In a few weeks I will be hosting the KonnectHouse Agentic AI in Procurement conference. Focused on the transformative impact of Artificial Intelligence (AI), I anticipate many diverse perspectives will be shared. But I am sure there is one commonality that will be underscored across the board – AI is no longer a futuristic concept but an immediate strategic imperative for businesses aiming to stay competitive and resilient.

The roles that make up procurement and supply chain functions are at a critical inflection point, with organizations increasingly relying on AI to make faster, more strategic sourcing decisions amidst volatile supply chains, rising costs, and talent shortages. While AI’s revolutionary potential is clear, its effective implementation requires a strategic, yet cautious enterprise-wide lens.

The Rise of Agentic AI: Beyond Automation

A central theme of Agentic AI is that it represents a major step forward from traditional generative AI. According to Deloitte’s 2025 Global CPO Survey, 94% of procurement executives now use generative AI at least weekly—a sharp rise from previous years. Yet, while generative AI adoption is becoming mainstream, Agentic AI is only beginning to emerge and demands a more integrated approach.

Generative AI is largely reactive—producing text, images, or other outputs in response to a prompt. Agentic AI, by contrast, is proactive and autonomous. These systems perceive their environment, make decisions, take actions, and pursue goals without constant human input. This shift moves AI beyond task automation toward autonomous decision-making and scaled action—a transformation with profound implications for procurement and supply chain operations.

Key Applications and Benefits in Procurement & Supply Chain

The potential applications of Agentic AI across procurement and supply chain are vast, promising to address long-standing challenges by analyzing large volumes of historical and real-time data to produce actionable insights. From my research, insights and pure curiosity on the topic, here are some key use cases that I am hearing from procurement and supply chain management leaders:

• Demand Forecasting: AI processes historical sales data, seasonality, promotions, and economic indicators to produce accurate forecasts, helping businesses anticipate market trends, optimize inventory, and allocate resources.
• Automated Sourcing & Negotiation: AI can semi-automate sourcing events, analyze RFP responses, and even conduct AI-based supplier negotiations, particularly for long-tail suppliers, freeing up human teams for more strategic tasks.
• Procurement Orchestration & Intake: AI-powered tools can serve as a “front door” for internal requests, translating needs into categorized choices and guiding users through appropriate approval channels.
• Supply Chain Optimization: By analyzing data from traffic conditions to fuel prices, AI can model multiple transportation and scheduling scenarios to reduce costs or shorten lead times.
• Supplier Risk Assessment: AI evaluates supplier performance using historical data, financial reports, and industry news to detect early signs of risk, enabling proactive strategies and supplier diversification.
• Sales and Operations Planning (S&OP): By integrating diverse data, AI can generate unified, accurate S&OP plans, supporting faster responses to demand changes and optimized resource allocation.
• Inventory Management: AI can set reorder points and safety stock levels based on demand variability, supplier lead times, and seasonal fluctuations, reducing carrying costs and minimizing stockouts.

These applications promise significant efficiency gains, cost reductions, and enhanced risk mitigation. By automating routine tasks, AI frees procurement and supply chain professionals to focus on higher-value activities requiring judgment, creativity, and business context.

Implementing Agentic AI: Challenges and Strategic Imperatives

While the benefits are compelling, successfully implementing Agentic AI requires careful consideration of several factors. As part of the research I mentioned earlier, one approach that stood out to me came from PwC’s 2025 Digital Trends in Operations survey. In this survey of operations and supply chain leaders, 92% cited at least one reason why their technology investments have fallen short of expectations—and 83% cited two or more reasons. The most common barriers were integration complexity (47%) and data issues (44%).

So as with any digital transformation initiative, there are several caveats I keep hearing and are worth repeating:

• Data Quality and Readiness: AI systems are only as good as the data they are trained on. Organizations must prioritize clean, accurate, and accessible data, addressing inconsistencies, incomplete information, and fragmented systems. The ability to capture and process both structured and unstructured internal data (e.g., emails, meeting transcripts, contract specifications) is crucial for competitive advantage.
  
• Change Management and Upskilling: The human element is paramount. Leaders must address employee concerns about job displacement, emphasize new higher-value responsibilities, and invest in training programs that build AI collaboration skills. The shift is from “job replacement” to “job evolution,” focusing on strategic analysis, negotiation, and AI oversight roles.
  
• Governance and Ethics: Clear governance is essential for risk management and adoption success. This includes defining AI decision authority boundaries, mitigating biases (e.g., in supplier selection), and ensuring regulatory compliance (e.g., data privacy laws like GDPR). The concept of a “human in the loop” is vital for strategic decisions, allowing human oversight even in highly automated processes.
  
• Avoiding “AI Washing”: Organizations must critically assess vendor solutions to distinguish true Agentic AI capabilities from mere “agent washing” where existing products are superficially relabeled.
  
• Strategic Roadmap: A successful implementation typically begins with pilot programs to demonstrate value, followed by gradual scaling and full integration into existing systems and processes. Executives are urged to “define business objectives, not just AI projects” and build a culture of responsible innovation.

Cutting versus Bleeding Edge

AI is and will continue to power constant cost benchmarking, real-time monitoring of production sites, and continuous analysis of supplier sentiment. This shifts organizations away from calendar-based reviews toward continuous optimization, enabling near-instant responses to market shifts or disruptions.

But as I’ve heard on a recent recorded conference session, “AI isn’t here for your jobs; people who know how to use AI are here for your jobs“. This highlights the need for procurement and supply chain professionals to embrace new skills and adapt to working alongside AI. So just like Darwin intimated, it’s not so much the strongest that will survive, it’s the ones that are most effective and adaptable to the new rapidly changing environment.

Moreover, many pundits say the next frontier lies in “agent-to-agent” interactions, where AI systems communicate and coordinate tasks directly, reducing interaction costs and accelerating processes even further. Yet, while the potential is significant, much remains unknown. Today we don’t yet fully understand how autonomous agents will compete or collaborate—or what happens when those interactions break down. These unanswered questions will shape how quickly organizations are willing to embrace the move to fully autonomous processes.

The Future Looks Agile and Autonomous

As new technology players unfold and existing technology platforms accommodate to it, the integration of Agentic AI is no longer optional; it’s becoming a competitive edge. Organizations that strategically embrace this transformation will position themselves as an essential contributor to competitive advantage in an increasingly complex global business environment.

And from this perspective, Liberis Consulting is committed to helping businesses navigate this complex landscape by helping the companies developing this technology to better annunciate the benefits they bring to market. In this regard, I am truly looking forward to drawing further insights on Agentic AI at the upcoming KonnectHouse conference in London on Sept 4. Conferences like these accelerate the understanding of the nuances of an Agentic AI implementation, for helping build resilient, efficient, and future-ready procurement and supply chain operations. Check it out!

Are you an AI-native technology provider in Procurement or Supply Chain that wants to navigate this new realm? Contact us to discuss your positioning and strategy in the evolving Agentic AI technology landscape. Let’s talk.