Written by Laura Mediorreal, Spring '24 intern

Looking ahead, the $3.17 trillion manufacturing industry is poised to leverage AI to rejuvenate its enterprise solutions enhancing a much-needed increase in efficiency and productivity.  

Today, we see there is value in vertical AI software specializing in unsexy businesses that can revolutionize ways people think about work in industries like manufacturing and procurement. 

By using AI as the key to unlock the slow-moving labyrinth of workflows, outdated technology will be replaced by unified systems streamlining information discovery for suppliers, line managers and business stakeholders.  

There are plenty of skeptics who do not believe manufacturers will adopt AI, influenced by risk aversion and a complex organizational infrastructure. Some startups may encounter difficulties with established companies withholding data and distribution solutions. However, the best startups will offer platforms vastly superior to outdated but still utilized 90s (or older) solutions, prompting manufacturers to embrace the value proposition without hesitation.  

Here is the next wave of AI-first opportunities to support manufacturing industries and a few ways founders can leverage hidden gems underlying slow moving processes.  

These are the largest opportunities for founders to build AI first vertical solutions for manufacturers: 

AI-first Enterprise Resource Planning Systems (ERP) 

Warehouse Management 

Procurement Optimization 

Predictive Quality Control and Maintenance 

AI First Enterprise Resource Planning Systems (ERP) 

Generalized horizontal solutions are insufficient because they can't address the specific needs of manufacturers, whereas AI tailored vertical solutions can offer faster customization. Legacy one-size-fits-all ERP systems dominated the last wave of digitization, creating billions of dollars in market cap and forming a growing global market valued at $71.4 billion. These systems were assumed to be powerhouses and the edge of technology. But now, AI can challenge the assumptions that Oracle ($346 billion), IBM ($172 billion), and SAP ($249.2 billion) can move quickly to support the needs of so many specialized industries. AI will impact a range of ERP one size models where incumbents will be slow to move, and entire categories within ERP such as financial, human capital, and customer management will be up for grabs. 

Currently, core ERP solution models can help top corporate systems, but subsidiaries need back-office improvement and operations. These down-funnel subsidiaries with heavy operation needs must streamline their processes and optimize reporting on efficiency and cost saving solutions to corporate. By integrating AI driven reporting on payments, energy, factory maintenance, and packaging efficiency, subsidiaries can communicate with top management on hidden costs. Then, corporations can leverage AI recommendations around quality costs and tighter project schedules to reduce budgets across its subsidiaries with real time information. 

For founders, considering specialized ERP solutions that can generate unique insights from lengthy burdensome data is essential. Examples: Automating payment legacy contracts and purchase orders with suppliers, procurers and customers. These future systems will connect data from multiple sectors within the supply chain in manufacturing, opening hidden pots of gold in cost savings while replacing outdated systems.  

Warehouse Management 

There is a significant need for optimizing inventory and supply chain systems, which AI can address by providing real-time demand forecasting and profitability insights. The need to transform growing data loads, previously left untouched by manufacturers, into valuable information creates an opportunity to develop new management systems for goods optimization. For many manufacturing use cases, the only feature that matters is inventory optimization to save costs, which allows new systems which have less features to capture market share. Additionally, AI-powered systems that enhance warehouse efficiency in storage, sorting, and order fulfillment processes are highly valued. These solutions can reduce errors and save costs for manufacturers with tight budgets. 

Manufacturing Assets and Supply Chain

Source: https://www.nist.gov/el/applied-economics-office/manufacturing/manufacturing-economy/total-us-manufacturing

For founders, opportunities in inventory management, storage, fulfillment and profitability of goods are of high value. Example: Creating a manufacturing inventory insights tool that leverages historical data with current market trends and predicts future demand and profitability accurately. Larger incumbents' competing offerings are at a different scope which leaves room for new incumbents to adapt quickly to tailored solutions.   

Procurement Optimization 

One of the most interesting new opportunities with AI is going after streamlining procurement processes since all goods are impacted by this part of the supply chain. Most of the trivial work involved aggregating sources of new products, materials and inventory which often is done through emails chains and lengthy excel sheets. These tasks can leverage algorithms to enhance efficiency and cost-effectiveness in the supply chain, improving decision-making and reducing reliance on manual processes. 

For founders, aggregating communication chains is a must.  If AI-based algorithms could combine information of timeline to procure specific materials, the current inventory stock, and the company’s historical usage rates of this material— all trained on one platform – a manufacturing manager could send specific replacement requests to suppliers and procurers immediately with one click. In the end, manufacturers are always better off interacting with 1000 suppliers and procurers instead of 10 based on real-time data.  

Predictive Quality Control and Maintenance 

Maintenance and quality control are at a forefront necessity for any manufacturer. Solutions to monitor equipment health, predict potential failures, and proactively schedule maintenance activities for machinery can optimize costs by decreasing machine downtime and increasing productivity.  

For founders, ensuring superior product quality calls for predictive solutions to enable real-time monitoring and analysis of production data, allowing manufacturers to detect and address quality issues right away. This proactive approach can improve product consistency and increase customer satisfaction. 

Conclusion 

Manufacturing does have a lot of untapped potential in the midst of archaic systems and industry hesitation. Undoubtedly, there will be skeptics who believe manufacturing companies will not move from outdated systems. But founders who see vertical AI as the driving force behind modernizing burdensome solutions will create value in new markets and old ones that never existed historically.  

Manufacturing is a key component of the global economy and AI is a key generational movement that can be leveraged to move this industry to a faster innovator. Founders can unlock gaps in the current services based on modernizing specific ERP solutions, developing products that optimize warehouses, relationships with procurers, and quality control specialists. If you are a founder interested in building within this space, reach out on LinkedIn (laura-mediorreal) or the Cowboy team (Jillian@cowboy.vc). 

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