Throughout history, technological revolutions have fundamentally reshaped industries, business models and ways of working—often met with skepticism, resistance and fear before becoming indispensable. The rise of AI and Generative AI (GenAI) is no different.
Many procurement professionals and business leaders say, “We’re not there yet.” But the reality is, we are already there—just not in the way we might expect. AI and GenAI aren’t standalone tools waiting for adoption; they are already embedded in the ERPs, procurement platforms, customer service operations and communication systems businesses rely on every day. The question is no longer “Should we adopt AI?” but rather, “How do we understand and adapt to AI’s growing role in our work?”
To see why this shift is inevitable, let’s look at other major technological revolutions that transformed industries, workforces and business models in similar ways.
🔹 1. The Industrial Revolution: Mechanization of Work
🚀 What Happened?
- In the late 18th and early 19th centuries, the rise of mechanized production eliminated labor-intensive processes, shifting work from manual craftsmanship to machine-powered efficiency.
- Factories emerged, restructuring economies and leading to the creation of entirely new industries.
📌 AI Parallel: Just as machines automated physical labor, AI is automating cognitive tasks—from contract management to supplier negotiations and data analysis.
🌍 Lesson: People resisted industrialization at first, fearing job losses. Yet, it led to higher productivity, new job roles and new industries—a pattern we are already seeing with AI.
🔹 2. The IT Revolution: From Paper to Digital
🚀 What Happened?
- The rise of computers in the 1970s and 1980s transformed businesses, moving them from paper-based operations to digital workflows.
- Entire functions—finance, procurement, HR—became systematized through digital databases and ERPs like SAP and Oracle.
📌 AI Parallel: The IT revolution digitized data; AI now interprets and automates decisions based on that data.
- Early resistance: “We don’t need computers for this.”
- Today’s reality: Digital systems are the backbone of every major enterprise.
🌍 Lesson: Companies that failed to embrace digital transformation lost their competitive edge. AI and GenAI are the next layer on top of this digital infrastructure—those who ignore it risk falling behind.
🔹 3. The Internet Boom: Connectivity Reshaped Business Models
🚀 What Happened?
- The 1990s and 2000s saw the internet disrupt entire industries—retail (Amazon), travel (Expedia), media (Netflix).
- Traditional business models crumbled as online platforms introduced new ways to access products and services.
📌 AI Parallel: Just as businesses had to adapt to an always-online world, today they must adapt to an AI-integrated business environment.
- AI is already embedded in procurement software, CRMs and customer service chatbots.
- New AI-driven platforms may disrupt procurement, supply chain and decision-making models.
🌍 Lesson: Companies that dismissed the internet as a temporary trend struggled to survive. Ignoring AI’s role today could lead to the same fate.
🔹 4. Cloud Computing: Data Access and Automation
🚀 What Happened?
- The shift from on-premise servers to cloud computing in the 2010s allowed businesses to scale rapidly.
- Instead of owning infrastructure, companies relied on cloud-based SaaS models.
📌 AI Parallel:
- Just as companies gave up full control of their IT infrastructure in exchange for efficiency and scalability, AI is now doing the same for decision-making and automation.
- Procurement teams are already using AI without realizing it—in spend analytics, contract reviews and supplier risk assessments embedded in platforms.
🌍 Lesson: AI will not be an isolated tool—it will be embedded into the software businesses already use. The shift is happening whether we realize it or not.
🔹 Why AI & GenAI Are a Defining Shift (And Not Just Another Trend)
Unlike past technological changes that required hardware investments or physical infrastructure, AI is different because:
1️⃣ It’s already here: AI doesn’t require separate adoption—it’s being built into existing tools (ERPs, procurement platforms, supply chain systems).
2️⃣ Governments & Enterprises Are Investing Heavily: The EU, US and China are pouring billions into AI research, policies and regulations. Denmark alone has a national AI strategy to stay competitive
3️⃣ Data is more accessible than ever: AI thrives on data and today’s business world generates vast amounts of it. Public and proprietary datasets make AI more powerful than previous automation attempts.
4️⃣ Business models will evolve around AI: Just as the internet created new ways of selling, AI is creating new ways of operating—from automated procurement strategies to AI-driven contract negotiations.
🔹 The Real Question: How Do We Adapt to AI’s Integration into Business?
Instead of debating “Are we ready for AI?”, businesses must now ask:
✅ How do we ensure AI works for us rather than against us?
✅ Where does automation help and where do humans need to stay in control?
✅ How do we build governance and trust in AI-driven insights?
✅ What new skills and roles do we need to manage an AI-enhanced procurement function?
🔹 Final Thought: AI Is No Longer an If—It’s a How
We’ve seen this before—industries resist change, only to find that those who adapt first gain a competitive edge. AI is already embedded in the tools we use, the decisions we make and the way businesses interact with suppliers, customers and data.
The question is no longer “Should we use AI?”—the question is “How do we use AI responsibly, strategically and effectively?”
📌 History tells us that businesses that embrace technological shifts early don’t just survive—they lead. The same will be true for procurement, supply chain and business leaders in the age of AI.
This is what we will explore at EBG | Xperience in Copenhagen. 🚀
Join us to uncover how AI is already shaping procurement, how to leverage it wisely and how to remain in control of technology-driven transformation.
🔹 Final Note: Why Governments Are Increasing AI Funding Now
AI has been evolving for decades, but why are we seeing a surge in funding and policy action now? The answer lies in a combination of technological breakthroughs, competitive pressures and economic priorities that have pushed governments to accelerate AI investments at an unprecedented scale.
📌 The European Union has launched the €200 billion InvestAI initiative, which includes €20 billion for AI “gigafactories” to scale AI infrastructure and applications across industries (European Commission, 2024 + 2025).
📌 Denmark, Sweden, Norway and Finland have all implemented national AI strategies to drive AI research, innovation and ethical governance, with new initiatives such as a Nordic AI Center planned for 2025 (Nordic Innovation, 2024).
📌 AI R&D funding worldwide is at an all-time high, with the US, China and the EU competing to dominate AI leadership and establish strong regulatory frameworks to balance innovation with governance (BCG, 2024).
📌 Publicly available data, increased computing power and cloud infrastructure have made AI training and deployment significantly more scalable, driving mass adoption across industries (Copenhagen Economics, 2024).
This moment in AI development is not just about hype or future potential—it’s about governments and businesses recognizing AI as a foundational economic driver. The shift is no longer about whether AI will transform industries, but rather how it should be governed, integrated and leveraged responsibly.
👉 For procurement and supply chain professionals, this means AI will increasingly shape decision-making, efficiency and business models—whether they actively pursue it or not.
💡 Now is the time to explore how AI fits into existing workflows, ensures better insights and enables organizations to remain competitive in an AI-driven world.
📢 Resources & Further Reading:
🔗 European Commission (2024): EU InvestAI Initiative – Mobilizing €200 billion for AI investment
🔗 Nordic Innovation (2024): Nordic AI Center Initiative – A collaborative effort between Sweden, Norway, Denmark, and Finland
🔗 BCG Report (2024): Denmark’s GenAI Paradox – From Lagging to Leading
🔗 Copenhagen Economics (2024): Generative AI Partnerships – Separating Good from Bad