Nordic Procurement 2025: AI, Risk & Future Skills Report
This spring, 86 senior procurement professionals from 81 companies joined EBG | Xperience workshops in Stockholm, Gothenburg, and Copenhagen. Together, they explored how to future-proof procurement in the face of digital disruption, rising risk, and shifting business expectations.
The Post-Workshops Report 2025 captures these insights, blending pre-event surveys, interactive mapping exercises, and live feedback from participants.
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EBG Xperience 2025
Executive Summary
Key Findings
- The Hybrid Transformation: 39% of organizations are creating hybrid procurement models that combine traditional expertise with digital transformation roles and AI-driven capabilities, signaling a practical approach to modernization.
- Collaboration Dominates Operating Model Evolution: Three-quarters (75%) of organizations are emphasizing cross-functional collaboration with finance, supply chain, and sustainability teams, marking procurement’s shift from isolated function to enterprise connector.
- Risk Management is the Overwhelming Competency Priority: 58% identify risk management and resilience planning as a critical competency need, followed closely by sustainability & ESG compliance (52%) and digital tools proficiency (51%). The tight clustering reveals procurement professionals must develop multiple competencies simultaneously.
- The Messy Middle of Digital Transformation: 74% describe their digital maturity as “developing” – past the basics but struggling with integration and automation. Only 14% have reached advanced maturity, and notably, 0% consider themselves “leading.”
- AI Exploration Phase: Among Copenhagen participants, 60% are actively exploring AI and automation but haven’t widely implemented solutions yet, while 28% have achieved basic adoption in specific areas like contract analysis or supplier risk.
- Data Quality Blocks Progress: Data quality and system fragmentation (56% of Copenhagen respondents) emerges as the primary barrier to AI adoption, followed by integration challenges with existing ERPs (33%) and lack of internal AI expertise (30%).
- Risk Management Reality Check (Gothenburg): While 68% claim proactive/structured risk frameworks, 75% admit lacking visibility beyond Tier 1 suppliers, and 57% struggle with geopolitical and regulatory uncertainty, revealing a gap between aspirations and operational reality.
Survey Context
This report aggregates findings from three EBG Xperience events held across the Nordic region in Spring 2025. The survey captured perspectives from 86 procurement professionals across Stockholm (30 participants), Gothenburg (29 participants), and Copenhagen (27 participants). While most questions were asked across all cities, AI-related questions (Q6-Q7) were introduced specifically in Copenhagen, and risk management questions were asked specifically in Gothenburg to explore emerging patterns in these critical areas.
Beyond the quantitative survey, each city conducted interactive workshop mapping exercises where participants visually positioned their organizations across diagnostic frameworks. These mappings revealed critical patterns around empowerment gaps, structural readiness, data strategy, and AI implementation priorities that complement and deepen the survey insights.
Procurement Organization Size
Understanding the distribution of procurement organization sizes provides important context for interpreting transformation challenges and capabilities across the Nordic region.
Analysis
The participant base represents a diverse range of procurement organization sizes, with a notable concentration in larger enterprises. Approximately two-thirds of participants (66%) come from organizations with 51 or more procurement professionals, suggesting the survey captures perspectives from established procurement functions with significant organizational influence.
The strong representation from larger organizations (35% with 201+ people) indicates these findings particularly reflect the challenges and transformation approaches of mature procurement functions navigating complexity at scale. Medium-sized teams (11-50 people) represent nearly a third of participants, providing important perspective from organizations large enough to face enterprise challenges but potentially more agile in implementing change.
Size Matters for Transformation
Organization size significantly influences transformation approaches. Larger organizations often struggle with legacy systems integration and change management across distributed teams, while smaller teams may face resource constraints but can pivot more quickly. This distribution helps explain why 74% describe themselves as “developing” in digital maturity – organizations of all sizes face distinct but significant barriers to advancement.
Building Future-Proof Procurement Capabilities
How organizations approach capability building reveals their strategic priorities and readiness for procurement’s evolving role.
The Hybrid Model Emerges
Nearly 40% of organizations are pursuing a hybrid approach that combines traditional procurement expertise with digital transformation roles and AI-driven capabilities. This pragmatic strategy acknowledges that foundational procurement skills remain essential while new digital capabilities become increasingly critical.
Digital-First vs. Balanced Approaches
A quarter of organizations (25%) focus primarily on expanding digital skills including automation, AI, and data analytics. When combined with the 39% pursuing hybrid models, this means 64% of organizations are actively integrating digital capabilities into their procurement teams – a clear signal that digital transformation is no longer optional.
However, 17% of organizations recognize the need for change but struggle to redefine procurement competencies, indicating significant execution challenges despite strategic awareness. Only 13% continue investing primarily in traditional procurement skills, suggesting most organizations understand that historical capabilities alone won’t suffice for future success.
The Competency Redefinition Challenge
The 17% who struggle to redefine competencies despite recognizing the need represents a critical risk group. These organizations understand transformation is necessary but lack clarity on how to evolve their talent strategy. This gap between awareness and action can create competitive disadvantages as more decisive organizations pull ahead in capability development.
What Hybrid Actually Means
The popularity of hybrid models reflects a sophisticated understanding that procurement transformation isn’t about replacing traditional skills but rather augmenting them. Organizations need professionals who can negotiate complex contracts AND interpret supplier risk analytics, who understand category strategy AND can leverage AI-driven market intelligence. The hybrid approach acknowledges this reality while providing a practical pathway forward.
Operating Model Evolution
How procurement structures itself fundamentally shapes its ability to deliver value. Organizations are pursuing multiple operating model changes simultaneously, with strong consensus on cross-functional collaboration as the dominant evolution.
Collaboration Dominates
Cross-functional collaboration emerges as the overwhelming priority, with three-quarters (75%) of organizations emphasizing closer integration with finance, supply chain, and sustainability teams. This isn’t just one among many priorities – it’s the clear dominant theme in how procurement is evolving its operating model.
Dual Transformation Paths
Beyond the collaboration imperative, organizations are pursuing two parallel approaches in equal measure, each with 55% adoption:
Process-Driven Approaches (55%): Moving toward category-based or end-to-end sourcing process ownership represents a shift from functional silos to integrated process ownership. This approach aligns procurement activities around value creation rather than organizational boundaries.
Digital Tool Adoption (55%): Increasing reliance on self-service procurement, automation, and AI-driven workflows indicates organizations are actively investing in technology infrastructure, even as many struggle with implementation (as reflected in the digital maturity findings).
That both process and digital transformations show identical adoption rates (55%) suggests organizations recognize these as complementary rather than competing approaches – you need both new processes AND new tools to transform effectively.
Additional Evolution Paths
Role Redefinition (35%): About a third of organizations are creating new skills, career paths, and digital-first roles. While significant, this receives less emphasis than collaboration, process, or digital changes, which may explain why 18% struggle to redefine competencies (noted in the capabilities section).
Traditional and Business-Integrated Models (32% and 31%): Nearly a third maintain traditional function-based structures, while a similar proportion moves toward business-integrated models. Combined, these conventional approaches represent a substantial minority continuing with more established operating models.
The Collaboration Imperative
The overwhelming emphasis on cross-functional collaboration (75%) reveals a fundamental shift in how procurement creates value. This isn’t one option among many – it’s the defining characteristic of modern procurement operating models. As sustainability requirements, supply chain resilience, and financial optimization become increasingly interconnected, procurement cannot operate in isolation. Three-quarters of organizations recognize that procurement’s future effectiveness depends on its ability to orchestrate value across enterprise boundaries rather than optimizing within its own functional silo.
Critical Competencies for Procurement Professionals
Understanding which competencies procurement professionals need most reveals the changing demands on the function and where capability gaps present the greatest risk. The results show strong consensus around a core set of competencies that more than half of organizations identify as critical.
The Core Competency Triad
Three competencies emerge as the overwhelming priorities, each identified by more than half of all respondents:
Risk Management Dominates
Risk management and resilience planning stands apart as the single most critical competency need at 58% – nearly six in ten organizations identify this as essential. This priority reflects the volatility and uncertainty that have defined recent years, from supply chain disruptions to geopolitical instability. Procurement’s role in organizational resilience has moved from peripheral to absolutely central.
What makes this finding particularly striking is that while 58% identify risk management as a critical need, the Gothenburg data reveals that 68% claim to have “proactive/structured” risk frameworks. This suggests the competency gap isn’t about establishing frameworks but about operationalizing them effectively – particularly for extended supply chain visibility where 75% struggle beyond Tier 1.
The Sustainability and Digital Imperatives
Sustainability & ESG Compliance (52%): Just slightly behind risk management, sustainability and ESG compliance is identified as critical by more than half of respondents. This reflects escalating regulatory and stakeholder pressure around environmental and social governance. Procurement’s role in Scope 3 emissions and supply chain sustainability makes this competency increasingly non-negotiable. The 52% prioritization aligns with the Gothenburg finding that 32% struggle with integrating sustainability risk into their frameworks.
Digital Tools & Automation Proficiency (51%): Rounding out the top three, digital and automation proficiency is essential for just over half of organizations. This confirms that technical capability is now fundamental rather than specialized, aligning with the 64% pursuing digital or hybrid capability models (39% hybrid + 25% digital-first). The tight clustering with sustainability (52% vs 51%) suggests these aren’t competing priorities but rather complementary requirements.
The Secondary Competency Tier
Four additional competencies form a second tier, each identified by 39-48% of organizations:
Supplier Collaboration & Relationship Management (48%): Nearly half identify traditional relationship skills as critical, suggesting that even as procurement digitalizes, human relationship capabilities retain fundamental importance. The emphasis on collaboration across nearly half of organizations connects to the 75% prioritizing cross-functional collaboration in operating models.
Leadership & Change Management (47%): Closely following supplier relationships, leadership and change management skills at 47% reinforces that procurement transformation isn’t just about technical capabilities but requires professionals who can drive organizational change and influence stakeholders.
Data Literacy & Analytics Skills (42%): Two in five organizations identify data literacy as critical. While clearly important, data skills rank lower than might be expected given the digital transformation emphasis. This may indicate organizations view data literacy as enabling rather than core, or that the gap is less severe than in other areas. However, the 56% of Copenhagen respondents citing data quality as the primary AI barrier suggests data capabilities remain under-developed.
Strategic Negotiation & Stakeholder Management (39%): Just under 40% identify negotiation and stakeholder management as critical. This relatively lower ranking might suggest organizations feel more confident in these traditional strength areas, or perhaps these skills are assumed as baseline capabilities rather than development priorities.
From Specialists to Generalists
The competency distribution reveals a fundamental shift in procurement professional requirements. With six of seven core competencies identified by 39-58% of organizations – and no single competency dominating above 60% – procurement professionals face expectations to develop substantial capabilities across risk, sustainability, digital tools, relationships, leadership, and data analytics simultaneously. This isn’t about developing T-shaped profiles anymore; it’s about building hexagonal capabilities with reasonable proficiency across all six domains. Organizations can no longer hire narrowly specialized procurement professionals – they need versatile professionals who can navigate complexity across multiple domains.
Risk Management as the Defining Competency
The elevation of risk management to the top priority (58%) marks a significant shift in procurement’s identity. Historically focused on cost reduction and supplier management, procurement increasingly owns enterprise resilience. This competency priority reflects hard-learned lessons from supply chain disruptions, geopolitical instability, and climate-related risks that have characterized recent years. The connection to operational reality is clear: organizations identify risk management as their top competency need while simultaneously admitting (in Gothenburg data) that 75% lack visibility beyond Tier 1 suppliers – the very visibility needed for effective risk management.
Digital Maturity Assessment
Understanding where organizations sit on their digital transformation journey provides critical context for capability development and technology investment priorities.
The Overwhelming “Developing” Majority
Three-quarters of organizations (74%) describe their digital maturity as “developing” – characterized by some digitalization but limited integration and automation, while exploring basic AI use cases. This concentration in a single maturity stage reveals that most Nordic procurement organizations face similar challenges in moving beyond foundational digitalization.
The Integration and Automation Barrier
The concentration at “developing” maturity, combined with only 14% achieving “advanced” status, indicates that organizations can implement digital tools but struggle to integrate them effectively or automate workflows at scale. This barrier between developing and advanced maturity appears more challenging to cross than moving from basic to developing.
The 11% at basic maturity (mostly manual processes, limited tools beyond Excel and email) represents a small but notable group still in early stages of digital transformation. For these organizations, the gap to industry norms has widened significantly.
The Missing Leading Edge
Perhaps most striking is the complete absence of organizations describing themselves as “leading” – fully digital procurement workflows enhanced by automation, advanced analytics, AI, and data-driven decision-making. This 0% at leading maturity suggests:
- The vision of fully digital, AI-enabled procurement remains aspirational even among the most advanced organizations
- Organizations recognize the gap between current capabilities and true digital maturity
- Realistic self-assessment reveals that even “advanced” organizations have significant room for improvement
- The rapid evolution of AI and automation continually raises the bar for what constitutes “leading” maturity
The Stuck Middle Phenomenon
The massive concentration at “developing” (74%) creates both a risk and an opportunity. The risk is that organizations may become comfortable in this middle ground, implementing enough digitalization to feel progressive but not enough to realize transformative value. The opportunity is that shared challenges at this maturity level enable collective learning and solution development across the Nordic procurement community.
Integration Over Implementation
The data suggests the primary challenge has shifted from implementing digital tools to integrating them effectively. Organizations have moved past the question of “whether” to digitalize and now face the harder question of “how” to make disparate digital solutions work together seamlessly. This integration challenge explains why data quality and system fragmentation emerges as the primary AI adoption barrier in the Copenhagen data.
AI and Automation Adoption
Current AI Adoption Status
The Copenhagen data reveals a procurement community in active exploration mode, with most organizations researching AI capabilities but not yet implementing them at scale.
The Exploration Phase
With 60% actively exploring AI and automation but not yet widely implementing, Copenhagen organizations are in a critical decision-making phase. They’re researching use cases, evaluating vendors, and assessing organizational readiness, but haven’t yet committed to scaled deployment.
The 28% with basic adoption have moved past exploration to implementation in specific areas such as contract analysis or supplier risk assessment. These targeted deployments represent a practical approach – proving value in contained use cases before broader rollout.
Only 1% report advanced adoption where AI, automation, and predictive analytics are embedded in procurement workflows. This minimal advanced adoption aligns with the 0% “leading” digital maturity finding from the broader survey, confirming that truly advanced AI integration remains rare.
Barriers to AI Adoption
Copenhagen participants identified specific challenges blocking AI adoption progress:
Data Quality as the Primary Blocker
Data quality and system fragmentation accounts for 56% of respondents, emerging as the dominant barrier. This finding directly connects to the digital maturity challenges noted earlier – organizations have implemented multiple digital tools but struggle to integrate them effectively, resulting in fragmented data that undermines AI effectiveness.
Integration challenges with existing ERPs and procurement platforms (33%) reinforce this theme. Legacy systems weren’t designed for AI integration, creating technical debt that must be addressed before advanced AI deployment becomes feasible.
Lack of internal AI expertise in procurement (30%) indicates a skills gap, though notably this ranks lower than data and integration challenges. Organizations may believe they can acquire or develop AI expertise more easily than they can solve fundamental data quality issues.
What “Other” Actually Means
The 44% selecting “other” barriers provided specific open-ended responses that reveal important organizational and cultural challenges not captured in standard adoption barrier categories:
Participant-Reported “Other” Barriers:
- Risk aversion: “Company is risk averse” – organizational culture blocks experimentation
- Resource constraints: “Lack of resources,” “Funding,” “Funding issues” – budget and capacity limitations
- Leadership engagement: “Lack of interest from the management” – executive sponsorship gaps
- Security and governance concerns: “Data security assessments and contracting, IT architecture concerns,” “Security issues,” “IT policies,” “Governance” – compliance and risk management barriers
- Reliability concerns: “Not being able to rely on result” – trust in AI outputs
- Infrastructure limitations: “Bandwidth” – technical capacity constraints
- Change readiness: “Be openminded for changes” – organizational adaptability
These responses reveal that AI adoption barriers extend well beyond technical challenges like data quality or integration. Organizations face fundamental issues with risk tolerance, resource allocation, leadership commitment, and organizational culture that must be addressed before technical solutions can succeed.
The Cultural Dimension of AI Adoption
The open-ended responses highlight a critical insight: technical readiness is necessary but not sufficient for AI adoption. Organizations struggling with risk aversion, lack of management interest, or resistance to change will find that solving data quality problems doesn’t automatically enable AI deployment. These cultural and organizational barriers may actually be more difficult to overcome than technical challenges, requiring sustained change management efforts and executive commitment.
AI Adoption Structure
Organizations are taking varied approaches to structuring AI adoption:
Three approaches tie at 26% each, revealing no dominant organizational model:
AI Center of Excellence (26%): Centralizing AI capabilities in a dedicated center aims to build expertise, ensure governance, and enable knowledge sharing across functions. This approach can accelerate learning but may create distance between AI capabilities and procurement operations.
IT-Led with Procurement Input (26%): Having IT lead AI adoption with procurement input leverages existing technical expertise but risks creating solutions that don’t fully address procurement needs or workflows.
Still Figuring It Out (26%): That 26% haven’t determined their AI adoption structure reinforces that organizations remain in exploration mode, wrestling with fundamental questions about governance and ownership before scaling implementation.
Only 15% have each function responsible for its own AI initiatives, suggesting most organizations recognize that AI adoption requires coordinated rather than siloed approaches.
From Exploration to Implementation
The 60% in exploration phase face a critical transition. Moving from research to implementation requires resolving the data quality, integration, and structural challenges identified. Organizations that successfully navigate this transition – addressing data fragmentation, clarifying AI governance, and building targeted expertise – will likely move into the “basic adoption” category within the next 12-18 months. Those that don’t risk remaining stuck in perpetual exploration.
The Data Foundation Problem
AI adoption cannot succeed without solid data foundations. The 56% citing data quality and system fragmentation as their primary barrier signals a fundamental challenge: organizations want to deploy AI before they’ve properly integrated their existing digital infrastructure. This sequence problem means many AI initiatives may struggle or fail until organizations first address digital maturity gaps identified in the broader survey.
Risk Management Maturity (Gothenburg)
Understanding where organizations stand on risk management maturity reveals both self-assessed capabilities and the practical challenges they face in operationalizing risk intelligence.
Self-Assessed Risk Maturity
Gothenburg participants positioned their organizations across a risk maturity spectrum from ad hoc/reactive to leading/optimized approaches.
The Proactive Majority Narrative
A striking 68% describe their risk management as “Proactive/Structured” with formal frameworks, supplier risk assessments, and defined mitigation strategies. This self-assessment suggests that most organizations have moved beyond reactive firefighting to establish systematic risk management processes.
However, the reality check comes when examining the operational challenges these same organizations report. While claiming proactive frameworks, 75% admit lacking visibility beyond Tier 1 suppliers, and 57% struggle with geopolitical and regulatory uncertainty. This gap between aspiration and operational reality reveals that having a framework doesn’t necessarily translate to effective risk mitigation.
The Missing Edges
Two notable absences shape the risk maturity landscape:
No Ad Hoc/Reactive Organizations (0%): Not a single participant placed themselves in the reactive/ad hoc category, suggesting either that truly reactive organizations didn’t attend, or that there’s a social desirability bias in self-assessment. Given the visibility and operational challenges reported, some organizations describing themselves as “proactive” may actually operate more reactively than they acknowledge.
No Leading/Optimized Organizations (0%): Similar to the broader digital maturity finding, zero participants claim “leading” risk management status (AI-driven, fully automated, predictive risk monitoring). This honest self-assessment indicates organizations recognize the gap between current capabilities and truly advanced risk management.
Biggest Risk Management Challenges
When asked about their primary operational challenges, the responses reveal where frameworks meet reality:
Tier 1 Visibility Dominates
Three-quarters of organizations (75%) cite lack of visibility beyond Tier 1 suppliers as their biggest challenge. This overwhelming response indicates that supply chain transparency remains the primary barrier to effective risk management, regardless of how sophisticated frameworks might be.
The Tier 1 visibility problem connects directly to the “proactive/structured” self-assessment. Organizations may have formal supplier risk assessment processes, but if those processes only reach direct suppliers, their risk intelligence has critical blind spots. Sub-tier disruptions, environmental violations, or labor practices beyond Tier 1 remain invisible.
The Uncertainty and Complexity Challenge
Beyond visibility, organizations face substantial challenges managing external volatility and internal tensions:
Geopolitical & Regulatory Uncertainty (57%): Over half struggle with navigating shifting trade policies, sanctions, and regulatory changes. This high percentage reflects the current global environment where supply chains face ongoing disruption from geopolitical events and evolving compliance requirements.
Proactive vs. Reactive Balance (39%): Four in ten organizations struggle to shift from reactive firefighting to proactive risk mitigation. This finding reveals a critical execution gap – even organizations with “proactive frameworks” find themselves pulled back into reactive mode by the demands of daily operations.
Cost vs. Compliance Trade-offs (32%): Nearly a third wrestle with balancing risk mitigation costs against compliance requirements and operational efficiency. This tension becomes particularly acute when addressing sustainability requirements or supply chain resilience improvements that may increase procurement costs.
Secondary Challenges
Additional challenges received more modest emphasis but remain significant for specific organizations:
AI & Digital Tools Uncertainty (21%): About one in five express uncertainty about how to leverage AI and digital tools for risk management. This connects to the broader survey findings on AI adoption barriers, particularly around data quality and integration challenges.
Sustainability Risk Integration (32%): A third struggle with embedding ESG and circular economy principles into risk frameworks. As sustainability moves from nice-to-have to regulatory requirement, procurement must integrate environmental and social risk assessment into traditional supplier evaluation processes.
Supplier Financial Stability (7%): Only 7% cite this as their primary challenge, suggesting most organizations have reasonable visibility into direct supplier financial health, even if they lack transparency into sub-tiers.
Visibility Beyond Tier 1: The Operational Reality
To validate the self-reported challenge, participants also assessed their current visibility capabilities:
The Limited Visibility Reality
A remarkable 71% describe their visibility as “limited” – having some Tier 2 insights but mostly reacting when issues arise rather than proactively monitoring. This finding validates the 75% who cite Tier 1 visibility as their biggest challenge. Organizations know sub-tier suppliers exist and occasionally get visibility when problems surface, but lack systematic monitoring capabilities.
Only 7% achieve high visibility with ongoing monitoring of extended supply chains, and zero organizations claim end-to-end transparency with fully mapped multi-tier networks. The gap between “proactive/structured” self-assessment (68%) and actual visibility capabilities (7% high visibility) reveals a significant disconnect between frameworks and operational reality.
The Framework-Reality Gap
The disconnect between risk maturity self-assessment and operational challenges creates a critical vulnerability. Organizations may believe their “proactive/structured” frameworks provide adequate protection while simultaneously acknowledging that 75% lack visibility beyond Tier 1 and 71% have only limited sub-tier transparency. This gap suggests frameworks exist on paper but haven’t been operationalized effectively, particularly for extended supply chain monitoring.
From Frameworks to Operations
The Gothenburg risk data reveals that procurement’s next frontier isn’t establishing risk frameworks – most organizations have those. The challenge is operationalizing frameworks to address practical barriers: gaining sub-tier visibility, navigating geopolitical uncertainty, and balancing proactive monitoring with reactive firefighting demands. Organizations claiming “proactive” status must now prove it through operational capabilities rather than documented processes.
The Tier 1 Ceiling
The overwhelming focus on Tier 1 visibility challenges (75% cite it as primary challenge, 71% have limited sub-tier visibility) indicates a structural barrier in procurement risk management. Traditional supplier relationship management models, data collection processes, and contractual obligations all focus on direct suppliers. Breaking through this Tier 1 ceiling requires fundamentally different approaches – supply chain mapping technologies, industry collaboration platforms, and risk intelligence sharing that transcends individual buyer-supplier relationships. Organizations stuck at the Tier 1 ceiling face substantial sub-tier risk exposure regardless of how sophisticated their direct supplier assessment processes might be.
Workshop Mapping Analysis
Beyond the quantitative survey data, each EBG Xperience event featured interactive mapping exercises where participants positioned themselves across diagnostic frameworks. These visual exercises reveal patterns, clusters, and gaps that numbers alone cannot capture, providing texture to the transformation challenges facing Nordic procurement organizations.
Stockholm: Acting in Imperfect Conditions
Framework: Competence Readiness (X-axis) vs. Empowerment Level (Y-axis)
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The “Skilled but Stuck” Phenomenon
A significant cluster appears in the right-center quadrant (“Skilled but Stuck”) where teams possess necessary competencies but lack empowerment to act. This pattern reveals a critical organizational dynamic: the barrier to transformation isn’t primarily about skills development but about decision rights, approval processes, and organizational trust.
Key Observations:
- Individual vs. Team Empowerment: Pink dots (individuals) cluster more in the upper-right (“Skilled & Empowered”) while yellow dots (teams) spread across the middle, suggesting individuals feel more empowered than their teams as a whole.
- The Doubly Challenged Quadrant: Multiple organizations position in the lower-left where teams lack both capabilities and empowerment, representing the highest-risk group requiring fundamental organizational intervention.
- The Confidence Gap: Few dots reach the top quadrant where “people take ownership and act with confidence,” indicating that even skilled teams hesitate or wait for approval rather than acting autonomously.
Empowerment as the Bottleneck
The concentration of dots below the midline on empowerment suggests that governance structures, approval processes, and organizational culture may be more significant barriers to transformation than technical capabilities. Organizations investing heavily in skills development without addressing empowerment frameworks risk creating frustrated, capable teams unable to execute on their knowledge.
Stockholm: Structures That Support Change
Framework: Structural Fit (X-axis) vs. Transformation in Motion (Y-axis)
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The “Clarifying Path Forward” Cluster
The dominant cluster sits in the center-left quadrant labeled “Clarifying Path Forward” – organizations committed to change but with unclear processes and roles while actively shaping how transformation will happen. This positioning reveals a critical phase: organizations have bought into transformation but are still figuring out the operating model to support it.
Key Observations:
- Movement Without Structure: Many dots cluster around medium-high transformation velocity but low structural clarity, indicating organizations are changing before establishing stable frameworks to support that change.
- The Emerging Flow Group: A secondary cluster in the upper-left (“Emerging Flow”) represents organizations moving fast in pockets but questioning scalability without structural support.
- Few Reach Transformation-Ready: The upper-right quadrant (“Transformation-Ready” with both structural support and active evolution) remains sparsely populated, confirming that few organizations have achieved alignment between structure and momentum.
- The Intent-Action Gap: The single dot at the bottom center (“aligned in intent, but slow to move”) captures organizations where strategic clarity hasn’t translated to operational velocity.
Structure Lags Behind Ambition
The concentration of dots with higher transformation velocity than structural readiness creates organizational stress. Processes and roles remain siloed or unclear even as teams attempt to work differently. This misalignment can create confusion, rework, and eventually transformation fatigue as enthusiasm meets structural friction. Organizations must invest in clarifying operating models, decision rights, and cross-functional workflows to sustain momentum.
Gothenburg: Risk Data vs. Actionability
Framework: Data Quantity (X-axis) vs. Actionability Level (Y-axis)
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The Goldilocks Zone: Limited but Sharp
A striking pattern emerges with a strong cluster in the upper-center quadrant – organizations with modest data volumes but high actionability. This positioning challenges the assumption that more data automatically enables better decisions. Instead, it suggests that data quality, relevance, and focus matter more than comprehensiveness.
Key Observations:
- The Center Mass: The largest concentration sits at moderate data levels with medium-to-high actionability, suggesting most organizations have found a workable balance where they have enough data to act without being overwhelmed.
- Data Swamp Avoidance: Very few dots appear in the right-side quadrants (“Too Much Data” / “Data Swamp”), indicating organizations have largely avoided the trap of collecting data they cannot use.
- The Upper Cluster: Several organizations have achieved high actionability with limited data, demonstrating that focused risk intelligence with clear decision triggers outperforms comprehensive but unwieldy data systems.
- The Scattered Few: A few outliers sit in low actionability zones (left-center), suggesting they either have too little data to make decisions or haven’t established clear decision frameworks for the data they possess.
Quality Over Quantity
The upper-center clustering directly validates a key principle: actionable risk management doesn’t require exhaustive data collection. Organizations succeeding in this space have likely identified critical risk indicators, established clear decision thresholds, and empowered teams to act on signals without waiting for perfect information. This pattern stands in notable contrast to the survey finding that 56% of Copenhagen respondents cite data quality and fragmentation as a primary AI adoption barrier – suggesting that the challenge isn’t data volume but data integration and decision clarity.
Copenhagen: Value versus Complexity
Framework: Implementation Complexity (X-axis) vs. Value if Implemented (Y-axis)
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The High-Value, Low-Complexity Opportunity Zone
Participants assessed four agent types – Compliance, Supplier Performance, PO Creation, and Predictive Dispute Management – plotting where each would land on value versus complexity. The distribution reveals strategic prioritization patterns and highlights implementation trade-offs.
Key Observations by Agent Type:
- Compliance (Orange): Dots cluster heavily in the upper-center (“High Value, Moderate Complexity”) with several in the ideal upper-left quadrant. Organizations see clear value in compliance automation and view it as relatively achievable with current tools, making it a logical first-mover use case.
- Supplier Performance (Yellow): Spreads across the upper half from low to high complexity, with concentration in the upper-center and upper-right. Organizations recognize high value but perceive varying complexity levels, possibly reflecting different approaches (simple scorecards vs. complex predictive models).
- PO Creation (Green): Clusters primarily in the left side – low complexity zones. This positioning suggests organizations view PO automation as relatively straightforward technically, though perceived value varies from moderate to high. Several dots in the lower-left indicate some see limited transformative potential.
- Predictive Dispute Management (Pink): Scatters widely across all four quadrants with concentration in the center and right side. This agent type shows the most polarized assessment – some see high value and manageable complexity, others see high complexity for uncertain value. This divergence likely reflects different organizational pain points around disputes and varying data maturity for predictive capabilities.
The Missing Lower-Right: No Low-Value, High-Complexity Traps
Notably, very few dots appear in the lower-right “Low Value, High Complexity” quadrant, suggesting participants successfully avoid the trap of pursuing complex initiatives with limited payoff. However, the concentration in the upper-center and upper-right means many high-value opportunities require significant integration or redesign work. Organizations must make explicit prioritization choices: pursue easier wins with moderate value (PO creation, basic compliance) or tackle complex, high-value opportunities (advanced supplier performance analytics, predictive dispute management) that require sustained investment.
Strategic Sequencing Implications
The mapping suggests a natural implementation sequence: start with compliance automation (high value, moderate complexity), layer in PO creation efficiencies (quick wins), build toward supplier performance intelligence (high value, increasing complexity), and reserve predictive dispute management for organizations with mature data foundations. This sequencing allows organizations to build capability and confidence progressively rather than attempting the most complex use cases first.
Patterns Across Cities: What the Mappings Reveal Together
Five Cross-Cutting Themes
1. The Capability-Empowerment Gap
Stockholm’s “Skilled but Stuck” cluster reveals that competence development alone doesn’t drive transformation. Organizations have invested in building capabilities but haven’t correspondingly evolved governance structures, decision rights, and cultural norms that enable skilled teams to act autonomously.
2. Structure Lags Behind Momentum
Stockholm’s “Clarifying Path Forward” concentration shows organizations transforming before establishing structural support. This creates organizational stress as teams work in new ways while processes and roles remain unchanged. The mismatch between transformation velocity and structural clarity risks creating confusion and eventual fatigue.
3. Data Minimalism Wins
Gothenburg’s upper-center cluster challenges the “more data is better” assumption. Organizations achieving high actionability with moderate data volumes have likely focused on quality over quantity – identifying critical indicators, establishing clear decision thresholds, and empowering action without requiring perfect information.
4. Pragmatic AI Prioritization
Copenhagen’s value-complexity mapping shows organizations successfully avoiding low-value, high-complexity traps. The concentration in upper-center and upper-right quadrants indicates organizations recognize that meaningful AI deployment requires accepting complexity, but they’re making strategic choices about where that complexity investment delivers highest return.
5. The Missing Leading Edge
Across all four mappings, very few dots occupy the “ideal” quadrants (transformation-ready, skilled & empowered, proactive & smart risk management, high value/low complexity solutions deployed). This absence confirms the survey finding of 0% at “leading” digital maturity – even the most advanced organizations recognize significant gaps between current state and transformation aspirations.
The Systemic Nature of Transformation
The workshop mappings collectively reveal that procurement transformation isn’t a linear progression from less mature to more mature. Instead, organizations face interconnected challenges across capabilities, empowerment, structure, data strategy, and technology deployment. Progress in one dimension without corresponding advances in others creates new bottlenecks. This systemic reality explains why 74% remain stuck at “developing” digital maturity despite significant investment – transformation requires orchestrating multiple changes simultaneously rather than optimizing individual dimensions sequentially.
Key Takeaways & Strategic Implications
The Nordic Procurement Transformation Landscape
Nordic procurement organizations are navigating a complex transformation characterized by pragmatic approaches, shared challenges, and realistic self-assessment. The EBG Xperience 2025 survey reveals an industry moving beyond digital transformation theater toward the hard work of integration, capability building, and organizational change.
1. The Hybrid Model Signals Maturity
The 39% pursuing hybrid capability models that combine traditional and digital expertise represents a sophisticated understanding of procurement transformation. Rather than viewing digital and traditional skills as competing alternatives, leading organizations recognize they’re complementary. This pragmatic approach acknowledges that negotiation, category management, and supplier relationships remain essential while digital literacy, data analytics, and AI proficiency become increasingly critical.
Implication: Talent strategies must evolve from “hire for digital OR traditional skills” to “develop both in every professional.” This requires fundamentally rethinking procurement career paths, training programs, and hiring profiles.
2. Collaboration IS the Operating Model
Cross-functional collaboration isn’t just one evolution among many – it’s THE defining characteristic of modern procurement operating models. With 75% of organizations emphasizing closer integration with finance, supply chain, and sustainability teams, this represents overwhelming consensus. Procurement’s identity has fundamentally shifted from independent function to enterprise connector, and the data confirms this isn’t aspirational – it’s how three-quarters of Nordic organizations are actively restructuring.
Implication: Success metrics must evolve beyond procurement-specific KPIs to measure value created through cross-functional initiatives. Procurement leaders need stakeholder management and influence skills as much as category expertise. The 75% adoption rate means cross-functional collaboration capability is now table stakes, not a differentiator.
3. The Stuck Middle Represents Both Risk and Opportunity
The concentration of 74% at “developing” digital maturity reveals a critical inflection point. Organizations have moved past basic digitalization but struggle with integration and automation. This shared challenge creates opportunity for collective learning, but also risks complacency in the “messy middle.”
Implication: Organizations should prioritize integration and data quality over new tool acquisition. The next maturity leap requires making existing digital investments work together effectively rather than adding more point solutions.
4. Data Quality Blocks AI Adoption
With 56% of Copenhagen respondents identifying data quality and system fragmentation as the primary AI barrier, organizations face a sequencing challenge. Many want to deploy AI before establishing the data foundations AI requires. This sequence problem explains why 60% remain in AI exploration without implementation.
Implication: AI readiness assessments must start with data infrastructure audits. Organizations should invest in data quality, governance, and integration before pursuing advanced AI use cases. Master data management may be less exciting than generative AI but it’s more foundational.
5. Risk Management Isn’t Just Priority – It’s THE Priority
Risk management and resilience planning identified as critical by 58% of organizations isn’t just “top of the list” – it’s in a category of its own, representing overwhelming consensus that this capability is now central to procurement’s value proposition. Combined with sustainability (52%) and digital tools (51%), more than half of organizations identify each of these three competencies as essential, marking them as the new core skillset.
Implication: Procurement must develop scenario planning capabilities, supplier relationship depth beyond transactional metrics, and cross-functional crisis response protocols. Risk mitigation may sometimes increase costs, requiring different stakeholder conversations about procurement’s value proposition. The 58% prioritization isn’t academic – organizations recognize procurement now owns enterprise resilience in an era of continuous supply chain volatility.
6. The End of Specialization
With six core competencies each identified by 39-58% of organizations – risk management (58%), sustainability (52%), digital tools (51%), supplier relationships (48%), leadership (47%), and data literacy (42%) – procurement professionals face expectations to develop substantial capabilities across all domains. This isn’t about T-shaped profiles with one deep expertise anymore. Organizations need hexagonally-skilled professionals with reasonable proficiency across all six competencies.
Implication: Procurement talent strategies must completely reimagine role definitions, hiring profiles, and development pathways. The days of hiring specialized negotiators, category managers, or sourcing specialists are ending. Organizations need versatile professionals who can manage supplier risks AND navigate ESG compliance AND leverage digital tools AND lead cross-functional initiatives. This fundamentally challenges traditional procurement career paths and organizational structures.
7. The Framework-Reality Gap in Risk Management
Gothenburg data reveals a striking disconnect: 68% claim “proactive/structured” risk frameworks, yet 75% lack visibility beyond Tier 1 suppliers and 71% have only limited sub-tier transparency. Organizations have established frameworks on paper but haven’t operationalized them for extended supply chain monitoring.
Implication: Risk management maturity requires moving from framework development to operational capability building. Organizations must invest in supply chain mapping technologies, industry collaboration platforms, and risk intelligence sharing that transcends traditional buyer-supplier relationships to break through the Tier 1 ceiling.
8. No One Has Figured It Out Yet
The 0% at “leading” digital maturity, 0% at “leading” risk management maturity, and just 1% with advanced AI adoption reveals that even the most progressive organizations haven’t fully cracked the code on digital procurement transformation. This levels the playing field – no organization is so far ahead that others cannot catch up.
Implication: Rather than benchmarking against mythical “digital leaders,” organizations should focus on learning from those a step ahead in specific areas. The most valuable insights come from organizations navigating the messy middle, not from theoretical best practices.
9. AI Structure Remains Unresolved
The three-way tie at 26% each between AI Centers of Excellence, IT-led approaches, and “figuring it out” reveals organizations wrestling with fundamental AI governance questions. Without clear ownership and structure, AI initiatives risk stalling despite technical readiness.
Implication: Organizations should clarify AI governance before scaling initiatives. The specific structure matters less than having clear accountability, decision rights, and integration mechanisms between AI capabilities and procurement operations.
10. Skilled but Stuck: The Empowerment Bottleneck
Stockholm’s workshop mapping revealed a critical pattern: numerous organizations cluster in the “skilled but stuck” zone where teams possess necessary competencies but lack empowerment to act. This indicates that the barrier to transformation isn’t primarily skills development but decision rights, approval processes, and organizational trust.
Implication: Organizations investing heavily in capability building without correspondingly evolving governance structures and decision rights will create frustrated teams unable to leverage their skills. Transformation requires empowerment reforms alongside competency development.
11. Structure Lags Behind Ambition
The “Clarifying Path Forward” cluster from Stockholm shows organizations with high transformation momentum but unclear processes and roles. Teams are changing how they work before establishing stable frameworks to support that change, creating organizational stress and potential confusion.
Implication: Sustainable transformation requires deliberate operating model design rather than hoping structures will organically emerge from new behaviors. Organizations should invest in clarifying decision rights, cross-functional workflows, and role definitions to support the momentum they’re building.
12. Data Quality Beats Data Quantity
Gothenburg’s risk data mapping showed organizations achieving high actionability with moderate data volumes, clustered in the “Limited but Sharp” zone. This challenges the assumption that comprehensive data collection enables better risk management.
Implication: Organizations should focus on identifying critical risk indicators and establishing clear decision thresholds rather than pursuing exhaustive data capture. The goal is actionable intelligence, not comprehensive dashboards. This finding directly addresses the data quality barriers to AI adoption – the issue isn’t volume but focus and integration.
13. Pragmatic AI Prioritization Matters
Copenhagen’s value-complexity mapping revealed strategic thinking about AI deployment. Organizations cluster around compliance automation (high value, moderate complexity) while taking varied approaches to supplier performance and predictive dispute management based on their specific contexts.
Implication: There’s no universal AI implementation sequence. Organizations should map their specific use cases against value and complexity, then sequence implementation based on their data maturity, resource availability, and organizational readiness. Starting with moderate-complexity, high-value use cases like compliance automation allows capability building before tackling more complex deployments.
Looking Forward: The Systemic Nature of Transformation
The EBG Xperience 2025 survey and workshop mappings together capture Nordic procurement at a pivotal moment. The quantitative data reveals what organizations are prioritizing – hybrid capabilities, cross-functional collaboration, risk management, and data quality. The workshop mappings reveal why transformation remains challenging – organizations face interconnected barriers across empowerment, structure, data strategy, and governance that must be addressed simultaneously.
The workshop patterns particularly highlight that procurement transformation isn’t a linear journey from less mature to more mature. Organizations can build skills without empowerment (Stockholm’s “skilled but stuck”), create momentum without structure (Stockholm’s “clarifying path forward”), achieve actionability without comprehensive data (Gothenburg’s “limited but sharp”), and make smart prioritization choices while recognizing complexity ahead (Copenhagen’s value-complexity mapping).
Success will belong to organizations that recognize transformation’s systemic nature – progress requires orchestrating changes across capabilities, empowerment frameworks, operating models, data strategies, and technology deployment simultaneously. Organizations must prioritize integration over implementation, develop hybrid capabilities rather than choosing between traditional and digital, honestly assess their maturity rather than claiming premature leadership, invest in structural enablers like decision rights and governance alongside technical solutions, and address the Tier 1 visibility ceiling that blocks effective risk management. The path forward requires patience, pragmatism, and persistence – but the Nordic procurement community is navigating it together, learning from each other’s experiments across Stockholm, Gothenburg, and Copenhagen.
Procurement Leaders sharing their know how during EBG | Xperience 2025
Expert Organizations supporting EBG | Xperience 2025
About Coupa
Coupa makes margins multiply through its community-generated AI and industry leading total spend management platform for businesses large and small. Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers. We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins. Coupa is the margin multiplier company.
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About Prewave
At Prewave, we’re committed to enhancing supply chain transparency, resilience, and sustainability. As pioneers of an end-to-end and future-ready sustainability, risk, and compliance platform, we strengthen supply chains, safeguarding clients’ reputation and profitability. Our advanced AI and comprehensive platform future-proof supply chains, delivering remarkable results and ensuring compliance globally.
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About Ivalua
Ivalua is a leading provider of cloud-based Spend Management software. Our complete, unified platform empowers businesses to effectively manage all categories of spend and all suppliers, increasing profitability, improving ESG performance, lowering risk and improving employee productivity. We are trusted by hundreds of the world’s most admired brands and recognized as a leader by Gartner and other analysts.
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About Zycus
Zycus is the pioneer in Cognitive Procurement software and has been a trusted partner of choice for large global enterprises for two decades. Zycus has been consistently recognized by Gartner, Forrester, and other analysts for its Source to Pay integrated suite.
Zycus powers its S2P software with the revolutionary Merlin AI Suite. Merlin AI takes over the tactical tasks and empowers procurement and AP officers to focus on strategic projects; offers data-driven actionable insights for quicker and smarter decisions, and its conversational AI offers a B2C type user-experience to the end- users.
Zycus helps enterprises drive real savings, reduce risks, and boost compliance, and its seamless, intuitive, and easy-to-use user interface ensures high adoption and value across the organization. Learn more via zycus.com
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