Understanding the Foundation for AI: Why Data is King

For UniPhi’s AI capabilities to truly take off and provide valuable, assured insights for informed business decision-making, a certain level and quality of data is essential.

Unlike large language models such as ChatGPT, which draw on vast amounts of publicly available information to summarise and answer questions, UniPhi’s AI for portfolio and project management relies entirely on your organisation’s own data.

This is what powers machine learning–based insights that can guide key decisions, from shaping business cases and pricing project quotes to forecasting resource requirements.

Key Concepts

• Data-Driven Decisions: The only way to unlock meaningful AI insights in UniPhi is to base them on your organisation’s data.

• Structured Data Advantage: UniPhi is a structured database with a semantic model embedded in its API (Application Programming Interface). This is ideal for building inferences and training machine learning algorithms, and helps avoid the “data sewers” that often arise from poorly managed, unstructured data lakes.

• Volume and Breadth of Data: AI for business decision-making requires significant amounts of high-quality data. For competitive advantage, your data should be broad, covering a wide range of scenarios and variables.

  
  

A real-world example comes from a large roads programme run across multiple sites in Sydney. Years of detailed work breakdown structures, timesheet data, issue tracking (including defects and design challenges), and commentary created a rich dataset.

This enabled accurate forecasting for future projects in terms of cost, timelines, and resource needs, the kind of insights that would be impossible without such breadth and depth of information.