Insights

Building the foundation for intelligence-driven decision-making

artificial intelligence

This second blog exploring Beroe’s latest report from its Future Visions series, “Artificial Intelligence: Real Decisions”,  outlines what it truly takes to enable intelligence-driven decision-making, moving beyond the hype around new tools to focus on the structural capabilities that really matter. In today’s high-stakes procurement landscape, making confident, strategic decisions is tougher than ever, especially when procurement teams are overloaded with fragmented data and navigating tools that don’t talk to each other. 

Building the foundation for intelligence-driven decision-making 

Procurement decisions today are more consequential and more complex than ever before. Yet teams are still making these decisions using incomplete data, unconnected tools, and limited visibility. The result of this is a high-cost, low-confidence environment where intuition too often fills the gap. 

 To enable smarter, faster, and more strategic procurement, organizations must build the right foundations. This isn’t about adopting the latest toolset. It’s about addressing the systemic barriers that block decision-making and investing in the capabilities that move teams from data to action, at speed. 

 At Beroe, we see three critical pillars underpinning intelligent procurement decision-making: 

 1. Data Excellence  

From fragmented inputs to trusted intelligence Most procurement organizations are data-rich but insight-poor. Information is scattered across ERP systems, supplier portals, market feeds, and analyst reports. These systems are rarely harmonized, often duplicated, and seldom contextualized. This fragmentation forces teams to spend time collecting data that should be spent interpreting it.  

 What’s needed is not just more data, but better data. This means data that is: 

  • Relevant to the decision at hand 
  • Structured and standardized across sources  
  • Timely, so decisions aren’t made on outdated inputs 
  • Traceable, with clear provenance and auditability 
  • Enriched with context, so procurement professionals understand not just what has changed, but why those changes matter 

 Without this, AI applications will underperform, automation will hit a ceiling, and human judgment will be constrained by partial views. Data excellence is the prerequisite for intelligence at scale. 

2. Intelligent Recommendations: Moving from reporting to guided action  

Traditional procurement tools generate reports. But do they really support better decision-making? Instead, what is needed are recommendations that are contextual, prioritized, and aligned to business goals. 

 The challenge is that most decision-making environments are still geared toward monitoring, not guidance. While the procurement dashboards may now have moved from Excel to Tableau/Power BI to web apps (maybe even with some natural language querying), it still falls to the procurement professionals to sift through and make sense of scattered data and infer next steps. To compound matters, this decision-making process is often conducted under time pressure and without clarity on trade-offs. 

 Intelligent recommendations shift this dynamic, enabling procurement teams to: 

  • Receive proactive signals about risk, opportunity, or market change 
  • See prioritized options that factor in cost, risk, ESG, and operational and cross-functional impact 
  • Understand the reasoning behind suggestions, building trust, and enabling faster action 
  • Simulate different scenarios to explore the implications of each decision 

 3. Simplicity and Relevance: Reducing noise, increasing confidence 

Procurement operates in a high-stakes, high-volume environment. Cognitive overload is real and growing. That’s why the most effective intelligence isn’t just accurate, but simple, timely and relevant. Tools and insights must be designed to reduce friction and deliver what is needed, when it is needed, and in a format that matches how teams work. 

 This includes: 

  • Role-based insights tailored to individual users 
  • Natural language interfaces that allow fast, intuitive queries 
  • Integrated delivery into platforms procurement teams already use (such as Microsoft Teams, Slack etc.) 
  • Multi-format content (text, audio, visual) that aligns with modern workflows 

 If intelligence adds complexity, it won’t be adopted, and if the results AI produce is just creating yet more data, it will hinder decision-making. 

 Key takeaway 

Together, these three pillars form the operating system for intelligent procurement decision-making: a foundation that enables decisions to be made faster, and with greater context, consistency and confidence. 

 Look out for the next blog is this series which aims to understand how AI can be applied, not for the sake of innovation, but to strengthen decision-making at every point in the procurement process. 

 “Artificial Intelligence: Real Decisions” explores how leading procurement teams are using AI today to strengthen decision-making across key domains spanning insight generation and risk forecasting to supplier engagement and strategic sourcing.  

Download the full report here.