The stakes are always high in large capital projects where budgets run into billions and timelines are measured over the years. Yet, the harsh reality is that only 35% of projects are successful, according to the Standish Group, an international IT research advisory firm. The group also found that with US $48 trillion spent annually on projects worldwide, even marginal improvements in success rates could yield significant financial gains. Enter artificial intelligence (AI), a technology poised to redefine how projects are planned, executed and delivered. Global management consulting firm McKinsey estimates that the long-term opportunity presented by AI could add in the range of US $2.6 trillion to $4.4 trillion in business value across industries.  

The question is no longer whether AI will disrupt project management, but how organizations can capitalize on its potential to drive better outcomes.  

In this blog, we will explore how companies can future-proof their organizations for the AI-driven era of project management by establishing the right data foundation, enabling them to reap the most benefits from this transformative technology.

From Manual Chaos to Intelligent Systems  

Project management has long been bogged down by inefficiencies. Teams often rely on outdated tools such as spreadsheets and fragmented systems that create data silos. These disjointed systems hinder visibility, impede collaboration and lead to poor forecasting, ultimately costing organizations millions. For example, it's estimated by CrowdFlower, provider of a “data enrichment” platform, that 80% of the work of data scientists is spent on preparing and managing data. This is a colossal waste of resources in an era where time is money.  

Additionally, these tools are inadequate for an environment where projects and initiatives constantly adapt and continuously change the business. "While there has been improvement in project portfolio management applications, planning and team collaboration capabilities, automation and 'intelligent' features are still lacking," states the Harvard Business Review.

AI offers a way out of this quagmire. AI will provide an added layer of intelligence that accelerate workflows and reduces human error, helping organizations enhance productivity and complete projects faster and more efficiently. However, the value provided by AI is largely dependent on the quality of the prompts and data it is fed.  

Hence, organizations poised to benefit the most from AI are the ones willing to invest in a solid data foundation today. According to McKinsey, high performing organizations tend to have a clear data strategy, centralized governance processes for data quality and management and clear data ownership structure.  

Additionally, Research firm Gartner predicts that by 2030, AI will eliminate 80% of traditional project management functions. While this doesn't mean project managers will become obsolete, it does mean their roles will evolve to exploit AI insights for higher-value activities.  

Project professionals will find themselves honing more of their project-related expertise rather than dealing with manual, administrative tasks. Take risk management as an example. According to a survey conducted by the Project Management Institute, 64% of respondents who adopted GenAI for risk management and identification saw an increase in productivity.  

These gains are not just theoretical; they translate into real-world efficiencies and cost savings.  

The Foundation: High-Quality Data  

Despite its remarkable potential, AI is only as good as the data it's trained on. Incomplete, inconsistent and biased data can lead to flawed AI outputs, undermining decision-making processes. As Forbes states, “AI is only as good as the data that trains it”.  

But what constitutes ‘complete data’? It must be accurate, consistent, timely, valid and unique. Achieving this level of data quality requires organizations to address longstanding challenges in data management. The primary culprits are the lack of standardization, manual processes and siloed systems.

For instance, teams operating independently often produce fragmented datasets, making it impossible to achieve a clear and comparative view of project performance.

By automating repetitive tasks such as data collection, tracking and reporting, companies can streamline operations and prepare to fully capitalize on AI, ensuring they stay competitive in the future.

This is where digital transformation becomes critical. By adopting an Enterprise Project Performance (EPP) approach, organizations can create a "digital spine" that integrates planning, design, execution and asset management into a single ecosystem. This connected landscape not only improves visibility but also enables predictive analytics, portfolio optimization and better decision making, capabilities that enhance AI's value and impact.  

AI in Action

The benefits of AI in projects extend across the entire project lifecycle. Consider the following examples:  

• Predictive Cost Forecasting: AI algorithms can accurately analyze historical cost data to predict future expenses for similar projects, allowing project professionals to allocate resources more effectively.  
• Portfolio Optimization: By analyzing multiple projects simultaneously, AI can identify synergies and conflicts in relation to strategic goals, enabling organizations to more effectively prioritize their initiatives.  
• Decision Guidance: AI-powered tools can provide actionable insights, helping teams decide when to pivot, scale or terminate a project. This reduces the risk of costly mistakes.  

The Human Element: AI as a Partner, Not a Replacement  

While AI offers unprecedented capabilities, it is not a panacea. Human oversight remains essential to validate AI outputs and enact decision-making. As Jonathon Montalvo, Senior Solution Consultant at Hexagon’s Asset Lifecycle Intelligence division, cautions in a recent webinar, "Don't take AI results as gospel. Don't set it and forget it."  

This underscores the need for a collaborative approach where AI augments human expertise rather than replacing it.  

Moreover, the adoption of AI requires a cultural shift. McKinsey found that employees are more prepared for AI than their leaders realize. However, while a slight majority are AI optimists, a significant portion (41%) feel anxious and will require additional support. Leaders need to embrace their role as AI change agents, ready to rewire the enterprise.  

Future-Proofing Projects: Building for Tomorrow  

To fully harness AI's power, organizations must embrace a mindset of continuous improvement and adaptability. While AI offers immense potential to streamline project management, its effectiveness hinges on the quality and connectivity of the underlying data. Implementing an Enterprise Project Performance (EPP) approach provides the foundational infrastructure to consolidate disjointed systems, enabling seamless collaboration and data cross-functionality across all roles and project phases across an organization.

Today’s leading project organizations are turning to Hexagon’s EPP solution, EcoSys, not only as a powerful tool for planning and managing projects, but also as a centralized data hub to support AI-driven technologies. By providing a reliable foundation of structured project data, EcoSys enables more accurate prompts and intelligent automations. The result: reduced risk of error, improved project outcomes and the capacity for teams to successfully take on more projects with greater confidence. 

By establishing a single digital spine via EcoSys, organizations can reveal valuable insights into cost and schedule performance, compliance and risk management, ensuring that teams can quickly make informed decisions. This centralized approach drives productivity and profitability and lays the groundwork for future AI integration, scaling as technology and business needs evolve.

See how an EPP solution like EcoSys can enable your organization to make the most of upcoming AI advancements.  

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