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Generative Artificial Intelligence as an Enabler of Organizational Ambidexterity in the Knowledge Economy Cover

Generative Artificial Intelligence as an Enabler of Organizational Ambidexterity in the Knowledge Economy

By: Sapan Tiwari,  Dharmam Buch and  Aditi Rao  
Open Access
|Mar 2026

Figures & Tables

Figure 1.

Generative AI and organizational ambidexterity framework Source: own processing

Illustrative examples of Generative AI applications in business workflows

Industry/SectorSpecific workflow/Process impactedType of GenAI impactConcrete example/benefit
Legal ServicesLegal document drafting, workflow automationAutomationDrafting time cut from 40 hours to minutes; saves up to 25 hours/case
HealthcareMedical appeal processingAutomationSaves 11,000 nursing hours; 99% approval rate for letters
ManufacturingStandard Operating Procedure (SOP) creationAutomationCreation time cut from 1 hour to 10 minutes for 1,000 SOPs
Financial ServicesCredit report generationAutomationUp to 25% time savings in report generation
GovernmentPolice report writingAutomation82% reduction in time officers spend on reports
Customer ServiceCustomer inquiries, virtual assistantsAutomationAutomates over 50% of interactions; handles millions of queries/month
Software DevelopmentCode generation, refactoring, debuggingAugmentationIncreases productivity by 10%; boosts delivery volume by 25%
MarketingContent drafting, personalized campaignsAugmentationDrafts copy for blogs, emails; real-time personalized content
ManagementReport, summary, projection generationAugmentationStreamlines administrative burdens; frees time for strategic analysis
Innovation/R&DNew product compound discoveryNew Process/InnovationReduces development time from days to minutes for new compounds
Customer EngagementHyper-personalized interactionsNew Process/InnovationEnables hyper-personalized campaigns at scale; proactive actions
Research & DevelopmentScientific problem-solving, data synthesisNew Process/InnovationProposes novel solutions; synthesizes medical images for training

Changes in job roles and required skills due to GenAI

Category of impactExamples of job rolesNature of change/impactKey skills affected/required
Fully Replaced RolesBill and Account Collectors, Data Entry Keyers, Word Processors and TypistsAutomation of routine data entry, document processing, and administrative tasks.Mundane/repetitive tasks (decreased), Technical ICT skills (decreased)
Partially Replaced/Augmented RolesCustomer Service Representatives, Computer Network Support SpecialistsAI handles common queries and initial troubleshooting; humans focus on complex, nuanced issues.Technical ICT skills (decreased for routine, increased for complex), Critical thinking (increased), Social skills (increased)
New/Enhanced RolesAI Ethics Specialist, AI Solutions Architect, AI TrainerOversees AI system development, ethical compliance, data analysis, and human-AI collaboration.AI literacy (new), Problem-solving (increased), Ethical reasoning (increased), User experience design (new)
DOI: https://doi.org/10.2478/mdke-2026-0003 | Journal eISSN: 2392-8042 | Journal ISSN: 2286-2668
Language: English
Page range: 40 - 53
Submitted on: Oct 27, 2025
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Accepted on: Feb 3, 2026
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Published on: Mar 23, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Sapan Tiwari, Dharmam Buch, Aditi Rao, published by Scoala Nationala de Studii Politice si Administrative
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.