Your Guide to Gaining the Competitive Edge Using Next Gen Integration
GAIN INSIGHTS
“The future of technology adoption will resemble less of a quick fix—like taking a pill—and more of a gradual, sustained effort, akin to using a treadmill or free weights. An essential but often overlooked aspect of adopting emerging technologies is the mindset and behavioral change that must occur within the enterprise to ensure that the technology can truly perform the work
– Joe Cicman, Principal Analyst, Forrester
Over the next ten years, a key transformation in supply chains will be the gradual integration of generative AI across various functions – not as a one-off solution, but as a dynamic, continuously evolving tool that adapts in real-time to B2B market disruptions.
IN THIS INTERACTIVE GUIDE
Felice Miller, Business Strategy Leader for Supply Chain & Operations at Microsoft, and Arvind Rao, CTO at EdgeVerve, share insights with CGT on the future of B2B integration.
Discover what the smartest players are prioritizing as they transform their operations and prepare for
what’s next.
it was designed to do.”
of all supply chain executives expect to experience a supply chain shock in the next 24 months as a result of various external challenges including:
44%
Source: Deloitte, Is Your Supply Chain Trustworthy?
46%
price volatility
42%
resource
shortage
32%
geopolitical
instability
44%
inflation
As any consumer goods executive will tell you, the supply chain has been under pressure the last few years, thrown into disarray by pandemics, global conflict, environmental factors, and more. The need to be resilient has never been more evident.
Some of the top current challenges are:
Data Fragmentation and Integration
The integration of data from diverse sources with different formats and standards remains a monumental task.
Silo Management
These silos prevent a unified view which is essential for strategic decision-making, especially in dynamic markets.
Black Swan Events
Supply chains need to be resilient yet flexible, capable of adapting quickly to changes like geopolitical disruptions, natural disasters, or sudden shifts in demand.
Adoption of AI and New Technologies
The shift towards autonomous supply chains involves addressing both technological and human elements.
Supply chains need to be resilient yet flexible, capable of adapting quickly to changes like geopolitical disruptions, natural disasters, or sudden shifts in demand.
The integration of data from diverse sources with different formats and standards remains a monumental task.
The shift towards autonomous supply chains involves addressing both technological and human elements.
These silos prevent a unified view which is essential for strategic decision-making, especially in dynamic markets.
Emboldened by leaps in technologies like generative AI, leaders are looking for smart solutions that create a more connected ecosystem – one that transforms the supply chain from
a cost center to a value creator.
In discussing what they’re seeing among customers in their context, Felice Miller shares a few key themes:
Enhanced Precision: AI enhances existing planning and execution systems for greater speed, precision, and predictability.
Real-Time Execution: The shift is moving beyond dashboards to enable real-time execution across interconnected systems.
Cascading Alignment: AI helps manage cascading impacts in supply chains, aligning consumer demand predictions with network and warehouse capacity.
Automated Insights: Generative AI delivers analytical horsepower, processing massive datasets and automating tedious workflows
“Consumer goods companies are adopting digital disruptors to optimize supply chains, shifting from reactive to proactive and predictive models. This change aims to anticipate consumer demand, improve forecasting accuracy, and overcome challenges like siloed data and disconnected systems.
– Felice Miller, Microsoft
The goal is to simplify and optimize B2B operations across the entire supply chain, enhancing coordination, execution, and collaboration.”
Chain Reaction: Autonomous Systems Will Bring the Future Full Circle
Source: EY 2024 Supply Chain Survey: Bridging the C-Suite Disconnect
C-suite leaders expect to achieve a mostly autonomous supply chain by 2040.
27%
supply chain executives expect to achieve a mostly autonomous supply chain by 2030.
39%
C-suite leaders expect to achieve a mostly autonomous supply chain by 2040.
27%
The journey to an autonomous supply chain is all about using data to optimize processes and become more predictive, ultimately creating a system that can run itself. It’s about moving from reacting to changes to proactively adapting to them and orchestrating everything in a seamless, self-driving way.
“Take demand forecasting, for instance. With gen AI, you can analyze historical data alongside unstructured inputs like weather or geopolitical events in real time. This helps the supply chain prepare for different scenarios, cut down on overstock and stockouts, and reduce the bullwhip effect. You can even run "what-if" simulations to plan for disruptions – whether it’s a supplier delay or a logistics hiccup – and adjust sourcing strategies or optimize routes on the fly.”
– Felice Miller
“Take demand forecasting, for instance. With gen AI, you can analyze historical data alongside unstructured inputs like weather or geopolitical events in real time. This helps the supply chain prepare for different scenarios, cut down on overstock and stockouts, and reduce the bullwhip effect. You can even run "what-if" simulations to plan for disruptions – whether it’s a supplier delay or a logistics hiccup – and adjust sourcing strategies or optimize routes on the fly.”
– Felice Miller
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An Autonomous Supply Chain:
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Operates in a continuous cycle of learning, adapting, and improving.
“For global companies, compliance is a big challenge, with ever-changing regulations across hundreds of countries. Automating the tracking and management of these regulations would remove a huge burden. These foundational improvements—enhancing accuracy, automating repetitive tasks, and enabling real-time decision-making—are the building blocks of a truly autonomous supply chain.”
– Arvind Rao
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CASE STUDY
This chimes with what CPG companies themselves are saying. Speaking at Groceryshop 2024, Gallo’s VP of Supply Chain Excellence, Nitin Murali, said the company is focused on creating a four-part center of excellence.
“Eventually what we want to do is create a really connected ecosystem where we can clearly understand where the value is and what value is driven by each part of the chain.”
“For global companies, compliance is a big challenge, with ever-changing regulations across hundreds of countries. Automating the tracking and management of these regulations would remove a huge burden. These foundational improvements—enhancing accuracy, automating repetitive tasks, and enabling real-time decision-making—are the building blocks of a truly autonomous supply chain.”
– Arvind Rao
Data Harmonization Will Fastrack Agility in Two Ways
“The end goal of supply chain data harmonization is enabling a single source of truth. With gen AI, businesses can harmonize inconsistencies, like product codes or formats, to unlock faster and more reliable forecasting, demand sensing, and decision-making. This capability optimizes processes and
– Felice Miller, Microsoft
improves the overall customer experience.”
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6 in 10 global organizations plan to invest in digital technology to bolster their supply chain processes, data synthesis, and analysis capabilities.
Source: KPMG
CLOSE
“In the complex landscape of supply chains, AI emerges as the most effective solution for managing different data formats. It automatically translates product categories between various taxonomies and rationalizes data in ways that traditional rules-based techniques find un-scalable. This long-standing challenge is being addressed more effectively with AI technologies.”
– Joe Cicman, Principal Analyst, Forrester
Two Considerations for Gen AI and Data Harmonization:
Getting data ready for generative AI
Data harmonization across disparate systems will be crucial for modern B2B integration, helping standardize and reconcile data formats and naming conventions in messy and chaotic supply chain data.
Future Prediction: Companies that prioritize data harmonization will experience a faster time to market due to streamlined integration and reduced errors.
Transforming Teams: Technology, Tasks, and Trading Partners
Integrating AI is a marathon, not a sprint.
“With generative AI, we’re redefining how the world works at one of the most significant technological inflection points of our time. Generative AI has the ability to empower organizations to adapt to their unique contexts and adopt a goal-based approach. This involves leveraging optimization strategies in highly complex business environments and fostering collaboration within connected ecosystems. By integrating diverse signals from trading partners across networks, businesses can drive greater operational awareness and unlock data for near real-time insights.”
– Felice Miller
“With generative AI, we’re redefining how the world works at one of the most significant technological inflection points of our time. Generative AI has the ability to empower organizations to adapt to their unique contexts and adopt a goal-based approach. This involves leveraging optimization strategies in highly complex business environments and fostering collaboration within connected ecosystems. By integrating diverse signals from trading partners across networks, businesses can drive greater operational awareness and unlock data for near real-time insights.”
– Felice Miller
click here
According to McKinsey research, organizations looking to implement Gen AI successfully must focus on two key areas:
Targeted Use Cases: Instead of applying AI broadly across many areas, they should prioritize specific domains where AI can have the greatest impact, ensuring efficient resource allocation.
Scaling AI: Moving from small-scale pilots to full deployment requires not only technical integration and data management but also significant organizational adjustments. These include restructuring processes and systems to support and sustain widespread AI adoption.
Source: McKinsey: LLM to ROI: How to scale gen AI in retail
“The last three years of uncertainty have blurred the line between business and technology strategies to the point that they must be considered together.
Supply chain leaders must have an understanding of the strategic, disruptive, and unavoidable technologies that will impact their planning processes over the next five years.”
– Simon Jacobson, VP analyst in Gartner’s supply chain practice.
The Key Factors Motivating Supply Chain Investments in Emerging Technologies Over the Next 5 Years Are:
36%
Support new business/ operating model
35%
Improve supply chain resiliency/agility
35%
Enhance decision making
31%
Improve process efficiency/
productivity
26%
Address labor constraints or shortages
Source: Gartner
How AI Co-Pilots Are Changing the Supply Chain Game
“Thanks to co-pilots, we're able to rethink and redefine the relationship between data and users. Traditionally, accessing usable business data involved long cycles, static dashboards, and layers of IT barriers. With the advancement in data as well, now we have almost reached a place where we have truly democratized access to data to everyone, whenever the business needs it.
With advancements like gen AI and large language models (LLMs), co-pilots can help reduce bottlenecks, automate decisions, and integrate into workflows. What once took hours or days now happens in minutes, transforming business processes and unlocking unprecedented efficiency.”
– Arvind Rao, CTO EdgeVerve
“[With co-pilots], you don’t need to be an expert in any specific supply chain system to take meaningful actions or access the business answers you need. Co-pilots democratize information across the organization, empowering team members to respond quickly to changes – especially in today’s volatile environment with fluctuating consumer demand.”
– Felice Miller
“AI, Gen AI, and agentic AI have the ability to significantly transform almost all processes. Wherever humans make decisions, agents can augment this process—taking on many decisions autonomously—and where human input is needed, they provide the right contextual data, insights, and recommendations to enable quicker, more informed choices. Additionally, agentic AI can orchestrate complex business processes across partners and systems.”
– Arvind Rao
AI-powered co-pilots are reshaping how organizations operate, with their intuitive usability and rapid ability to turn complex data into actionable insights encouraging uptake among workers across the business.
A few features of co-pilots include:
Microsoft Recommendations
5 Key Strategies for Harnessing Gen AI to Build a Resilient, Collaborative B2B Supply Chain
Start Small, Scale Smart Target specific areas in your supply chain where AI can make the biggest impact—whether that’s demand planning or inventory management—before scaling up to ensure efficient use of resources.
Automate the Chaos Leverage AI-powered data mapping to harmonize data across systems, cutting down on the chaos of mismatched formats, disparate taxonomies, and manual processes. This paves the way for faster, cleaner B2B integrations.
Build for Resilience, Not Reaction Generative AI isn’t just for quick fixes — use it to continuously learn and adapt your supply chain to market disruptions, making your systems proactive, not just reactive.
Break Down the Silos Integrate API-led, AI-driven solutions to create a more connected ecosystem. These composable architectures help cut through siloed operations, boosting operational agility and lowering costs.
Ready to forge ahead with a more resilient supply chain?
Unlock the full potential of generative AI and build a resilient, collaborative B2B ecosystem.
Contact EdgeVerve or Microsoft today to explore tailored solutions that drive agility and innovation in your supply chain.
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Automates key tasks like placing purchase orders when specific triggers are hit or deciding between air freight and container shipping based on situational needs.
Replaces manual processes such as order-related email processing, follow-ups, and back-and-forth communications.
Introduces capabilities like automatic negotiation with suppliers and advanced scenario planning.
Automates quality control checks and ensures compliance with changing regulations.
Taps data and analytics to respond proactively to disruptions.
Get Data AI-Ready Before you dive in, ensure your data is prepped for AI integration. Investing in data harmonization upfront will smooth out any kinks in real-time, future-proofing your B2B ecosystem and accelerating time-to-market response.
REPORT
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“Thanks to co-pilots, we're able to rethink and redefine the relationship between data and users. Traditionally, accessing usable business data involved long cycles, static dashboards, and layers of IT barriers. With the advancement in data as well, now we have almost reached a place where we have truly democratized access to data to everyone, whenever the business needs it.
With advancements like gen AI and large language models (LLMs), co-pilots can help reduce bottlenecks, automate decisions, and integrate into workflows. What once took hours or days now happens in minutes, transforming business processes and unlocking unprecedented efficiency.”
– Arvind Rao, CTO Edgeverve
“Thanks to co-pilots, we're able to rethink and redefine the relationship between data and users. Traditionally, accessing usable business data involved long cycles, static dashboards, and layers of IT barriers. With the advancement in data as well, now we have almost reached a place where we have truly democratized access to data to everyone, whenever the business needs it.
With advancements like gen AI and large language models (LLMs), co-pilots can help reduce bottlenecks, automate decisions, and integrate into workflows. What once took hours or days now happens in minutes, transforming business processes and unlocking unprecedented efficiency.”
– Arvind Rao, CTO Edgeverve
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Plain-Language Power:
Interact naturally to get answers, insights, and guidance.
Predictive Smarts:
Ability to anticipate issues like maintenance needs or sourcing challenges before they happen.
Collaboration:
Sharing insights seamlessly across teams, vendors, and partners for smarter decision-making.
Data for Everyone:
Democratize critical knowledge, empowering users to respond quickly to changing demands.
Better Business Outcomes:
Streamline workflows, boost productivity, and drive efficiency across operations.
Microsoft Recommends:
Infosys Edgeverve Recommends:
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Tie every process improvement back to an end-consumer experience that also links to measurable business outcomes.
Harmonize and unify data for accurate, actionable AI insights.
Use AI to anticipate market demands, mitigate supply chain risks, and unlock new opportunities for sustainable growth.
Unlock unstructured data for richer, more informed decisions and aim for a single source of truth.
Improve visibility and efficiency with Gen AI-powered automation and co-pilots.
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EdgeVerve Recommendations
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A solid data strategy isn’t optional—it’s the backbone of AI success. Focus on responsible data management to train models effectively and ensure reliable outcomes.
Data comes in all shapes and sizes – structured, unstructured, and now AI-generated. Use AI to harmonize and simplify mismatched formats so your supply chain runs smoothly.
Streamline how data flows between teams and organizations to save time and reduce errors, for example in emails.
Build in checks to verify that insights and recommendations are accurate and actionable.
Generative AI can make sense of messy data – like matching product codes or harmonizing information across platforms – helping you unlock smarter, faster decisions.
TOPICS AT A GLANCE:
Current Challenges | Current State of Supply Chain Integration
Autonomous Systems | Data Harmonization
Implementing Gen AI | Key Factors of Investment
AI Co-Pilots | 5 Strategies for Harnessing Gen AI
The Current State of
Supply Chain Integration
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AI-Powered Supply Chain: