I left this year’s Gartner Supply Chain Planning Summit surprised but also validated. Validated, because many of the themes we’ve been investing in for years: explainability, scenario thinking, the limits of automation and the evolving role of the planner were front and center.
Validated, because the conversations reinforced what our customers are already telling us: the future of supply chain planning isn’t about chasing autonomy. It’s about designing tools that work the way real organizations work, balancing constraints, honoring complexity and giving planners the leverage they need.
Surprised, because for all the talk about planning, execution still sat in the background.
Here are some things that stood out for me.
Planning Dominated the Conversation, but Execution was Lacking
Across sessions were recurring themes of planning architectures, scenario modeling, risk management, resilience and planning governance. These are valuable topics, and they anchor important progress in the industry.
But amidst all the energy on planning, there was noticeably less focus on the bridge to execution: the place where plans either hold up or fall apart.
For organizations with complex, capacity-driven operations, execution is not a downstream afterthought. It’s the proving ground. Quality holds, CIP sequences, tank turns, line constraints and yield variability determine the viability of the plan as much as demand signals, forecast accuracy or tariff scenarios. Those organizations need systems that reflect the physics and rules of their operations to minimize the “recoverability” gap that traditionally exists when execution realities are not well understood or represented in plans. Planning only matters when it can be executed. That’s why our platform unifies planning and scheduling on one model, keeping the realities of the plant connected to the strategy of the business.
Execution belongs in the conversation, particularly in asset-intensive industries and we hope it will take a more central role in the years ahead. This is an industry-wide gap, not a Summit oversight. But it’s one we believe deserves more attention.
For planners living in capacity-intensive, constraint-heavy operations, the real bottlenecks happen on the plant floor. When those bottlenecks are treated as afterthoughts; no amount of scenario modeling can save the plan. Execution breaks, Excel fills the void, and trust in the system erodes.
Our view: planning only works when it reflects the physics of execution.
It’s also why Arkieva is explicitly built for process manufacturing, capturing the “last 5–10%” of constraints that most tools overlook, the very constraints that decide whether a plan will succeed.
AI Has Entered a Phase of Pragmatism
One of the most refreshing shifts at this year’s event was the tone around AI.
Gone was the narrative of fully autonomous supply chains running themselves. Instead, the conversation centered around practical use cases, time to value and explainability. The underlying message was:
AI is another tool in the toolkit, not a replacement for planners,
and not a magic wand for supply chain complexity.
The industry’s tone is shifting toward realism. In many ways, it’s catching up to the philosophy we’ve held for years.
- AI should serve the planner, not replace them.
- AI must be auditable, explainable and grounded in business logic, not a black box.
- A few high-impact use cases outperform a dozen theoretical ones.
- LLMs are one ingredient in a broader scientific foundation, not the entire recipe
The Next Phase of AI in Planning Isn’t Autonomy, It’s Acceleration
That’s why we’re investing in:
- Conversational, mobile-first experiences that let planners express intent without wrestling with interfaces.
- Transparent, auditable logic that explains why the system recommends a given action.
- Integrated planning and scheduling models that capture the true constraints, not sanitized approximations.
- Problem localization, so issues are addressed at the source before they ripple outward.
- Security and control that protect customer data and keep AI behavior predictable.
Gartner Confirmed the Industry Is Shifting Toward Practical, Domain-Aware Solutions
The Summit made one thing clear: the market is moving past abstract promises and toward solutions that can stand up to real operational complexity.
Organizations—especially those running asset-intensive, constraint-heavy supply chains, are not asking for “autonomy.” They’re asking for partners who can combine scientific optimization, transparent logic and deep domain modeling so planners can trust that a plan survives first contact with the plant floor.
This is what a pragmatic era looks like: not less science, but better-targeted science; not fewer promises, but promises that withstand operational pressure.
If this grounded, execution-connected approach aligns with where your supply chain is heading, we’d welcome a deeper conversation about your constraints, your plants and how a more realistic planning foundation can improve adherence and responsiveness across your network.
