AI for Inventory Management
The Growth of AI
Artificial Intelligence (AI) has sparked a data revolution that is transforming our world in many ways. A study by PwC states that the global gross domestic product (GDP) will increase by 14 percent by 2030 due to the adoption of AI, contributing an additional USD$15.7 trillion to the worldwide economy. Another study from the Economist Intelligence Unit suggests that, in the next five years, business executives across the globe expect AI to have a positive impact on growth (90%), productivity (86%), and job creation (69%) in their country and industry.
For manufacturers and wholesalers, AI is changing every aspect of the industry, from intelligent supply chains to product-as-a-service offerings, and to factories of the future. This accelerates the creation of new business models, products, services, and experiences.
Manufacturers often grapple with challenges such as fragmented data, inefficient processes, and the need for real-time decision-making directly at engineering workstations, factory lines, and field service locations. To address this, Microsoft and its partners are at the forefront, empowering industrial organisations to take advantage of generative AI to enhance operational processes and decision-making.
AI for Inventory Management: How It Works
Manufacturing success today requires a seamless integration of materials, technology, and resources. With these complex environments, AI is changing how we think about industrial operations. The merging of physical assets with AI, the Internet of Things (IoT), and automation solutions are enabling manufacturers to optimise production, reduce downtime, and improve real-time decision-making for greater competitiveness.
Microsoft Cloud consolidates data within the cloud, standardising its structure. Once organised, AI solutions can extract the hidden value of this data by analysing it for insights. This includes the increasing use of predictive maintenance which can identify patterns and anomalies on the shop floor that might signal potential equipment failures. AI-enabled factories empower manufacturers and wholesalers to better manage supply chains, anticipate production shifts, and optimise their resource allocation.
For critical operational needs, Microsoft Azure IoT Operations ensures your data is processed on-premises for immediate action before being transmitted to the cloud for further analysis. Azure IoT Operations employs an adaptive cloud approach, underpinned by Azure Arc, which enables manufacturers to unify data across their hybrid, multi-cloud, and edge environments. This adaptive cloud approach simplifies infrastructure management and security, while maximising resource utilisation and ensuring AI-powered solutions scale across production lines and multiple sites. By embracing this approach, manufacturers can streamline operations, enhance scalability, and establish a standardised architecture, ensuring resilience and continuous improvement throughout the enterprise.
Demand Forecasting
Using AI to analyse and learn from data can give companies access to innovative solutions that might not be apparent through traditional methods. Microsoft Dynamics 365 Customer Insights powers Copilot and agents with the latest customer information, enabling your teams to take advantage of this data directly within their daily workflow. Enriched with the real-time customer data, your business can access up-to-date customer profiles instantly, helping you accurately forecast demand, optimise inventory, and reduce waste.
Inventory Optimisation
AI for inventory management helps maintain optimal stock levels and reduce waste. Microsoft Dynamics 365 Business Central introduces intelligent AI agents to enhance efficiency and automation for small or medium-sized businesses (SMBs). These agents seamlessly integrate to execute complex tasks, generate reports, automate processes, and optimise order creation using natural language processing. This optimisation of the day-to-day operations will save time and increase efficiency, leading to a more productive workforce and improved margins.
Supply Chain Efficiency
AI improves predictive maintenance and reduces waste, cutting costs and preventing downtime. Microsoft Dynamics 365 Supply Chain Management advances autonomy by integrating intelligence, automation, and analytics to improve productivity and organisational adaptability. AI can help with repetitive tasks such as automating supplier communications, allowing manufacturers to deal with some of the less frequent challenges. Additionally, AI can also surface production data so manufacturers can identify any problem areas which can help to improve actual processes.
Automation
Generative AI can identify bottlenecks and optimise workflows to speed up production times and increase overall operational efficiency. This automation streamlines operations and allows manufacturers to focus on more strategic tasks, thereby driving productivity.
Challenges and Considerations
Scaling AI in inventory management can streamline operations, enhance demand forecasting, and reduce waste. However, to fully realise these benefits, manufacturers must overcome key challenges when implementing AI at scale.
Talent, skills, and data
One of the main challenges in scaling AI use cases is the deficit of talent, skills, and data. Manufacturers cite this as their toughest challenge in both the design and engineering of factory operations. Inadequate data quality and governance also hamper use-case development in both areas.
AI model governance is expected to be one of the big challenges on the factory floor, with 61% of manufacturers that have begun deploying AI use cases citing governance as a major data challenge. This underscores the difficulties in maintaining high standards of data quality, consistency, and compliance within the complex and variable manufacturing settings.
The solution? Implement robust frameworks around AI, and invest in training for staff to help them understand how to use AI within this governance to ensure quality, consistency and ethical use. This relies on ownership and accountability from leadership who can lead the way to a more efficient factory operation.
Data unification and contextualisation
Scaling AI use cases can be hindered without solid data foundations, as respondents have identified inadequate data quality (57%) and weak data integration (54%), as significant challenges. Only approximately one in five manufacturers have production assets with data prepared for utilisation in current AI models.
To prepare for the inevitable implementation of AI, businesses can take advantage of our free data assessment to understand the current state of their data, the opportunities for optimisation and the roadmap to being AI ready. Find out more about our free data assessment here.
Data fragmentation
To effectively scale AI in the manufacturing industry, data fragmentation must be minimised. Most manufacturers will need to update their data architecture, infrastructure, and processes to gain full benefits from AI, as well as other technological and business objectives.
It is crucial to prioritise a modernisation strategy that enhances interoperability between engineering and design and factory data systems, as well as between operational technology (OT) and informational technology (IT). Tools like Power Bi can help to pull together data from across multiple departments to give a clearer view of the business. Leadership teams can make more informed decisions based on the full picture rather than smaller fragments.
How We Can Help
As a recognised Microsoft Partner, we have a comprehensive understanding of the Microsoft ecosystem, enabling us to empower your organisation to maximise the potential of AI. As AI continues to grow in the market, our expertise will help you sustain growth and success,
We provide end-to-end support, facilitating your organisation’s seamless adoption of artificial intelligence. We guide you through the preparatory stages, ensuring your data architecture is optimised and your security frameworks are robust. This foundational work is critical for effective AI integration. Our proficiency guarantees a smooth deployment of AI functionality within your operational infrastructure. Moreover, we leverage the broader Microsoft ecosystem and the Power Platform to extend Copilot’s functionality, crafting bespoke solutions that align precisely with your unique business requirements. We can also help your team understand AI’s role in your specific business and how it can be used to build a roadmap.
Recognising that business needs will evolve, we tailor AI solutions to address the specific challenges inherent to your industry. This ensures you maximise the value of Copilot and other Microsoft AI resources. We can support you with the implementation of best practices, stringent security protocols, and effective governance, alongside cultural change management. We are dedicated to guiding your organisation through the intricacies of AI integration, delivering tangible and measurable return on investment.
Our status as a Microsoft Partner affords us access to ongoing research, development, deployment, and maintenance expertise in cutting-edge technologies, such as Agentic AI, placing us at the forefront of its practical application; all alongside our access to exclusive Microsoft funding opportunities.
Trusted Microsoft Solutions Partner
We bring unparalleled expertise to every AI implementation. With a team exceeding 450 professionals and a portfolio of over 1,600 clients, we possess the requisite knowledge and experience to guide your business through each phase of AI adoption. We specialise in the wholesale and manufacturing sector, providing tailored solutions that address the specific needs of these industries.
To commence your AI journey, we invite you to undertake our Copilot Readiness Assessment, ensuring your organisation is fully prepared for the AI revolution. Allow us to assist you in harnessing the transformative power of Copilot, enabling you to maintain a competitive advantage in an ever-evolving digital landscape.
