What happens when a PMIS rollout reaches 4,000 users? How should project leaders decide what level of confidence is enough when making risk-based decisions? And as artificial intelligence enters the estimating process, how can organizations take advantage of its speed without sacrificing confidence in the results?
PMA explored these questions at the 2026 AACE International Conference, sharing three peer-reviewed papers grounded in real-world project experience. The annual conference, which celebrated AACE International’s 70th anniversary, brought together project controls professionals from around the world for more than 100 hours of technical sessions covering cost engineering, scheduling, estimating, risk management, and emerging technologies.
Francisco Cruz, Ernesto Toxqui, and Daniel Posada examined what happens when project management technology must work at enterprise scale in Lessons Learned from a Large-Scale PMIS Implementation Across a 4,000-User Organization. Their experience revealed that some of the toughest challenges were not technical at all. Governance, stakeholder engagement, standardized business processes, and change management became critical to making the system work for thousands of users. The paper offers practical lessons for organizations undertaking similarly complex digital transformations.
AACE International members can access the PMIS implementation paper here.
A second paper tackled a familiar challenge for project leaders: turning quantitative risk analysis into information executives can actually use. In Confidence: What Stakeholders Want and What We Need from QRA, John Hollman of Life Validation Estimating LLC and PMA’s Francisco Cruz explored how organizations can move beyond simply reporting confidence levels and instead select them intentionally based on business objectives, project type, governance, risk tolerance.
The paper also makes the case for a broader role for risk analysts. Their value lies not only in producing sophisticated statistical models, but in helping decision-makers understand what those results mean for the business. By connecting quantitative analysis with organizational strategy and risk tolerance, risk professionals can become trusted advisors who help leaders make better-informed decisions.
AACE International members can access the QRA paper here.
The third presentation looked ahead to one of the most rapidly changing areas of project controls. Amtrak Project Controls Manager Vishwambhara Kumbharathi and PMA’s Saumil Maniar presented AI-Aware Influences on Cost Estimate Maturity, exploring how artificial intelligence could reshape estimating while reinforcing the need for engineering judgment and sound governance. AI can already help automate quantity takeoffs, develop parametric estimates, and perform real-time risk analysis, potentially giving decision-makers useful information more quickly.
The authors proposed supplementing AACE International’s established Cost Estimate Classification System with three measures that address the distinctive risks of AI-assisted estimates: an Information Fitness Index for the quality and traceability of underlying data, a Model Risk Grade for the transparency and reliability of the AI model, and an Automation Level showing how much machine-generated output influences the estimate. Together, the measures offer a way to embrace AI while maintaining accountability and confidence in the information used for critical project decisions.
Although the three papers address very different challenges, they share a common theme. Technology, data, and sophisticated analytical tools can strengthen project controls, but their value ultimately depends on how effectively people use them to make decisions. By translating lessons from real projects into practical guidance for the profession, PMA continues to contribute to the industry’s body of knowledge and help owners and project teams improve project delivery.