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
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 Disconnected systems and a reliance on intuition or outdated batch data.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?
ABOUT THE AUTHOR
You hear a lot of new supply chain terminologies alongside the old ones—IBP, S&OP, MRP, DDMRP. But in reality, alignment is still the true differentiator. A new acronym or a rigid dashboard will not fix a culture of “synchronized confusion.” If Sales, Finance, and Operations are all working from different spreadsheets, your ERP becomes nothing more than an expensive archive.
To achieve a true single version of reality and prepare for the shift toward Agentic Commerce organizations need to move beyond legacy “Systems of Record” and adopt a System of Action.
This is where Pi Agent on Gemini Enterprise changes the game. It compresses the traditional, siloed Integrated Business Planning (IBP) cycle into a real-time, 60-second autonomous decision engine.
Traditional ERPs and SaaS platforms were built for a slower business environment. They were designed around stability, batch processing, and human-led CRUD (Create, Read, Update, Delete) operations. These systems are excellent at telling you what happened.
Planning in a Box – Pi Agent on Gemini Enterprise functions differently. It acts as a System of Action that sits on top of your existing enterprise infrastructure including SAP, Oracle, Salesforce, and manufacturing systems—and shifts the organization from an “analyze, then act” approach to a continuous “sense, decide, and act” loop.
Instead of depending on planners to manually bridge disconnected data silos, Pi Agent leverages an Autonomous Council – a network of 100+ specialized micro-agents for functions such as Demand Sensing, Inventory Visibility, Procurement, Logistics, and Supply Planning.
Leveraging Pi.Unify, Pi Agent creates a real-time agentic foundation establishing a single source of truth across Sales, Finance, Operations, and Supply Chain teams. The result is alignment without endless meetings, conflicting spreadsheets, or delayed decision-making.
Traditional S&OP cycles often take weeks, while the business changes daily. Forecasts become outdated before decisions are executed, factories operate under pressure, and planners spend more time reconciling data than responding to disruption.
Pi Agent addresses this challenge by collapsing the traditional planning cadence into a 60-second autonomous decision cycle.
Here’s how it works:
Specialized AI agents continuously ingest and process hundreds of real-time signals simultaneously, including:
The platform identifies risks and opportunities instantly—whether it is declining service levels, excess inventory, supplier delays, or margin erosion.
Instead of relying on static dashboards or executive debates over forecast bias, Pi Agent runs over 10,000 digital twin simulations in seconds.
These simulations evaluate multiple supply, demand, inventory, and logistics scenarios to determine the most resilient and profitable path forward.
Once the optimal scenario is identified, Pi Agent autonomously writes decisions back into the enterprise systems of record, including ERP, TMS, CRM, and manufacturing environments.
This transforms planning from a reactive process into a continuously adaptive operating model.
Commerce is rapidly becoming agent-driven.
In the era of Agentic Commerce, the biggest challenge is no longer access to data. The real constraint is the latency between identifying a signal and acting on it.
AI agents will increasingly discover products, evaluate constraints, negotiate supply conditions, and execute transactions autonomously on behalf of customers and businesses. As a result, demand patterns will become far more dynamic and less predictable than traditional planning models were designed to handle.
Organizations that still rely on cycle-based planning, disconnected spreadsheets, and manual intervention workflows will struggle to keep pace. Opportunities will be missed not because the data was unavailable, but because the organization could not act fast enough.
A System of Action changes this dynamic completely.
When the platform can ingest signals, align constraints across Finance, Supply, and Demand, simulate outcomes, and execute the optimal decision in near real time, the organization stops debating whose spreadsheet is correct and starts operating from a shared version of reality.
The future of supply chain management will not be defined by static dashboards or isolated planning tools. It will be defined by systems that can think, collaborate, simulate, and act autonomously across the enterprise.
Pi Agent on Gemini Enterprise enables organizations to move from fragmented planning processes to intelligent, autonomous decision-making at enterprise scale without replacing their existing systems.
It transforms SAP, Oracle, Salesforce, and manufacturing platforms from passive Systems of Record into an active, intelligent System of Action built for real-time supply chain execution.
See how Pi Agent on Gemini Enterprise enables autonomous planning, real-time decision-making, and cross-functional supply chain alignment in under 60 seconds.
Request a Demo to experience how a System of Action can transform your supply chain operations.
ABOUT THE AUTHOR
