This presentation is open to all, including non-INCOSE members.
(* See the Presentation Slides and Recorded Video!)
Please join us on Wednesday, 25 June, 2025, for a HYBRID presentation on the application of a systems engineering maturity and cost modeling framework for generative artificial intelligence (GenAI)!
Please note: This presentation will take place at G2-OPS, Inc. in Kearny Mesa. Due to government contracting regulations, in-person attendance is limited to U.S. citizens only. However, non-U.S. citizens are invited to join us virtually!
MAIN INFORMATION
When: Weds, 25 June, 2025, from 5:45-7:00pm (presentation starts at 6 pm).
Where: G2-OPS, Inc. conference room (3rd floor), 8787 Complex Dr #310, San Diego, CA 92123. (Google Maps). Parking is free.
Cost: free! There will be an optional dinner with soft drinks, priced at $5 INCOSE members and students, $10 non-members. Please RSVP
Teleconference: remote attendees can join using the Zoom information below (Important – INCOSE now requires a passcode in addition to the waiting room. The code is also listed below.
Zoom: https://incose-org.zoom.us/j/87436486602?pwd=XtBmAD9UeEZcZv5UkTipBnTBlQPzKp.1
Meeting ID: 874 3648 6602
Passcode: 132956
Telephone: (669) 444-9171
(codes already listed above)
SYNOPSIS
Generative Artificial Intelligence (GenAI) is rapidly transforming systems engineering processes by automating tasks, generating architectural and design alternatives, supporting tradeoff analysis, implementation, testing, enhancing decision-making, and more. This presentation introduces an integrated maturity and cost modeling framework to guide the strategic adoption of GenAI within SE. The framework is being developed through collaboration between the Naval Postgraduate School and the Naval Information Warfare Center (NIWC), which is contributing empirical data on cost and quality impacts of GenAI use.
The model defines five maturity levels with key practices for hardware and infrastructure investment, knowledge integration and data management, LLM customization and fine-tuning, LLM retraining, and personnel training. It extends the Constructive Systems Engineering Cost Model (COSYSMO) for estimating project costs with a new cost factor for AI usage.
By understanding these maturity levels and their associated cost implications, organizations can formulate effective strategies to leverage GenAI, drive continuous improvement, reduce costs, and align with technological advancements.
This harmonized maturity and cost model enables a cohesive evaluation of the financial impacts of AI adoption. An example investment case demonstrates how advancing a level of GenAI process maturity per the key practices can yield substantial cost savings with a short break-even period. Though the cost model calibration is provisional, the modeling framework supports ongoing empirical calibration and refinement to keep up with evolving AI technologies and engineering processes.
PRESENTER
Ray Madachy
Raymond Madachy, Ph.D., is a Professor in the Systems Engineering Department at the Naval Postgraduate School. His research interests include systems engineering tool environments for digital engineering, modeling and simulation of systems and software engineering processes, generative AI, and system cost modeling. He has developed widely used cost estimation tools for systems and software engineering, and created the Systems Engineering Library (se-lib). His books include Software Process Dynamics, What Every Engineer Should Know about Modeling and Simulation, What Every Engineer Should Know about Python; and co-authored Software Cost Estimation with COCOMO II and Software Cost Estimation Metrics Manual for Defense Systems.