Supply Chain 2035: How AI, data, and digital transformation will redefine supply chain management

From digital hype to pragmatic transformation

A new study by SAP’s Industry Transformation Advisory and Kühne Logistics University shows how supply chain management will evolve by 2035: more connected, data-driven, and adaptable. Drawing on the latest research, the experience from SAP’s Business Consultants, and surveys of 660 supply chain experts, the research tracks a clear shift from past tech-driven euphoria to pragmatic, use-case-led transformation – where value must be proven before scaling.

The starting point is a study that SAP conducted ten years ago with researchers from RWTH Aachen. Back then, the digital hype promised sweeping change – 3D printing, augmented reality (AR), IoT, social data forecasts, and drone delivery. Reality proved slower realization, caused by underestimated complexity, immature solutions, skills gaps, and inconsistent data often stalled progress, among other issues. Pioneers still succeeded, typically by targeting specific, high-ROI use cases that improved delivery reliability, reduced disruptions, and created tangible user value.

However, external shocks like the pandemic, geopolitics, or economic volatility have reinforced a new discipline. As indicated within a recent follow-up study, companies invest only when benefits are clear, start small, and scale after results are proven. The winners are building the foundations for a truly digital supply chain: high-quality data, integrated platforms, and teams fluent in AI.

Looking into the future, the present study paints a vision for the supply chains of the future and identifies "no-regret moves" companies should act on now. The logic is simple and follows the recommendation of Wayne Gretzky, who said that good players skate to the puck, while great players to where the puck is going to be. Applied to supply chains, this means strengthening data governance, standardizing processes, and systematically introducing employees to AI tools before the pressure to do so becomes unavoidable.

The study consists of deep dives into 5 key areas: Plan, Source, Make, Deliver, and People. Here are key highlights for each area.

By 2035, planning will look fundamentally different – more intelligent, more integrated, and more automated.

• Planning is becoming a data-driven early warning and control system: Integrated, multi-horizon planning anchored in high-quality, harmonized data and a company-wide IBP (Integrated Business Planning) and S&OP (Sales and Operations Planning) backbone is expected to be decisive by 2035; lacking this integration correlates with loss of operational control and competitiveness.
• AI and autonomous agents will materially reshape planning: Forecasting accuracy and proactive risk detection rise with expanded data sources; planning becomes simpler and more intuitive as agents automate repetitive tasks and shift human roles toward analysis and decisions – yet most firms today remain far from this state due to data and maturity gaps.
• Operating models will diverge while end-to-end integration advances: Strategic, bespoke planning gravitates to agent-based AI, whereas standardized environments trend toward market-standard platforms and planning-as-a-service; cross-company planning, simulations, and AI-assisted digital twins become practical as modeling agents reduce complexity and improve scalability.

By 2035, today’s routine purchasing tasks will run fully autonomously, freeing professionals for strategic and risk mitigating work.

• Procurement is changing under stronger macro pressures and widespread AI. Geopolitics, sustainability, raw-material scarcity, and the battle for top talents matter more. Integrated apps with semantic data, AI agents, analytics, and business network signals start to shape every process, with impact differing by industry and business model.
• Vision exceeds today’s maturity. By 2035, many expect a bigger strategic role for procurement and better AI-driven outcomes with high-quality data. Yet today, only 12% report a C-level integration and 3% strong AI analytics. On the other hand, 28% expect a strategic role for procurement and 31% better AI outcomes, revealing a large execution gap.
• End-to-end data and process design are the decisive enabler for AI in sourcing. Category strategies managed in apps, standardized BPMN processes, modern integrated purchasing tools, and a shared semantic data model enable full visibility and analytics. As data quality improves, adoption of AI agents and orchestration across buyers, requestors, and suppliers significantly increases, driving more agent-to-agent interactions across networks.

By 2035, many organizations need to overcome the gap between their bright ambitions for 2035 and the maturity of their current digital environment.

• Production is the nerve center of the future supply chain, driven by data, networks, and the pursuit of flexibility. Real-time data and AI link design, manufacturing, logistics, and recycling. While geopolitics, energy volatility, and sustainability pressures push regionalization, cost discipline remains essential.
• Ambition exceeds current maturity. Leaders describe a connected, AI-enabled, and sustainable factory for 2035, yet execution today is fragmented. The most significant gaps are digital continuity and interoperability, clean and connected data, circular models and closed-loop flows, and the step from AI pilots to scale.
• The 2035 factory is autonomous, modular, and circular. AI orchestrates material flows and schedules; mobile robots and self-learning systems adapt in real time; digital twins and IoT create a lifecycle memory for each product – enabling traceability, predictive maintenance, precise material returns, and continuous design improvement. Human roles shift to strategic, creative, and supervisory work, and scaling requires new skills, structures, and leadership, with progress coming from integrated data, technologies, and processes rather than isolated experiments.

By 2035, global competition will drive logistics to become more efficient, transparent, and cost-effective.

• Logistics sits at the heart of cost, service, and resilience. Tight digital integration across transport and warehousing prevents bottlenecks, reduces costs, and boosts service. AI, robotics, and digital platforms are ready and proving value: tightly integrating transport, yard, and warehouse unlocks speed, reliability, and transparency – preventing bottlenecks, reducing costs, and elevating service even as energy, transport, and labor pressures rise.
• By 2035, 39% of our surveyed experts expect data-driven warehouses, 28% expect autonomous vehicles or drones, 28% see AI agents supporting dispatchers and warehouse teams, and 20% expect real-time cross-company ecosystems. However, today, only a small proportion use real-time data comprehensively in warehousing, achieve real-time transport transparency with accurate ETAs, or have collaborative planning with partners.
• The greatest gains will accrue in environments with end-to-end, real-time data and robust orchestration; in these settings, AI agents and flexible robotics deliver measurable improvements in estimated time of arrival (ETA) accuracy, utilization, and error rates, while firms with fragmented systems and a cost-center mindset progress slowly despite mature technology.

Supply chain managers are moving away from reactive daily tasks – like reviewing schedules and fixing delivery issues – toward a data-driven, predictive role that anticipates problems before they arise.

• Cloud platforms and AI copilots amplify human impact. Automation clears routine work so teams can focus on strategic, end-to-end orchestration; tighter human-tech collaboration lifts speed, resilience, and transparency despite talent constraints.
• Decisions will move from execution to design, reaction to anticipation, and KPIs to outcomes. The control tower's morning review surfaces risks and opportunities at a glance, AI agents propose, AI agents propose scenarios, people adjust policies, run Digital Twin experiments, and make a few high-impact calls – supported by new roles like Network Orchestrator, Scenario Strategist, and Data Steward.
• The importance of developing T-shaped skills (a combination of broad, cross-functional knowledge and deep expertise in one specific area) will become even more significant. Combining broad end-to-end process understanding, data and digital fluency, and cross-functional collaboration with deep expertise in priority domains such as planning, logistics, sourcing, or customer service. With sharpened strategic judgment, a strong sense of responsibility, and the ability to orchestrate ecosystems, the supply chain teams of the future will turn tools into outcomes.

The research is clear: to lead in 2035, start now. Competitive advantage in 2035 will not be won by technology alone. It will be built on fundamentals: data quality, process discipline, and human capability. Companies that invest in these foundations now create the conditions for AI and automation to deliver real value, not just proof-of-concepts. The supply chain of 2035 will belong to those who treated today as a starting line.

Many of the changes described here do not require a large-scale project to get started – however, they do require a clear starting point. That is exactly what we developed the COO Lab for: a one-day workshop in which we work together with your team to apply our vision for the future to your specific situation. We share our perspective on developments up to 2035, discuss where your organization stands today, and develop potential priorities as well as an initial roadmap. The result is not a glossy strategy paper, but a shared understanding of which steps make sense right now. For more information, please visit: CxO Labs & Business Transformation Lab.

• Part 1: How Future Supply Chain Management Works
• Part 2: How Data, AI, and Agents are Changing Supply Chain Planning
• Part 3: Artificial Intelligence Determining Future Purchasing?
• Part 4: The Factory of the Future: Production in the Age of AI, Circular Economy, and Autonomous Systems
• Part 5: The New Era of Logistics: AI and Robotics in Action?
• Part 6: How Will Everyday Work Change in the Future of the Supply Chain?