc/article/view/11925
Chatrath, A. (2020). The role of policy-as-code in DevSecOps: Automating compliance, governance, and risk management in cloud-native and hybrid IT environments. International Journal of Innovative Research in Computer and Communication Engineering, 8(1). https://doi.org/10.15680/IJIRCCE.2020.0801020
Bhaskara Raju Rallabandi. (2024). Designing Ntn– Terrestrial 6g Experiments For Agriculture And Smart Grids. American Journal of Management and IOT Medical Computing, 3(3), 27–32. https://doi.org/10.64751/ajmimc.2024.v3.n3.pp27-32
Kanabar, K., Dey, R., Mahajan, R., Jadhav, P. V., Khan, M., & Karimullah, S. (2026). Comprehensive guide to blockchain technology: Ecosystems, implementation, governance, and innovations. In A. K. Singh, S. Saxena, & A. K. Haghi (Eds.), Cybernetic shield: Securing the future of machine intelligence (pp. 175–182). CRC Press. https://doi.org/10.1201/9781003567585-16
Bhanushali, B. (2020). The industry needs a validated model to justify the immense cost of migrating from manual, periodic KYC (know your customer) to automated. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 3(11), 1799–1805. https://doi.org/10.15680/IJMRSET.2020.0311009
Dwivedi, D. (2023). Integration of secure file upload mechanisms in user-facing applications for preventing malware injections and file-based exploits through content-type validation. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 768–775. https://www.ijritcc.org/index.php/ijritcc/article/view/11940
Aggarwal, A. (2026). Adoption of end-to-end encryption in cloud communication channels for ensuring data confidentiality and trustworthiness through secure protocol enforcement. Journal of Critical Reviews, 7(12), 5493–5499. https://doi.org/10.69980/jcr.v7:i12.13407
Anchala, S. (2020). Adoption of secure access service edge (SASE) in distributed enterprises for ensuring cloud application protection and network optimization through unified security frameworks. Turkish Online Journal of Qualitative Inquiry, 11(4), 2964–2973. https://doi.org/10.69980/60m26411
Mahadasu, S. S., & Rallabandi, B. R. (2023). Federated learning for privacy-preserving RAN optimization across multi-site enterprise 5G networks. International Journal of Engineering Science and Advanced Technology, 23(4), 53–57. https://doi.org/10.64771/ijesat.2023.v23.i04.pp3847
Devulapalli, N. (2023). Database security in disaster recovery and business continuity planning: Ensuring data availability, backup integrity, and secure failover mechanisms. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 820–827. https://www.ijritcc.org/index.php/ijritcc/article/view/11944
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
