1336. GenAI and OR – a boost for productivity?
Invited abstract in session TC-43: GenAI and Learning, stream Software for Optimization.
Tuesday, 12:30-14:00Room: Newlyn GR.07
Authors (first author is the speaker)
| 1. | Jens Schulz
|
| FICO |
Abstract
In Operations Research, we deal with complex business problems such as optimizing a logistics network incorporating uncertain demands, prices, and capacities along the supply chain, or identifying a pricing strategy that balances competing objectives such as expected return and risks. Deriving insights from data and running strategies what the best path forward is key to decision makers. With simple answers they are facing the challenge of trust; with complex answers and user interfaces, they feel overwhelmed. There are reoccurring themes of (i) missing data quality, (ii) the need for flexible software tools that adapt to the business situation rather than pre-canned screens, and (iii) efforts to level up via trainings in order to dare using decision support tools.
From the data scientist to the decision maker, there is a huge potential for where Generative AI can make users more productive and enables them to go beyond the current status quo. Onboarding experience for new software tools as well as having the right information at hand and presented in the right context is key. At the same time, a proper responsible AI policy is required by companies emphasizing transparency, ethical aspects and explainable outcomes before putting such models into production.
Generative AI will not resolve all problems, yet, integrated properly into the tools with focus on the user needs and current obstacles it is having tangible impact.
Keywords
- Software
- Decision Support Systems
- Agent Systems
Status: accepted
Back to the list of papers