Transform Your Supply Chain Planning and Marketing Strategies with Google Cloud and SAP Integration
Transform Your Supply Chain Planning and Marketing Strategies with Google Cloud and SAP Integration
June 8, 2026 | Manju Devadas
Blog / The Dawn of Agentic Commerce: How to Stop Guessing and Build a Make-to-Order AI Backbone with Pi Agent in Gemini Enterprise
My day typically starts at 4:30 a.m. local time, deep-diving into business problem formulation, mapping solutions to AI platforms, and, most importantly, managing organizational change. This continues late into the night until I am mentally exhausted after spending the day running agents, testing prompts, attending meetings, and engaging with customers, partners, and the broader ecosystem.
2026 is different, and it is happening at a pace I have not witnessed in 26 years in Silicon Valley. Why is this happening, and why now? Legacy software and services are collapsing simultaneously in the supply chain planning world, and new leaders are emerging. Thankfully, we spent a decade preparing for this. For more on this topic, read the Pluto7 blog, with additional insights coming soon in an upcoming book.
A massive shift is happening right now in global manufacturing across Retail, CPG, Semiconductor, and many other industries. We are moving beyond the era of e-commerce and have already entered a phase that will be exponentially larger: Agentic Commerce.
Let’s focus on one use case—inventory positioning—to understand the magnitude of this change.
In the near future, the businesses that survive will not be the ones with the largest warehouses or the lowest manufacturing costs. The winners will be those that can seamlessly connect the digital retail storefront directly to the factory floor, transforming rigid, legacy Make-to-Stock operations into dynamic, real-time Make-to-Order ecosystems. With humanoid robotics, factories in the United States and other local markets may eventually become more cost-effective than shipping products from China.
For decades, the standard playbook has eroded margins. Supply chain leaders have been forced to forecast demand months in advance, overproduce to avoid stockouts, and then discount aggressively to clear excess inventory. The root cause? Disconnected systems and a reliance on intuition or outdated batch data.
Even today, nearly 80% of planners make decisions using Excel despite owning sophisticated software such as Kinaxis, o9, Blue Yonder, SO99+, SAP IBP, SAS, and many others. These planning mistakes often result in at least a 2% revenue loss, if not more. For more information, read this blog.
However, forward-thinking brands are already rewriting the rules by using Pi Agent in Gemini Enterprise within their own Google Cloud tenant, built on the right AI foundation.
If you want to achieve the real-time, 60-second planning that Agentic Commerce demands, you cannot rely on legacy tools.
Traditional systems such as Kinaxis, SAP IBP (Integrated Business Planning), and Oracle ASCP were built for a different era. They depend on historical batch processing, rigid data models, and siloed modules. They are inherently designed for the slower Make-to-Stock world, forcing planners to wait days or even weeks to understand the impact of a demand shift.
At the other end of the spectrum, platforms like Palantir offer advanced data integration capabilities, but at a staggering cost. They are widely known for being expensive, requiring armies of specialized FDE consultants, extensive custom coding, and large multi-year deployments just to get started.
You don’t need a rigid legacy system, nor do you need a billion-dollar bespoke science project. You need an AI foundation that scales rapidly and transparently.
Planning in a Box provides exactly that.
Built on a transparent “glass box methodology“—meaning you can clearly see why the AI is making a recommendation—it does not require you to rip and replace your existing IT infrastructure.
The Pi Agent platform coexists seamlessly with your ERP, WMS, TMS, and PLM systems. It acts as an intelligent overlay—an AI Backbone—powered by more than 100 specialized sub-agents working in harmony to execute 60-second planning loops.
These sub-agents autonomously connect the entire lifecycle:
Demand Sensing → Demand Forecasting → Demand Planning → Inventory Positioning → Production Planning → Production Scheduling → Design → Logistics → Returns Management
The true power of Agentic Commerce lies in eliminating the silos between marketing, fulfillment, production, and reverse logistics.
It starts with hyper-accurate demand sensing. Pi Agent ingests top-of-funnel signals—live digital ad performance, real-time website traffic, and cart abandonment data—and instantly connects them to inventory and ATP (Available-to-Promise) engines.
If a digital advertising campaign suddenly goes viral, you need to know within seconds whether you have the inventory required to fulfill the surge, ensuring you only promise what you can actually deliver.
When inventory positioning goes wrong, the losses can be staggering. I witnessed this firsthand when Cisco recorded a $2.1 billion inventory write-off in 2001.
But this process must go one step deeper by aligning with manufacturing yield management.
When a demand spike is detected, the AI Backbone dynamically adjusts the factory floor. It ensures that raw materials, machine capacity, and labor are instantly reallocated to maximize manufacturing yield for the highest-margin products, eliminating the waste associated with producing low-demand variants.
Finally, the system addresses one of the biggest margin killers: returns management.
In a world where e-commerce returns can destroy profitability, sub-agents continuously monitor return patterns in real time. The AI Backbone immediately adjusts future demand forecasts, routes returned goods to regional hubs with stronger local demand, and even modifies manufacturing specifications when defect patterns emerge.
When demand sensing, ATP, yield management, and returns management are aligned, organizations gain the ultimate superpower: defect-free inventory positioning.
This ensures the right SKU is available at the right regional hub at the exact moment a customer clicks “Buy.”
This is not just an apparel strategy, a semiconductor strategy, or a plumbing fixtures strategy. Whether you sell through B2B, B2C, or e-commerce channels, if manufacturing is core to your business, this approach applies to you.
Let’s look at how Planning in a Box enables this reality across very different industries.
Denim forecasting and large-scale retail operations have traditionally been rigid and difficult to manage.
With Planning in a Box, Levi’s and retailers such as Kohl’s analyze live regional store trends and digital cart additions to forecast demand and position inventory dynamically. This ensures Kohl’s shelves carry the exact styles and sizes customers want, significantly reducing markdowns.
Tacori aligns intricate jewelry craftsmanship and production yield directly with live storefront demand.
California Design Den (CDD) matches dye lots to emerging digital consumer trends, while Lulu’s prevents costly overproduction and protects margins in real time.
In the world of housing products and plumbing fixtures, a single inventory mismatch can delay entire construction projects.
Lixil moves beyond static 60-day forecasts by using demand-sensing agents to autonomously position bulky inventory across regional hubs, ensuring accurate ATP commitments for builders.
Consumer packaged goods companies live and die by seasonal demand spikes and regional distributor pull.
Corona.co uses Pi Agent in Gemini Enterprise to execute 60-second ATP-driven planning, dynamically adjusting production lines and routing supply precisely where regional demand emerges.
Technology manufacturers increasingly use AI to manage demand volatility and returns.
By improving demand prediction accuracy, Seagate can better plan inventory and production, capabilities that are more critical than ever in semiconductor manufacturing.
The shift to Agentic Commerce is urgent, but it doesn’t have to be slow.
Unlike the lengthy and painful implementations associated with legacy ERP upgrades, Planning in a Box is designed for speed. We deliver value quickly through a four-week pilot followed by a three-month production rollout at scale.
Agentic Commerce is not a future-state vision that lies five years away—it is happening now.
Every company must evolve toward Agentic Commerce within the next 18 months.
The gap between winners and losers is widening at an unprecedented rate. If you are still running daily, weekly, or monthly batch planning on a legacy ERP while your competitor is executing 60-second planning powered by an AI Backbone that connects web traffic, Google Ads, Facebook ads, manufacturing yield, and returns management, you are operating at a significant disadvantage.
Failing to make this transition within the next 18 months exposes your business to substantial risk.
Companies that delay could lose 10% to 20% of revenue through stockouts, margin-eroding markdowns, rising customer acquisition costs, and supply chain inefficiencies. In highly competitive industries, organizations that fail to adopt a Make-to-Order AI Backbone may simply not survive through the end of the decade.
Your supply chain is either a reactive cost center that continuously bleeds cash, or it is a proactive Make-to-Order competitive weapon.
The technology required to connect your storefront directly to your factory floor already exists.
For all of this to work, you need people trained in AI.
AI cannot run itself. Organizations still need the right people to drive change, making change management one of the most critical aspects of the journey.
Empower your employees to become an agentic workforce (explore Operations in a Box within Pi Agent and Gemini Enterprise).
Are you going to start preparing now, or are you going to keep guessing until it’s too late?
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