Citation:

Debashis Patra, Ambar Nath Saha , 2026. "Preparing the Enterprise for AI-Driven Software Development: A Readiness Framework for Organizational Transformation", ESP Journal of Engineering & Technology Advancements  6(2): 30-36.

Abstract:

The whole human race is scurrying towards introducing the Artificial Intelligence in their work streams and the software development companies are on the frontline. However, in practice, the majority of software development organizations are finding it challenging to get beyond small AI experiments(1), and they are finding themselves using AI as a code assistant or business advisor. The cause is not on the technology itself but organizational issues like skills deficiency, ineffective processes, poor governance and resistance to change. In this paper, we put forward the Enterprise AI Coding Readiness Framework (EACRF), which assists companies to determine their readiness to embrace AI in their software development lifecycle. The framework primarily examines five crucial dimensions namely Infrastructure, Skills, Processes, Governance as well as Culture. It also outlines a realistic three-step adoption process, which begins with AI-assisted development, proceeds to AI-enhanced processes, and ultimately to AI-first model.

References:

[1] Ambar Nath Saha, Debashis Patra, 2026. "AI-First Software Development Lifecycle: An Agent-Driven Framework for Autonomous Planning, Coding, Testing, and Deployment", ESP Journal of Engineering & Technology Advancements 6(1): 131-139.

[2] M. Chen, J. Tworek, H. Jun, Q. Yuan, H. Pinto, J. Kaplan, H. Edwards, Y. Burda, and N. Joseph, Evaluating Large Language Models Trained on Code, arXiv preprint arXiv:2107.03374. 1(1) (2021) 1-34.

[3] N. Forsgren, J. Humble, and G. Kim, Accelerate: The Science of Lean Software and DevOps, IT Revolution Press, Portland, USA. 1(1) (2018) 1-288.

[4] E. Rogers, Diffusion of Innovations, 5th edition, Free Press, New York, USA. 5(1) (2003) 1-576.

[5] L. Tornatzky, M. Fleischer, and A. Chakrabarti, The Processes of Technological Innovation, Lexington Books, Lexington, USA. 1(1) (1990) 1-298.

[6] T. Fountaine, B. McCarthy, and T. Saleh, Building the AI-Powered Organization, Harvard Business Review. 97(4) (2019) 62-73.

[7] P. Vaithilingam, T. Zhang, and E. Glassman, Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models, ACM CHI Conference on Human Factors in Computing Systems. 1(1) (2022) 1-7.

[8] A. Ziegler, E. Kalliamvakou, X. Li, A. Rice, D. Rifkin, S. Simister, G. Sittampalam, and E. Aftandilian, Productivity Assessment of Neural Code Completion, Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming. 1(1) (2022) 21-29.

[9] J. Kotter, Leading Change, Harvard Business Review Press, Boston, USA. 1(1) (2012) 1-208.

[10] G. Westerman, D. Bonnet, and A. McAfee, Leading Digital: Turning Technology into Business Transformation, Harvard Business Review Press, Boston, USA. 1(1) (2014) 1-292.

[11] J. Humble and D. Farley, Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation, Addison-Wesley Professional, Boston, USA. 1(1) (2010) 1-512.

[12] E. Brynjolfsson and A. McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, W. W. Norton, New York, USA. 1(1) (2014) 1-336.

[13] A. Bacchelli and C. Bird, Expectations, Outcomes, and Challenges of Modern Code Review, IEEE International Conference on Software Engineering. 1(1) (2013) 712-721.

[14] Y. Jia and M. Harman, An Analysis and Survey of the Development of Mutation Testing, IEEE Transactions on Software Engineering. 37(5) (2011) 649-678.

[15] D. Anderson, Kanban: Successful Evolutionary Change for Your Technology Business, Blue Hole Press, Sequim, USA. 1(1) (2010) 1-278.

[16] European Parliament, EU Artificial Intelligence Act, Official Journal of the European Union. 1(1) (2024) 1-144.

[17] US Copyright Office, Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, Federal Register. 88(51) (2023) 16190-16194.

[18] Financial Industry Regulatory Authority (FINRA), Report on Artificial Intelligence in the Securities Industry, FINRA Report. 1(1) (2024) 1-30.

[19] G. Kim, J. Humble, P. Debois, and J. Willis, The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations, IT Revolution Press, Portland, USA. 2(1) (2021) 1-480.

[20] E. Schein, Organizational Culture and Leadership, 5th edition, Jossey-Bass, San Francisco, USA. 5(1) (2017) 1-416.

Keywords:

AI-driven software development, enterprise AI readiness, organizational transformation, digital transformation strategy, AI adoption framework, intelligent automation, AI governance, executive alignment, change management, strategic roadmap, business-IT alignment