How confident are you that your EVMS is helping to proactively manage risk and performance? In this interactive workshop, participants will be introduced to the Integrated Project/Program Management (IP2M) Maturity and Environment Total Risk Rating (METRR), a rigorous framework for assessing Earned Value Management Systems (EVMS) effectiveness on large, complex capital endeavors. Participants will learn how to evaluate EVMS implementation, identify performance risks, and prioritize opportunities for improvement. With practical examples, the workshop will also highlight how IP2M METRR assessments result in statistically significant cost and schedule impacts, demonstrating the value of strengthening EVMS execution through IP2M METRR.

Why are we still estimating billion-dollar projects from static averages?” Modern estimating systems were built for a different era — one defined by static databases, generalized industry averages, and disconnected project data. But today’s projects already contain the information needed to build continuously learning estimating systems. This session explores how project archetypes, historical actuals, quantity installs, estimator expertise, and machine learning can be combined to create adaptive Cost Estimating Relationships (CERs) that evolve over time. By integrating quantity-based models, incurred labor performance, estimator feedback, and historical delivery data, organizations can continuously refine productivity assumptions using their own operational intelligence. The presentation will examine how semantic estimating structures, archetype-driven modeling, and machine learning workflows can create dynamic estimating environments that reduce dependence on static industry averages and better align estimates with actual project delivery performance. The future of estimating is not static reference data — it is continuously learning organizational intelligence built from every project delivered.

The data center industry is expanding at unprecedented speed, bringing complex challenges in supply chain, power delivery, community relations, regulatory requirements, and skilled resource availability. In this joint presentation, EdgeConneX share their real-world journey of business and digital transformation, with Omega 365 serving as a key enabler. Building on lessons from large-scale enterprise rollouts, they discuss practical strategies for navigating these challenges while improving project controls execution. They will openly discuss: • Key business and client challenges in hyperscale data center delivery • Business transformation strategies and organizational change • Digital transformation tools and processes, including deep integration with Omega 365 and Primavera P6 • Practical approaches to user adoption and breaking down silos • Where AI fits into forecasting, risk management, and decision-making

You have the controls data. The challenge begins when that analysis needs to drive a decision and gets reduced to a summary table that strips away the context behind it. By the time information reaches stakeholders, much of the rigor that project controls teams worked to produce has been lost. As programs become more interconnected, leaders need more than static reports. They need to understand how schedule, cost, risk, and dependencies interact across the portfolio and explore those relationships in real time. In this session, you'll learn how organizations are connecting controls outputs into a live portfolio layer that preserves context, improves stakeholder understanding, and enables more informed decisions. The result is a portfolio view leadership can navigate in the room, not a report that arrives after the meeting.​ What you’ll learn:​ Techniques for connecting P6, cost, and risk data into a unifed view. ​ Ways to visualize where schedule risk intersects with cost exposure and portfolio dependencies.​ Approaches that move organizations from reactive reporting to proactive portfolio navigation. ​ Practices for delivering executive-ready portfolio briefings without rebuilding data for every meeting.​ Methods for revealing interdependencies that static EVM reports often fail to show.

The project management landscape is undergoing a paradigm shift driven by disruptive technologies redefining how projects are planned, executed and delivered. This presentation explores how the strategic integration of AI, BIM, Blockchain, AR, Reality Capture, IoT and Power BI is not an aspirational concept — but a practical reality.  .Real-world examples demonstrate how these technologies solve long-standing industry challenges. BIM creates a single source of truth. IoT enriches it into a live tracking model.. Blockchain function as a smart contract. Power BI transforms data into actionable intelligence. The future of project management is not a distant vision. It is here.

Planning and scheduling are universal disciplines, but they are practiced within vastly different environments. While defense programs and construction projects share common objectives—delivering complex work on time and within budget—the approaches to planning, governance, risk management, and execution often reflect very different priorities and constraints. Drawing on firsthand experience leading planning and scheduling for large-scale defense programs, this session explores the similarities and differences between defense acquisition and construction project controls. Attendees will gain insight into how defense organizations leverage integrated master schedules, technical performance, earned value management, and structured governance to manage complexity, while also examining the agility, field-driven decision-making, and execution focus that characterize successful construction projects. Rather than suggesting one industry has the “better” approach, this presentation highlights the strengths of each and identifies practical lessons that can be applied across both. From schedule architecture and risk integration to stakeholder communication and executive decision-making, participants will discover ideas that improve schedule credibility, enhance project visibility, and strengthen project outcomes regardless of industry. Whether you work in construction, infrastructure, energy, aerospace, or defense, this session will challenge conventional thinking about project controls and demonstrate how cross-industry perspectives can elevate the planning and scheduling profession.

Project controls functions are still viewed as reporting centres rather than strategic decision support — leaving executives unable to translate data into actionable insights. Drawing on 25+ years of experience across capital programmes totalling $50 billion+, this session explores how organisations can evolve project controls into a critical driver of executive decision-making. Real-world lessons from infrastructure, utility, transportation and life sciences programmes demonstrate how integrated cost and schedule controls, portfolio forecasting and standardised governance frameworks deliver earlier risk and opportunity visibility. The session addresses key barriers — siloed data, inconsistent reporting and leadership misalignment — and provides practical strategies for building scalable controls structures that improve accountability, accelerate decisions and enhance programme predictability.

This session will begin by establishing a clear definition of the Controls Framework and the key success factors that underpin effective program delivery. It will then explore the drivers behind redefining the Controls Framework, including evolving infrastructure delivery models, shifts in procurement strategies, and rapid technological advancements that are transforming the industry. Looking ahead, the session will examine the future of the program controls workforce and the capabilities required to succeed in an increasingly complex environment. The discussion will conclude with key takeaways and an interactive dialogue. Designed as a workshop, this session encourages active participation, engagement, and the sharing of perspectives to collectively shape the future of program controls.

As infrastructure and capital mega programs continue to grow in scale and complexity, traditional Program Management Offices (PMOs) are being challenged to move beyond project reporting and administrative oversight toward proactive, data-driven decision support. At the same time, advances in AI are creating new opportunities to transform how PMOs monitor program performance, identify emerging risks, allocate resources, and support executive decision-making. This presentation explores how AI is reshaping the role of the PMO across the lifecycle of major capital programs. The session examines AI tools that are either actively being used or are in development related to submittal analysis, schedule review, meeting documentation that are all becoming key inputs for the PMO to manage interdependencies across projects, and surface risks before they escalate into major issues or disputes. Through practical examples drawn from large infrastructure programs, attendees will learn how AI-enabled PMOs can improve portfolio visibility, strengthen governance, enhance cross-project coordination, and provide executives with more timely and actionable insights.

Earned Value Management (EVM) is built on a simple principle: integrating scope, schedule, and cost to provide a more complete view of project performance than schedule or cost data alone. Many projects emphasize one dimension over the other, often avoiding full integration in the absence of a contractual EVMS requirement. While compliance with Federal Acquisition Regulations and standards such as EIA 748e may drive adoption, organizations can still realize meaningful benefits through a scaled approach. Attendees will learn how to: • use existing schedules to build baselines for effective performance tracking • improve forecast accuracy • analyze cost and schedule variances • scale EVM to capture its benefits without the burden of a fully compliant system See how EVM can be introduced using project management practices your organization likely already has in place.

Project controls quietly saves every megaproject from itself — yet in the US, it remains a hand-me-down skill picked up between crisis meetings. The UK and Australia recognised this years ago. With trillions flowing into infrastructure, chips, data centres and energy projects, the US is staffing programmes with people who learned EVM from a YouTube video. That is not a strategy. This session makes the case for accredited university project controls programmes — covering cost and schedule integration, risk quantification, AI literacy, commercial awareness and governance. AI won't replace project controls professionals. It will free them — if we build the pipeline now.

Progressive Design Build (PDB) requires project teams to commit to a Target Price while design evolves — placing intense pressure on estimating, planning and risk management. Traditional report-driven Project Controls cannot support the rapid decision-making this demands. This presentation draws on practitioner lessons from the Scarborough Subway Extension (SSE SRS) — a Canadian transit megaproject delivered by Scarborough Transit Connect (an Aecon JV) for Metrolinx — to show how Project Controls functioned as a confidence engine, not a back-end reporting function. Through an integrated operating system combining governance, estimating, production planning and risk, the team achieved Target Price with confidence despite evolving design maturity. Winner — PCE Mega Project of the Year 2025.

The Department of War faces a structural challenge: operational communities rely on real-time, data-driven decisions while acquisition governance remains rooted in periodic reporting, static baselines and retrospective Earned Value Management. The result: decision latency, limited risk visibility, and constrained performance management. This paper presents Integrated Program Management 2.0, a governance framework integrating cost, schedule, technical maturity, supplier readiness, and risk into continuous, decision-oriented performance management. Central to IPM 2.0 is a Digital Data Fabric supporting a Unified Performance Ledger, advanced analytics, and an Integrated Performance Index enabling portfolio-level prioritization. IPM 2.0 reframes program controls from periodic compliance to predictive outcome-oriented decision making.

Project controls has a credibility paradox. The technical rigor that earns a planner or cost engineer a seat at the table is the same rigor that can keep them stuck beside it. They are trusted to report performance, but rarely invited to shape the strategic decisions that data should inform. The profession too often monitors delivery rather than influencing portfolio outcomes and benefits realization. This session presents a practical career-architecture model for developing controls professionals across four altitudes of influence (project, program, portfolio, and enterprise) without trading away the technical foundation that underpins their authority. Drawing on competency-framework design and measurable outcomes, it maps the shift required at each transition: from producing data to interpreting it; from interpreting it to translating it into an executive narrative; and from advising on decisions to owning them. Attendees leave with a diagnostic for identifying individuals and teams on the technical-to-strategic continuum, a competency model built around career progression rather than static job descriptions, and tactics for the hardest transitions: translating cost and schedule insights into board-level decisions, navigating organizational politics, and leading multidisciplinary functions.

What truly differentiates high-performing scheduling organizations from the rest? This session explores the defining behaviors and capabilities of leading teams, with a focus on people, process, and systems. We’ll examine how effective organizational structures and clear translation of contractual requirements drive successful outcomes—while exposing the common pitfalls that hold others back. Drawing on real-world experience across Europe and the US, and spanning Rail, Defense, Commercial, and Heritage sectors, this session offers practical insights you can apply immediately.

On 7 Nov 2025, the Secretary of Defense announces a series of Acquisitions Reforms centered on requirement reform and accelerating fielding of systems to the warfighter. US Congress codified a significant number of the changes in Dec 2025 with the passing of the Fiscal Year (FY) 2026 National Defense Authorization Act (NDAA). Over the past 10 months, the transformation has proceeded at lighting speed creating significant change in how capital assets are planned and managed since the Goldwater Nichols changes in 1986. A significant focus is the wholesale change from program to a strategic portfolio management approach with the creation of portfolio scorecards. The prior 40-year Program Executive Officer structure is transforming to a Portfolio Acquisitions Executive (PAE) construct with significant effects on delegated power structures across contracting, financial/budget, performance management while also attempting to link systems direction to combatant missions with the goal of accelerating how gaps are closed. The talk will provide you an update on the different approaches being taken and the potential effects on commercial industry. US Defense approaches, given its mega size, has historically been a leading indicator of future expectations across many industries in Project Controls.

Most airport terminal cost overruns do not happen because of bad luck. They happen because the owner never had a financial authority who was truly independent — someone whose only job was to protect the public's money, validate every proposal against market reality, and say no when the numbers did not hold up. DFW Terminal C is a $1.2 billion modernization — $833M in direct construction — at one of the world's busiest airports, operating 24/7 through every phase. As the embedded owner-representative Chief Estimator, I held full financial authority: independent validation of contractor proposals, owner-side pricing of scope changes, value engineering facilitation, and real-time contingency tracking across 47 change events. Three owner-side disciplines drove performance: independent cost validation eliminated information asymmetry in change order negotiations; a scope change governance system gave leadership unambiguous budget visibility at every reporting cycle; and proactive value engineering captured savings during design — when change costs nothing — not during construction. Combined result: $60M in verified savings against the approved capital budget, with zero scope reductions.

Railway network upgrade programmes are among the most complex infrastructure deliveries — executed within live operational environments, constrained access windows, high system interdependency and evolving stakeholder requirements. Conventional deterministic schedules and static cost baselines are structurally inadequate for managing this uncertainty. This presentation advances a risk-integrated framework for target pricing and project controls, tailored to collaborative alliance-based delivery models and grounded in AACE RPs, FTA guidance and EN 50126 RAMS standards. Through Quantitative Schedule and Cost Risk Analysis (QSRA/QCRA), uncertainty is modelled into confidence-based outcomes — P50, P80 — replacing fixed estimates with dynamic, risk-adjusted target prices. The central finding: the primary limitation is not lack of data — but lack of integration.

City of Baltimore department of Public Works is exploring the use of Artificial Intelligence (AI) for real time performance monitoring and risk analysis. The objective of this exploratory study is to enhance predictive forecasting, flag early warning of delays and cost overruns, recommend corrective action based on past project behavior and historic data. AI tools/software were used to model possible construction sequences using resource constraints and activity logic to help identify and optimize the schedule by running a 3-point estimate model (optimistic, most likely and pessimistic) per activity or production rate. This results in side-by-side comparison for crew size, methods and sequencing. In addition, AI tools are useful in doing ‘what-if’ scenarios within minimal time. Overall, the analysis is critical in making informed decisions by providing an early warning system that identifies high-risk items, gaps in resources allocation and validates the sequence of construction. Although this is a limited study of about three projects, this study shows a promising outcome and the use of AI may be expanded to the whole portfolio.

AACE International’s Cost Estimate Classification System aligns estimate purpose with project maturity to support stage-gate decisions. Estimates traditionally progress from Class 5 to Class 1 as scope definition, engineering detail, and cost data increase, with accuracy refined through risk analysis and documented in the basis of estimate. The growing use of artificial intelligence is transforming this process. Applications such as automated quantity extraction, machine learning–based parametric modeling, and real-time probabilistic analysis can accelerate estimate maturity and provide continuous confidence updates. However, they also introduce challenges related to data integrity, model reliability, and transparency that must be addressed to maintain credibility. This paper examines how AI may supplement the classification of estimates and enhance decision-making practices. It proposes an “AI-aware” framework with three dimensions: information fitness index (IFI), model risk grade (MRG), and automation level (AL) to integrate AI while preserving governance, accountability, and decision confidence.

Capital improvement programs often struggle with outdated or inconsistently applied project controls processes, resulting in cost overruns, schedule delays, design quality issues, and increased claims exposure. This presentation introduces an integrated phase-gate project controls process that modernizes construction management by aligning cost, schedule, risk, and quality/claims management across the full project lifecycle. The session will examine common root causes of process failure, outline a practical methodology for evaluating and improving existing organizational processes, and demonstrate how structured gate reviews can strengthen governance, improve decision-making, and support design-to-budget and design-to-schedule outcomes. Attendees will gain a practical framework for improving predictability, transparency, and overall performance in capital improvement program delivery.

The most capable project controls teams still struggle when their technology doesn't match the way they work. Rigid platforms force process changes. Disconnected systems fragment data, restrict visibility and introduce cybersecurity risk. When you don't control your data, you don't truly control your project outcomes. This session explores how a new generation of connected, configurable construction management platforms are fundamentally changing how project teams operate (leveraging AI to shift from reactive controls to predictive, proactive delivery). Attendees will leave with a practical evaluation framework built around two criteria: connectivity (who controls and governs the data) and configurability (how well the platform adapts to your team).

This presentation showcases a practical, automated approach to tracking multiple float paths accurately across varied project timelines. By utilizing an AI-driven algorithm, this methodology simplifies network diagnostics by focusing strictly on the relationship gap between activities rather than traditional free or total float metrics. This shift provides a stable mathematical foundation for mapping sub-critical paths, ensuring parallel sequences are ranked based on true logical proximity.By replacing traditional activity-centric float filters with automated relationship-gap metrics, project teams gain an efficient, tool-agnostic utility for routine network reviews. The algorithm processes network data instantly, eliminating manual sorting when overlapping calendar structures are introduced. Attendees will discover how this streamlined diagnostic approach provides immediate clarity on sub-critical risks, allowing senior planners to deliver reliable milestone tracking with minimal administrative overhead. Ultimately, transitioning to relationship-gap tracking isolates mathematical artifacts and preserves network data integrity.Learning Objectives:Apply automated relationship-gap metrics to accurately track and rank multiple float paths.Streamline routine network reviews by substituting traditional activity float diagnostics with relationship-level analysis.Utilize an algorithmic framework to maintain consistent sub-critical path integrity across diverse network structures.

Project controls teams capture enormous volumes of data — timesheets, cash flows, risks, progress, quantities, RFIs — yet benchmarking across projects, programs and organizations remains stubbornly manual. The data exists; it just isn’t comparable. Every organization names, structures and classifies its records differently. This session presents UniPhi Chrysalis, a working data transformation pipeline that turns live project data from many independent SaaS deployments into a single, governed benchmarking dataset. We walk through the architecture end to end: scheduled extraction from each client instance via API into a medallion-structured data lake; metadata enrichment; and the core of the transformation — an AI-assisted classification engine that maps every record to a common classification system — Uniclass 2015 (EF, Ss, Pr, Ac) in our case, though the pattern applies equally to OmniClass, UniFormat or MasterFormat. Deterministic rules handle clean, repeatable mappings; a large language model proposes candidates for the fuzzy remainder; every code carries a confidence score, with below-threshold matches routed to human review — nothing lands in the benchmark silently. Confirmed matches feed back into the rules layer, so the system improves with use. The result is the “butterfly effect”: data captured once, at the point of work, re-emerges as self-service asset benchmarking — estimated costs, phasing and classification-aligned breakdowns drawn from real delivered projects.

This paper presents a PMO Control Architecture governing over 100 concurrent IT initiatives in a regulated industry through system-enforced lifecycle controls and integrated performance intelligence. A Controlling PMO model was established embedding defined checkpoints across initiation, planning, execution and closure. Manual reporting was replaced with system-generated control validation, ensuring traceability, metadata integrity and disciplined governance. Project artifacts were consolidated within an enterprise PMIS designed around structured data capture. Standardised digital forms enabled categorisation by project type, phase, risk exposure and ownership — integrated with BI dashboards for real-time portfolio visibility and executive decision support. AI-driven anomaly detection, advanced risk identification, and automated detection of process and capability gaps further enhance this structured control environment.

Most Prediction AI in project controls forecasts schedules and costs. But roughly 65% of project failures trace to management and people issues, governance breakdowns, decision latency, and contract behavior no schedule model can see. That is the gap the xPM Strategic Decision Engine closes. Built on 25 years across 13+ countries and over $6B in projects, and doctoral research on neural networks for cost intelligence, the Engine is a 7-layer Prediction AI architecture for every scale of construction, every delivery model, and every stakeholder seat: from project owner to specialty sub, pre- to post-construction. Each project is read through seven expert layers, Strategic Value Core, Governance Protocol, Capital Memory, Contract Risk Reality, Organizational Force Field, Physical Truth, and Digital Nervous System. A Cross-Layer Synthesis Agent then runs Conflict Detection, Compounding Risk, Priority Matrix, Systemic Weakness, and a composite xPM Score, compressing 169 techniques, 16 domains, 84 decision methods and 9 PM knowledge areas into one executive view. Four governing questions drive every output: What should be? What happened? What is happening? What will happen? turning data into expectation, history, present truth, and prediction owners and executives can act on with confidence. You will leave with a working framework for predicting failure before it surfaces in the numbers, and the language to brief your owner, your board, and your project team with certainty.

Delivering hyperscale data centre programmes demands excellence across risk, schedule and cost management. Yet even the most advanced tools fail when organisations face entrenched processes, siloed teams and resistance to change. Tom Phythian and Hasanthi Wijeratne — who together led the full lifecycle rollout of Omega 365 at Microsoft across one of the world's largest hyperscale data centre portfolios — share real-world lessons on the people and process dimensions of technology-enabled transformation. Key topics include overcoming organisational resistance, breaking down silos, change management at enterprise scale, and measured outcomes across hyperscale capital deployments. The session also highlights how Microsoft is applying AI to augment risk identification, forecasting and decision-making.

When developed, CPM focused on prospectively sourced, predictive, un-progressed schedules and not on delay analysis. This focus requires delay analysts to deal with the prospect of adapting CPM original criticality theories to retrospectively sourced schedulesa task made non-trivial by the lack of CPM calculations in the as-built window of an update (, i.e., left of the data date). A workaround involves analysts sourcing superseded, predictive schedules in for retrospective causal modeling and while applying a prospective view of criticality even in retrospective causal modeling. The integrated delay theory (IDT) opposes this oversimplification. Specifically, IDT criticality theorems explain that what counts as the critical path and whether two or/ more independent delays concurrently impact/ed completion depend on whether the schedule is prospectively or retrospectively sourced.

Construction project controls have long been defined by a fundamental tension: the data needed to make good decisions exists somewhere in the project record, but finding it, reconciling it, and presenting it in time to act on it is a full-time job in itself. Submittals pile up. RFIs multiply. Change orders accumulate. And somewhere in that volume of documents, the signals that should be driving owner decisions get buried. Agentic AI is changing that equation — not as a distant promise, but as a practical capability that leading capital program teams are deploying today. This session takes a ground-level look at how AI is being used to automate the collection, classification, and reconciliation of project data across the full document ecosystem. Attendees will see how agentic workflows can extract structured information from submittals, RFIs, change orders, and other construction documents, cross-reference it against established values and source records, and surface the discrepancies and trends that matter most to owners and project controls professionals. Drawing on real-world examples from university capital programs, the session will walk through the before and-after of an AI implementation: what the data environment looked like before automation, what the pilot targeted, how it was scoped and deployed, and what measurable outcomes resulted. The goal is to give attendees a concrete and honest picture of what AI can and cannot do for project controls today. Attendees will leave with a practical framework for identifying the workflows in their own programs most ripe for automation, a strong understanding of the technological capabilities available, and a clear methodology for building the business case needed to win internal buy-in. Whether you are early in your exploration of AI or already piloting solutions, this session will sharpen your thinking and accelerate your path to implementation.

As infrastructure programs grow in scale, complexity, and stakeholder expectations, the role of Program Management is evolving beyond traditional delivery oversight. Today's clients require strategic partners who can integrate governance, technology, data, risk management, stakeholder engagement, and organizational alignment to achieve successful outcomes. This presentation will explore AECOM's journey in shaping the future of Program Management through a client-centric and outcome-driven approach. Drawing on experiences from some of the world's most complex infrastructure programs, we will discuss how Program Management is transforming from a coordination function into a strategic capability that enables organizations to navigate uncertainty, improve decision-making, and deliver lasting value. The session will highlight emerging trends, lessons learned, and innovative practices that are redefining how programs are initiated, governed, and delivered. Attendees will gain insights into how integrated Program Management approaches can strengthen resilience, enhance collaboration, leverage digital solutions, and support clients in achieving their strategic objectives while delivering complex programs with greater certainty and confidence. As the industry continues to evolve, Program Management must move beyond managing projects to enabling outcomes. This presentation will demonstrate how AECOM is helping shape that future and partnering with clients to address the challenges and opportunities of the next generation of infrastructure delivery.

The Future of Major Program Delivery is the most extensive, current research on megaproject delivery analyzing 5,000+ present-day mega programs upwards of $1 billion, many over $10 billion. It examines why 90% of major programs fail to meet cost, schedule, and/or ROI targets. For an unprecedented $15 trillion invested in active megaprojects—wherein failures place $1.5 trillion of economic growth at risk—the report finds systemic delivery barriers and success measures proven to improve delivery certainty and catalyze long-term value, including collaborative models and multidisciplinary management aligning people, organizations, processes, data, and tech with digital AI to optimize outcomes.

Artificial intelligence is rapidly changing how organizations plan, monitor, and deliver complex projects. However, adopting AI tools does not automatically create better decisions, stronger controls, or more predictable outcomes. Without reliable data, aligned governance, prepared teams, and clear accountability, AI can accelerate existing weaknesses just as easily as it can improve performance. This presentation examines why project controls is uniquely positioned to serve as the bridge between AI adoption and successful project delivery. Project controls professionals operate at the intersection of data, cost, schedule, risk, change, performance, and leadership decision-making. That position gives the function a critical role in assessing whether an organization is truly ready to use AI responsibly and effectively. Using a practical AI Readiness framework, the session explores three foundational areas organizations must address before scaling AI: data readiness, organizational capability, and strategic alignment. It also introduces the E³ approach—Empower, Execute, and Elevate—as a structured method for preparing people, implementing AI-enabled workflows, and continuously improving performance. Attendees will learn how project controls can move beyond reporting and transactional execution to become a strategic decision-support function that strengthens project predictability, risk visibility, workforce readiness, and delivery confidence. The presentation will also identify common readiness gaps, practical actions leaders can take immediately, and the essential role of human judgment in an increasingly AI-enabled project environment.

Facility owners have traditionally managed capital construction and ongoing maintenance using separate systems, creating fragmented data, duplicated effort, and limited visibility across the asset lifecycle. As organizations face aging infrastructure alongside continued capital investment, the need for an integrated approach to facilities information management has become increasingly important. This presentation explores how a unified project and facilities management platform can support both capital project delivery and deferred maintenance within a single governance framework. By leveraging shared asset data, standardized business processes, configurable workflows, and integrated reporting, organizations can seamlessly transition information from design and construction into operations without manual re-entry or loss of institutional knowledge. The session will examine practical approaches to managing two interconnected lifecycles: capital project delivery and operational maintenance. Attendees will learn how facility condition assessments can be transformed into prioritized maintenance backlogs, enabling organizations to quantify deferred maintenance, evaluate risk, allocate funding, and execute renewal programs using consistent data and decision-making processes. Real-world implementation strategies will demonstrate how standardized workflows, portfolio-level visibility, and integration with enterprise financial and work management systems improve planning, governance, and long-term asset stewardship. Participants will leave with a framework for consolidating facilities data into a single source of truth that supports informed investment decisions, improves operational efficiency, and strengthens the connection between new construction and ongoing asset management.

A Schedule or Cost Risk Assessment can be an intimidating exercise... but it does not have to be! This session will help to demystify Risk inputs and reporting for all levels of experience. We will discuss the best methods of gathering inputs, including one vital prerequisite. Further, we will examine risk assessments in the session and gain consensus on the likely conclusions, ultimately equipping the group to be able to perform these while empowering analysts to brief their team using their own unique style. After this session, attendees will: • Understand the most commonly used risk inputs for a monte-carlo based Risk Assessment • Explain the distinction between a Risk Exposure Histogram and a Risk Drivers Tornado Chart • Quickly assess charts to be prepared to brief risk in an impromptu fashion • Steer Program Managers and Executives to the most important Enterprise and Project threats to mitigate so that the appropriate decisions can be made.

Mega capital programmes are delivered through complex contracting strategies, multiple stakeholders and accelerated schedules — introducing significant uncertainty in cost and schedule outcomes. Risk management is frequently treated as a parallel activity rather than an integrated component of project controls. Risk registers are developed and workshops conducted — yet outputs remain disconnected from cost forecasts, schedule updates and contingency management. This presentation introduces a practical framework connecting risk identification, structured risk registers and periodic reviews with core project controls processes — including Cost & Schedule Risk Analysis (CSRA). Drawing on EPC and EPCM programme experience, attendees will learn how to embed risk thinking directly into forecasting and decision-making — moving beyond standalone risk registers.

Projects rarely fail for lack of information. More often the data was fragmented, accepted without challenge, or summarized into more confidence than the evidence justified. A dashboard shows green while untested assumptions, weak schedule logic, understated cost, and disconnected risks build beneath the surface. This session examines how independent assurance exposes the gap between reported performance and actual project health. The issue is not whether reports are technically correct—it is whether schedule, cost, risk, and scope tell the same story. Each control function can perform its role flawlessly while no one reconciles the outputs as a single body of evidence. Drawing on cost estimating, scheduling, and program governance experience across major federal programs, this session identifies the conditions that let hidden risk go undetected, and shows how assurance strengthens resilience by surfacing problems early enough to act. Attendees leave with practical questions to challenge reported status.

In today’s rapidly evolving climate landscape, traditional risk management is no longer enough. This presentation reveals practical strategies for integrating climate risk into project controls and risk registers, empowering organizations to anticipate, adapt, and thrive amid uncertainty. Attendees will explore proven tools like climate scenario analysis, stakeholder engagement, and real-world case studies to identify both acute and chronic risks, enhance resilience, and unlock value for their projects. From leveraging climate data to embedding best practices for regulatory compliance and stakeholder confidence, this session provides a step-by-step roadmap from Risk to Resilience. Join us to learn how organizations are transforming risk registers into dynamic tools that safeguard investments and ensure long-term success.

Artificial intelligence (AI), particularly large language models (LLMs), are rapidly entering construction cost estimating and project controls, promising faster data synthesis, earlier decision support, and standardized workflows. Yet these same systems can produce hallucinations: confident, fluent, but factually incorrect or fabricated assertions. Hallucinations differ from ordinary software defects in that they are opaque (difficult to trace), highly persuasive (professional tone, formatted outputs), and contextually embedded (surrounded by otherwise correct content). In high stakes estimating contexts, this combination creates a systemic risk of false confidence that can propagate into budgets, contingencies, bids, and claims. This paper explains why hallucinations occur and how they manifest in estimating practice; offers tight narrative examples from other industries to show real world consequences; and proposes AI-Assisted estimate validation framework, a defense in-depth mitigation framework aligned to NIST’s AI Risk Management Framework (AI RMF 1.0), ISO/IEC 23894 (AI risk management), and ISO/IEC 42001 (AI management systems). The paper concludes with an implementation roadmap and a practitioner checklist that embeds human in the loop validation, data provenance, structured prompting, retrieval augmented generation (RAG), and auditability into everyday estimating workflows.

The federal government manages one of the largest capital construction portfolios in the world. The U.S. Army Corps of Engineers, Naval Facilities Engineering Systems Command, Air Force Civil Engineer Center, U.S. Coast Guard, and the Department of Veterans Affairs collectively oversee thousands of active projects annually — spanning hundreds of installations, multiple delivery methods, and some of the most complex reporting requirements in the industry. The challenge isn't a shortage of data. It's that the right data rarely reaches the right people at the right time. Project teams produce it. Leadership needs it. And somewhere between the field and the executive briefing room, visibility breaks down. This plenary session brings together senior leaders from across the federal construction enterprise to discuss how their agencies are confronting that gap — standardizing data across non-standard portfolios, meeting federal reporting mandates without sacrificing field-level flexibility, and leveraging technology to turn project data into program intelligence.

In design-build delivery, disproportionate risk allocation drives cost overruns, schedule delays, forecast volatility, litigation, adversarial relationships, insurance coverage gaps, compromised deliverables, and claims. Misaligning risk with control compromises project controls processes, including estimating, scheduling, and cost forecasting. The Design-Build Institute of America (DBIA) emphasizes that successful design-build projects require equitable risk allocation to the best-equipped party, enhancing predictability, integrity, and contingency effectiveness. This session examines practical mechanisms influencing performance, including limitation of liability, consequential damage waivers, pre-bid scope definition, integrated project delivery principles, contingency allocation, and coordinated insurance. These are discussed as levers for improving transparency, reducing uncertainty, and strengthening cost and schedule control. The session also explores innovations like data-driven tools and predictive analytics for early risk identification before they materialize into cost and schedule impacts. Attendees will gain actionable strategies to align contractual risk with project controls, boosting forecast confidence and promoting proactive risk management for better results.

The rapid adoption of generative AI has introduced underrecognised risks in construction, where invoices, change orders, estimates, and labour documentation form the foundation of financial controls and audits. Modern AI tools can now fabricate polished narratives, manipulate images, and produce complete document packages that closely mirror authentic records — without any field validation. Traditional audit workflows were not designed to detect AI-generated content that is consistent, well-structured, and statistically plausible. As GenAI lowers the cost of creating convincing artifacts at scale, the risk of undetected payment leakage and audit failure grows. This presentation examines AI-generated content through a construction-specific lens, evaluating the limitations of current detection technologies and introducing a structured framework of non-software-based methods — including metadata forensics, auditor pattern recognition, cross-verification, and statistical analysis. Together, these techniques form a layered defence to help auditors, project controls professionals, and construction managers detect the hidden hand of AI before it undermines project integrity and governance.

Artificial intelligence is transforming how project delivery organizations manage schedule, cost, risk, reporting, documentation, and performance visibility. However, its potential often fails to translate into sustained operational value. Pilot initiatives frequently succeed in isolation but struggle to scale, while tools are deployed before organizations are fully prepared to use them responsibly. As a result, project controls professionals are left without clear guidance on where AI fits, how to validate its outputs, and who is accountable when issues arise. This presentation introduces a practical AI–PMO Organizational Readiness Framework for project-driven organizations. It positions the Project Management Office (PMO) as a natural starting point for AI adoption, given its role at the intersection of project data, governance, procedures, reporting, quality assurance, and executive decision support. The framework outlines eleven key readiness dimensions required to move from controlled pilot initiatives to scalable organizational adoption: leadership and sponsorship, workforce capability, data readiness, workflow redesign, role alignment, responsible AI governance, technology integration, change adoption, value measurement, scale-up readiness, and AI agent quality assurance.

Developing a ten-year capital roadmap for a major public utility is more than an engineering exercise; it is a complex financial and operational puzzle. This presentation delivers an inside look at how the San Francisco Public Utilities Commission (SFPUC) successfully established its $12.5 Billion Capital Improvement Plan (CIP) for FY 2026–27 through FY 2035–36 amid unprecedented market headwinds. Attendees will learn how the SFPUC moved away from siloed planning by launching the cross-enterprise Capital Planning Improvement Initiative. Faced with initial project requests that drastically outpaced revenue limits, the agency instituted a strict, multi-phase governance framework to bridge the gap between engineering needs and ratepayer affordability constraints. Key takeaways and focus areas include: · Data-Driven Prioritization: How the SFPUC utilized risk-based validation models to separate critical infrastructure demands from lower-priority project requests. · Rigorous Deliverability Analysis: The method the Engineering Management Bureau (EMB) used to stress-test the plan against actual human resource constraints, factoring in vacancy rates and a citywide hiring freeze. · Predictive Cost Controls: Real-world application of compounding escalation rates and a proactive +5% market condition factor to insulate the portfolio against evolving U.S. import tariff shocks. · Portfolio Synchronization: The process of aligning contractor capabilities, public works coordination, and software data workflows (P6, Unifier, and SharePoint) to drastically reduce unspent carry-forward balances. Ultimately, this session demonstrates how robust program controls turn a massive, volatile wish list into a realistic, deliverable, and politically viable $12.5 billion baseline.

Availability, maintainability, and reliability are the main tenets of the standard OSD RAM-C report. The RAM-C report documents and tracks the sustainment and support metrics of a fielded system throughout its lifecycle. How are these metrics determined, and how do they relate to the overall concept of system affordability? The methodology behind these optimizations is rudimentary but are informative for both cost analysts and systems engineers involved in conducting trade-off analysis during early-life cycle conceptual design of a system. This topic will illustrate these interactions through a time-stepped simulation of system use, maintenance, failures, repairs, and associated costs

Many project challenges can be traced to decisions made before risks, costs, and value opportunities are fully understood. This session introduces the fundamentals of a phase-gate project controls framework and explains how risk management and value engineering work together to support better project decisions. Attendees will learn how structured gate reviews help teams evaluate scope, cost, schedule, and project risks before advancing to the next phase. Using practical infrastructure examples, this presentation provides young professionals with a simple, repeatable approach to improving project outcomes, reducing rework, and delivering greater value throughout the project lifecycle.

Extension of Time (EOT) claims are a fundamental part of construction project management, requiring both contractual compliance and sound schedule analysis. This session introduces the core principles of evaluating project delays using dynamic schedule analysis that reflect changing project conditions rather than static schedule assessments. It explains how changes in the critical path and near-critical activities can influence EOT entitlement and why understanding these concepts is essential. Through practical examples and industry best practices, the session provides young professionals with a foundation for understanding dynamic schedule analysis and its role in fair, transparent, and well-supported EOT evaluations.

Cost, schedule, and scope are the three fundamentals every project controls practitioner is trained to manage. Yet on too many projects, they're tracked in isolation. Cost reports live apart from schedule updates. Percent-completes get reported without tying back to either. The result is data without control. Without a performance measurement baseline that integrates all three, teams end up reacting to problems instead of predicting them. Earned Value Management gives practitioners something few other methods can: an objective, integrated view of cost, schedule, and scope performance that supports early trend identification, reliable forecasting, and defensible decision-making. This session examines how EVM operationalizes these core project controls principles, resulting in relevant data management can act on. Rather than framing EVM as a compliance exercise, this session makes the practitioner's case for it: Why integrating cost and schedule performance measurement produces better project outcomes, and what it takes to apply EVM effectively as a working discipline rather than a reporting formality. Attendees will leave with practical arguments for elevating earned value from a nice-to-have to a foundational project controls practice.

Traditional Earned Value Management (EVM) has significant limitations for schedule control because its schedule measures are cost-based, aggregate, and can lose meaning at project completion. This presentation introduces Earned Time Management (ETM), a fully time-based method that measures schedule performance from the activity level through lags, overlaps, paths, and the critical path. ETM does not require cost or resource loading and can be used with tools such as Primavera P6 and Microsoft Project. The presentation also demonstrates how ETM forecasts finish dates under diEerent performance assumptions and supports schedule-recovery decisions

Capital programs invest heavily in PMIS platforms, scheduling tools, and AI-enabled solutions, yet project teams still rely on spreadsheets and offline trackers to manage critical information. These shadow systems are rarely technology failures. They are symptoms of weak project controls fundamentals: gaps in governance, work breakdown structures, change control, data ownership, and reporting quality. Drawing on lessons from large-scale digital transformations, this session shows how technology amplifies strong project controls processes but cannot replace them. Attendees will learn to identify the control deficiencies behind shadow systems, apply a simple diagnostic framework, and strengthen the fundamentals that drive predictable outcomes.

The construction industry has often adopted new technologies unevenly across capital project delivery. As artificial intelligence reshapes capital planning, project controls, and project execution, many organizations continue to struggle to achieve the outcomes they expect. While AI promises to transform forecasting, reporting, risk management, and decision-making, stakeholders often lose confidence when these capabilities are applied to fragmented workflows, disconnected systems, and inconsistent data. This session outlines a practical roadmap for AI adoption in regulated capital infrastructure environments by addressing the critical relationship between process, data, and technology transformation. Before AI can deliver measurable value through automated reporting, predictive analytics, and intelligent risk management, organizations must establish standardized delivery processes and harmonize information across project controls, project delivery, capital investment planning, financial management, and business objectives. The result is a connected data foundation that reduces inconsistency across the broader asset lifecycle. The success of deploying AI in regulated, safety-critical environments rests on three foundational elements: establishing repeatable and disciplined business processes, creating trusted and integrated data, and implementing a phased approach to technology transformation. In simple terms, process creates repeatability, data creates visibility, and AI creates leverage. By connecting project intelligence to the broader capital infrastructure and asset management ecosystem,