From Project Controls to Programme Intelligence

Contents

The GCC is still building at scale.The question is how to stay in control.

The GCC remains one of the world's most active major capital programme markets. Infrastructure, aviation, logistics, real estate, energy, utilities and transport programmes continue to support national transformation agendas and long-term economic diversification across the region.

The delivery environment, however, is becoming more complex. Regional disruption, supply-chain pressure, shifting award patterns, regulatory development, cybersecurity requirements and rapid AI adoption are creating new challenges for major programme owners. The market itself remains substantial: contract awards reached US$61.2 billion in Q1 2026 and US$59.4 billion in Q2 – still 30% higher than the same period last year, while Kamco Invest / MEED report a longer-term pipeline of around US$2.05 trillion of upcoming GCC projects, 26.1% of it in the UAE.

Against this backdrop, three insights matter most.

1. 01

   Major programme delivery is now shaped by volatility as much as scale.

   Owners are no longer managing large capital commitments in a stable environment. They are managing shifting market conditions, supply-chain disruption, cost movement, contractor appetite, procurement timing and schedule risk. Timely, connected and reliable information has become essential to maintaining control.

2. 02

   The next performance frontier is connected programme intelligence.

   Major programmes already generate large volumes of cost, tender, procurement, market, risk, schedule and performance data, but it often sits across disconnected systems, reports and teams. The opportunity is to convert fragmented project data into a secure intelligence layer that improves decisions across the full programme lifecycle.

3. 03

   AI can improve performance, but only when it is secure, governed and human-led.

   Technology has an important role to play, but adoption alone does not create value. The challenge now is moving AI from experimentation into trusted, repeatable professional workflows without replacing professional judgement. 2026 research from the Royal Institution of Chartered Surveyors (RICS) shows AI use growing rapidly across construction and commercial property while widespread integration remains rare, reinforcing the importance of governance, data, integration and human oversight as adoption scales.

The GCC major programme market remains large, but increasingly volatile

The GCC projects market remains significant, but 2026 data points to a more selective and changeable environment. Contract awards reached US$61.2 billion in Q1 2026 before easing to US$59.4 billion in Q2. Although Q2 awards were lower than the previous quarter, they were still 30% higher than the same period last year, evidence of a market that remains active even as timing, prioritisation and risk conditions shift. Kamco Invest / MEED also report a longer-term GCC project pipeline of around US$2.05 trillion, with the UAE accounting for 26.1% of it.

In the UAE, project awards reached US$29.2 billion in Q1 2026, down 18.5% year-on-year, with transport representing the largest share of new awards. This reinforces the importance of live market intelligence in sectors where procurement strategy, cost planning and delivery decisions are closely linked to public outcomes, long-term infrastructure capacity and changing market conditions.

The macroeconomic context adds further pressure. PwC Middle East's May 2026 Economy Watch highlighted disruption to oil exports, trade and supply chains as factors reshaping the GCC outlook, citing the IMF's April 2026 forecast of 1.8% GCC GDP growth in 2026, down from a previous 4.4%. The World Bank's April 2026 MENAAP Economic Update projects GCC growth slowing from 4.4% in 2025 to 1.3% in 2026.

Publicly disclosed regional programmes also show why the challenge is not only about market size. These are multi-year, multi-package programmes with complex interfaces, significant capital commitments and fixed public outcomes; portfolios of interdependent packages, stakeholders, procurement decisions, cost plans, risks, approvals and delivery milestones. At that scale, the value of programme intelligence compounds: a single cost plan, tender return or progress report may support one decision, but structured and reused across packages, it becomes a strategic asset.

For major programme owners, cost, procurement and delivery decisions need to be informed by live intelligence, not static assumptions. That leads directly to the next challenge: volatility is now affecting programme delivery, not only cost.

Volatility is now a programme intelligence issue

Regional volatility is no longer confined to material price escalation. It affects procurement strategy, logistics, contractor appetite, programme certainty, contract administration, claims risk and delivery momentum.

Omnium International's Market Intelligence Bulletin: Geopolitical Risk & Cost Update, issued on 17 April 2026, described an active GCC risk environment affecting supply chains, procurement, programme, contract administration, safety and overall project delivery, noting extending lead times, risk premiums entering the market and uncertainty affecting decision-making across the project lifecycle. The report identified trends highly relevant to major programme owners: disruption to maritime and airfreight routes, pressure on UAE transshipment flows, longer lead times for critical materials, contractor force majeure and extension-of-time notices, risk premiums in new tender submissions and uncertainty around contractor appetite.

Selected cost movements illustrate why traditional cost plans can quickly become outdated.

Major programmes still struggle with cost, time and disputes

The difficulty of delivering major programmes is not new. Bent Flyvbjerg, a leading academic in megaproject management and former Professor at Oxford's Saïd Business School, has spent decades researching cost overruns, schedule delays, optimism bias and strategic misrepresentation in large infrastructure and capital projects. His 2014 paper estimated global megaproject spending at US$6–9 trillion annually, around 8% of global GDP, and described the "iron law" of megaprojects: over budget, over time, over and over again.

Industry data points in the same direction. HKA's Eighth Annual CRUX Insight Report, published in November 2025, analysed more than 2,200 projects across 114 countries with combined capital expenditure of US$2.433 trillion, and found contractor time extensions sought averaging 65.8% of planned schedules.

The Middle East is particularly exposed to schedule claims. HKA's regional analysis reports contractors in the Middle East claiming extensions of time averaging 80.9% of planned schedules, against a 66.5% global average, with claimed costs amounting to 34.0% of budgeted capex.

These patterns show why traditional project controls can be insufficient: they often explain what happened after the risk has already crystallised. The next step is to use data and AI to identify emerging risk earlier, but that only works when the technology is governed properly.

AI-enabled delivery is moving from concept to execution

AI is now moving into practical capital project delivery. McKinsey's July 2026 analysis of AI in architecture, engineering and construction put global construction output at around US$15 trillion in 2025, with projected demand reaching US$22 trillion by 2040, and estimated that AI and automation could unlock around US$228 billion of annual value in the US AEC sector by 2030.

The wider industry is reaching a similar inflection point. The Royal Institution of Chartered Surveyors' (RICS) AI in Commercial Property and Construction Report 2026, based on more than 3,100 industry responses globally, found around two-thirds of construction respondents now using AI in some part of their work, and more than three-quarters of commercial property respondents reporting some level of use. Embedded adoption, however, remains limited: early-stage pilot activity sits at around 39% in both sectors, while widespread or full integration is only around 4% in construction and 6% in commercial property.

RICS describes this as a "pilot-to-production gap". The barrier is increasingly not access to AI, but the ability to convert successful experimentation into routine professional practice, which makes data quality, systems integration, security, skills, supervision and governance progressively more important as adoption increases. For major programme owners, the objective should not be to deploy more AI for its own sake, but to establish the operating environment in which useful AI applications can be adopted securely, integrated with existing information and controls, and scaled with appropriate professional oversight.

This supports the evolution of portfolio-wide performance platforms. AI-enabled analytics can help teams identify early warning indicators, test schedule scenarios, understand critical path sensitivity, assess procurement sequence risk and spot emerging delivery pressure across a portfolio.

Governance, regulation and professional standards are raising the bar

The GCC is moving quickly on AI, data and digital government, and 2026 has been a landmark year for the UAE in particular.

Data protection and cybersecurity are equally important. The UAE's Federal Decree-Law No. 45 of 2021 provides the federal framework for personal data protection. Saudi Arabia's Personal Data Protection Law required organisations to take compliance measures by 14 September 2024, and Saudi Arabia's National Cybersecurity Authority has updated its Cloud Cybersecurity Controls as CCC-2:2024.

International frameworks reinforce the same direction. ISO/IEC 42001:2023 is the world's first AI management system standard, while NIST's AI Risk Management Framework and Generative AI Profile provide guidance for trustworthy and responsible AI risk management.

• UAE · KSA data law

  Federal Decree-Law No. 45 of 2021 (UAE) and the Saudi PDPL set the regional bar for personal data protection.

• ISO/IEC 42001:2023

  The world's first AI management system standard, a governance frame for enterprise AI adoption.

• NIST AI RMF

  Risk management framework and Generative AI Profile for trustworthy, responsible AI.

Professional standards are also evolving, led by RICS, whose first global standard for the responsible use of AI in surveying practice came into effect on 9 March 2026.

The RICS AI Standard: professional judgement at the centre

RICS' 2026 industry research shows why the standard matters. As AI use has increased, privacy and security concerns in construction have risen from 22% to 30%, while widespread operational integration remains uncommon. RICS argues that the next phase of adoption requires organisations to plan explicitly for how pilots become routine practice, including the data, integration and supervision needed to support them.

Its recommendations are practical: assess AI use against the RICS AI Standard; document where AI has contributed to professional outputs, including the tools, data and points of human review involved; use enterprise-grade tools where client data is concerned; and establish clear protocols for AI-assisted professional work. As adoption matures, RICS expects organisations to embed explainability, human oversight, audit trails and demonstrable accountability into client-facing AI processes.

RICS guidance places professional skill, judgement, oversight and output reliability at the centre of responsible AI use. Its July 2026 commentary goes further: where AI is used materially, clients should be told when it will be used, how its use can be challenged, what rectification exists and whether opting out is possible.

RICS also identifies a wider role for the profession in enabling responsible scale; sector-specific guidance and case studies, expanded AI CPD, greater awareness of the AI Standard and the relaunch of the RICS Tech Partner Programme, with technology partners expected to align with the Standard and, over the medium term, a more structured framework to help professionals evaluate technology against its responsible-AI requirements.

People-based capability remains the core of assurance

Major programmes involve judgements that are not purely computational. A platform can flag a tender anomaly, but a commercial professional must decide whether it is a scope gap, a pricing strategy, a genuine risk or harmless variance. A platform can surface schedule risk, but project leaders must decide what intervention is appropriate. A platform can generate benchmarks, but cost planners must decide whether the reference class is valid.

RICS' 2026 standard reinforces this principle by requiring professional judgement, oversight and reliability assessment wherever AI materially affects surveying services. RICS' Surveying Skills Report (October 2026) shows how scarce that judgement now is: 54% of professionals report critical or moderate skills shortages, driven above all by too few mid-career, experienced professionals, and only 9% feel well prepared to use generative AI. AI competence alone is not enough without the domain knowledge to interrogate and challenge AI-generated outputs. Responsibility remains with appropriately qualified professionals, it does not transfer to the technology.

Human-in-the-loop is therefore not a conservative fallback, it is an essential assurance mechanism. It protects clients from over-reliance on automated outputs, supports defensible decisions and keeps accountability with appropriately qualified people.

It is also how adoption scales. Teams trust AI-enabled workflows when outputs are transparent, source-linked, reviewable and challengeable. Leadership supports adoption when there is a clear audit trail. IT and cybersecurity teams approve deployment when data boundaries, access controls and retention rules are defined. With that foundation in place, major programme owners can move from isolated project controls to connected programme intelligence.

Advanced programme thinking points to connected intelligence

Leading programme thinking is moving away from isolated project controls and towards integrated delivery models, reference-class intelligence, shared data, better governance and portfolio-level decision support.

Flyvbjerg's work supports the use of an "outside view": comparing projects against actual outcomes from relevant reference classes to challenge optimism and improve forecast reliability. Nuno Gil, Professor of New Infrastructure Development at Alliance Manchester Business School, focuses on megaproject governance, value creation, value distribution and multi-party decision-making. His research describes megaprojects as complex organisational systems where governance evolves over the lifecycle, and where performance depends on how stakeholders align around purpose, value and decision-making, especially relevant to GCC programmes, which bring together government entities, developers, consultants, contractors, operators, regulators, funders and supply chains with different priorities and decision rights.

The same shift appears in practice. The UK Infrastructure and Projects Authority's Transforming Infrastructure Performance: Roadmap to 2030 promotes better use of data, digital approaches, benchmarking and modern delivery models, and its Data Analytics and AI in Government Project Delivery framework sets out how public project organisations can use data analytics and AI to improve delivery. Project 13, sponsored by the Institution of Civil Engineers, similarly promotes an enterprise model for infrastructure delivery, moving beyond transactional delivery towards integrated, outcome-focused collaboration.

From fragmented data to programme intelligence

Major programmes generate valuable intelligence throughout the lifecycle. Cost plans reveal assumptions and confidence levels. Tender returns expose live market behaviour. Clarifications, qualifications and exclusions show how bidders understand risk. Awards capture real pricing. Variations, delay events, progress reports and disputes provide evidence of scope pressure, performance risk and lessons learned.

Too often, this information is captured once, used once and left behind in documents, spreadsheets, reports or disconnected systems.

The opportunity is to create a programme intelligence flywheel.

This is the environment where IOX is designed to help. The IOX platform brings tender intelligence, commercial data structuring, cost modelling and portfolio-level performance analytics together within a secure, governed, human-in-the-loop intelligence layer, designed around the principles increasingly required for enterprise AI adoption: controlled data environments, traceable sources, defined professional review, auditability and clear accountability.

IOX is not designed to replace existing enterprise systems, consultant teams or professional controls. It is designed to connect the data and intelligence that already exist across the programme, and make them more usable, traceable and decision-ready.

One connected platform, four capabilities

• ioMaster

  Faster Investment Decisions

  • •Rapid feasibility studies
  • •Investment testing and scenario modelling
  • •Earlier cost-informed decisions
  • •Reduced pre-commitment risk
• ioProcure

  Tender Analysis Accelerated

  • •Reduce tender analysis effort by up to 80%
  • •Accelerate procurement decisions
  • •Improve commercial governance
  • •AI-enabled, auditable workflows
• ioInsight

  Cost Intelligence at Speed

  • •Rates and benchmark data
  • •Supplier performance intelligence
  • •Market cost movement tracking
  • •Single source of commercial truth
• ioInsight

  Programme-wide Cost Insight

  • •Portfolio-wide procurement visibility
  • •Commercial risk and delivery
  • •Proactive risk identification
  • •Increased investor confidence

Sources and references

• Kamco Invest / MEED Projects

  GCC Projects Market Update, Q1 2026. GCC contract awards of US$61.2bn in Q1 2026, down 9.7% year-on-year. Accessed August 2026 via Mubasher summary.

• Kamco Invest / MEED Projects

  GCC Projects Market Update, Q2 2026 / July 2026. Q2 2026 GCC awards of US$59.4bn, down 25.4% quarter-on-quarter; Saudi awards of approximately US$30bn.

• Kamco Invest / MEED Projects

  GCC project pipeline, July 2026. US$2.05tn of upcoming GCC projects, with the UAE accounting for 26.1% of the pipeline. (Arab News)

• Kamco Invest / MEED Projects

  UAE Projects Market Q1 2026. UAE Q1 2026 awards of US$29.2bn, down 18.5% year-on-year, with transport as the largest sector share. (Mubasher)

• PwC Middle East

  Middle East Economy Watch, May 2026. Disruption to oil exports, trade and supply chains; cites IMF April 2026 GCC GDP growth forecast of 1.8% for 2026.

• World Bank

  MENAAP Economic Update, April 2026. GCC growth slowing from 4.4% in 2025 to 1.3% in 2026 after a 3.1 percentage point downgrade since January.

• Omnium International

  Market Intelligence Bulletin: Geopolitical Risk & Cost Update, Omnium Insights Issue 01, 17 April 2026. Regional practitioner report on GCC supply-chain, cost, procurement, programme and delivery risk.

• Omnium International

  Selected cost and delivery indicators, 17 April 2026. Diesel price movement, selected material cost impacts, logistics disruption, tender risk premiums and delivery risk commentary.

• Bent Flyvbjerg

  "What You Should Know about Megaprojects and Why: An Overview," Project Management Journal, April/May 2014. Global megaproject spending, cost and schedule underperformance, and the "iron law" of megaprojects. (Sage Journals)

• HKA

  CRUX Insight Eighth Annual Report: From Insight to Foresight, November 2025. More than 2,200 projects across 114 countries. (HKA)

• HKA

  Managing risks and claims in Saudi Arabia / Middle East CRUX analysis. Middle East EOT claims averaging 80.9% of planned schedules; claimed costs of 34.0% of budgeted capex.

• McKinsey & Company

  "How AI is reshaping the future of the AEC industry," July 2026. Global construction output, projected demand and estimated AI/automation value opportunity.

• UAE Government / Dubai Media Office

  Agentic AI framework, April/May 2026. Framework to deploy Agentic AI across 50% of government sectors, services and operations within two years.

• UAE Cabinet

  Artificial Intelligence and Data Authority, 14 June 2026. Establishment of the national authority responsible for data, AI and digital government.

• UAE Government

  UAE Charter for the Development and Use of Artificial Intelligence, 3 July 2026. Charter focused on trusted, responsible and accountable AI development and use. (U.AE)

• RICS

  Responsible use of artificial intelligence in surveying practice, effective 9 March 2026. Global professional standard and supporting guidance on governance, oversight, professional judgement and output reliability.

• RICS

  AI in Commercial Property and Construction Report 2026. Global research based on 3,148 construction and commercial property professionals: adoption, readiness, barriers, investment and the pilot-to-embedded transition.

• RICS Modus

  "Opting out: three crucial questions on AI in surveying," 20 July 2026. Client disclosure, challenge, rectification and opt-out considerations where AI is used materially.

• RICS

  Surveying Skills Report 2026, October 2026. Global survey of 3,698 built and natural environment professionals: skills-shortage severity and drivers, AI preparedness and upskilling priorities.

• ISO

  ISO/IEC 42001:2023 Artificial Intelligence Management System. International AI management system standard.

• NIST

  Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, 2024. Guidance for trustworthy and responsible generative AI risk management.

• UK Infrastructure and Projects Authority

  Transforming Infrastructure Performance: Roadmap to 2030, 2021. Data, digital approaches, benchmarking and infrastructure performance improvement. (GOV.UK)

• UK Government / IPA, CDDO, APM, MPA

  Data Analytics and AI in Government Project Delivery, 2024. Framework for the use of project data analytics and AI in public project delivery. (GOV.UK)

• Institution of Civil Engineers

  Project 13. Enterprise model for infrastructure delivery, including digital transformation and integrated delivery thinking. (ICE)

• Nuno Gil

  Megaproject governance research, Alliance Manchester Business School. Megaproject purpose, value creation, value distribution and polycentric organising. (Taylor & Francis Online)

IOX - an Omnium × Innovaite joint venture