Seven years later: Charting procurement’s digital roadmap from automation to AI-driven human augmentation

We continue our Procurement Transformation Guide by hearing from Sammy Rashed, a productivity advisor and procurement strategist.

For the past 12 years, Sammy Rashed has applied the experience he gained from being a procurement and strategic sourcing leader at Novartis and Merck to serve as the expert facilitator of several practitioners-only Procurement Think Tanks globally. Spend Matters asked him to revisit his earlier theme of creating a digital transformation roadmap and update those insights to reflect his current focus expansion into AI and human augmentation for the Spend Matters Digital Procurement Transformation Survival Guide. Here’s what he had to say.

Introduction

Seven years ago, procurement organizations faced immense pressure to evolve — balancing operational efficiency with strategic agility in an increasingly digital world. Our 2017 Procurement Think Tank explored how digitalization could unlock significant opportunities, guided by Bill Gates’ insight: “We always overestimate the change that will occur in the next two years, and underestimate the change that will occur in the next ten.” Today, this wisdom reveals both our foresight and blind spots as procurement aims to embrace artificial intelligence and human augmentation.

Revisiting the original digital roadmap

The Think Tank members are practitioners who gather annually to ASSESS, ANALYZE and SOLVE a common problem. Their hands-on experience ensures that everything described here comes directly from ‘people in the trenches’ — procurement professionals facing these challenges daily. So our journey began with a pressing question: How should procurement teams digitally transform?

Initially, we proposed a linear, sequential model with clear milestones — from P2P automation and insights analytics through cognitive technologies and collaboration platforms to procurement-as-a-service, culminating in enterprise-wide digital enablement. Through intense discussions, we recognized this sequential path was overly rigid and impractical. The complexity and interdependency of processes led us to reshape our approach into a more nuanced, dual-towered roadmap (Figure 1):

• Operations efficiency tower: Progressing from individual and functional automation to robotic process automation (RPA) and AI-driven cognitive tools.

• Data insights tower: Advancing from basic descriptive analytics through diagnostics to sophisticated predictive and prescriptive analytics.

Figure 1

Source: Sammy Rashed

Central model explained: Building the digital roadmap

This model — built on our understanding at the time of ‘traditional AI’ — emphasized the integrated, parallel nature of operational automation and insightful analytics rather than strictly sequential progression. The ‘Twin-Tower’ framework linked operational improvements directly to insight quality:

1. Starting with basic technology and automation, organizations improve processes, collect essential data and establish clearer insights about what happened (descriptive) and why (diagnostic).
2. By implementing RPA and smart workflows, organizations enhance data accuracy and operational efficiency while reducing human error.
3. These operational improvements enable more reliable predictions of future events (predictive analytics).
4. This robust foundation of improved processes and quality data ultimately empowers procurement teams to leverage prescriptive analytics and advanced AI, automating strategic decision-making and unlocking digitalization’s true benefits.

Key learnings from the last seven years

Initially, we believed robust data and perfected processes were absolute prerequisites for advanced digitalization. Reality taught us differently. Meaningful progress and tangible benefits emerged precisely at the intersection of smart workflows, RPA and predictive analytics — which significantly enhanced data quality.

A crucial shift emerged: Despite significant efforts, organizations struggled to perfect their processes and data, limiting progress. The transformative realization was that AI itself could help address these challenges — actively improving processes and cleansing data. AI evolved from being perceived as dependent on good data and processes to becoming a key enabler that can improve both.

Current state: From digitalization to AI-driven human augmentation

With the rise of GenAI two years ago, our focus evolved to exploring where AI can be used and how it can actively augment procurement’s ways of working.

To narrow our aim, the group focused on answering eight practical questions around AI Usage, Strategy, Capabilities and Organizational impact (Figure 2):

Figure 2

Source: Sammy Rashed

This approach provided valuable insights, highlighting how quickly AI capabilities have evolved from initial awareness to broad adoption. Despite rapid progress, procurement teams often feel they are chasing rather than keeping pace with technology’s swift advancements.

A foundational step was thoroughly reviewing the entire procurement process (including Strategy, S2C, P2P and SRM) to identify precisely where AI:

• Should be implemented immediately.
• Could be beneficial in the medium term.
• Should be deferred.

Considerable effort went into upgrading internal capabilities and methods to support effective AI adoption. Even with growing understanding and enthusiasm, pinpointing exactly where and how to begin remained challenging due to multiple influencing factors. Nevertheless, consensus emerged around a structured roadmap outlining clear adoption steps for years 1, 2 and 3, as proposed by Horvath (Figure 3).

Figure 3

Source: Horváth

Current opportunities: How new AI changes the game

Recent developments, particularly in generative AI, have reshaped how procurement teams approach digital transformation. While reliable data and a clear roadmap remain critical prerequisites, AI’s role has evolved significantly. Instead of bypassing foundational steps, GenAI actively supports cleansing, structuring and enriching data, facilitating quicker progress and smoother adoption. This marks not a shortcut, but the beginning of a second wave of AI-driven transformation.

Furthermore, new AI capabilities demand new skills. Organizations increasingly recognize AI as a critical topic, focusing on upskilling and nurturing a robust organizational culture that embraces innovation, adaptability and continuous learning to sustain transformation. Procurement teams need to urgently invest in fostering these new competencies, ensuring their workforce is ready to leverage AI effectively.

Aspiration and future vision

Our aspiration extends beyond mere automation to genuine human augmentation. This vision includes frameworks for augmented thinking, personalized AI agents for enhancing individual productivity and a comprehensive repository of reliable AI practices. The goal is to ultimately free procurement professionals from repetitive tasks, allowing them to concentrate on strategic, high-value activities and achieving true augmentation of human capabilities.

Conclusion: Bridging past, present and future

Reflecting again on Bill Gates’ insight, we are reminded to continuously adapt our vision, as digital transformation and AI augmentation are iterative, evolving processes rather than fixed endpoints. Procurement organizations must now focus beyond data alone — urgently investing in skills, cultivating a culture of adaptability and innovation and defining actionable starting points.

Leaders should begin by establishing clear AI strategies, identifying practical early use-cases and systematically developing their teams’ AI-related competencies. By actively leveraging AI, procurement can overcome traditional data and process hurdles and accelerate its strategic value. This proactive stance transforms procurement from a reactive, operational function into a future-ready strategic partner, fulfilling the ambitious vision we set seven years ago and driving meaningful human augmentation in procurement practices today.