While manufacturers have embraced AI for automation and supply chain optimisation, its adoption in customer experience (CX) remains slow. Operating in B2B environments, many view CX as secondary to operational efficiency. However, with rising competition and evolving customer expectations, this mindset is shifting. AI-powered CX tools can enhance field service operations, vendor management, and demand forecasting, directly impacting efficiency and profitability. Yet, challenges like legacy system integration and skill gaps hinder adoption. In this interview with Efficient Manufacturing magazine, Maureen Chong, RVP Asia, Zendesk spoke about the barriers, opportunities, and the role of AI in transforming CX for manufacturers.
1. Why are manufacturers still slow in adopting AI for CX?
The manufacturing industry is no stranger to AI, with many already leveraging the technology for predictive maintenance, automation and supply chain optimisation. Often operating in a B2B environment, manufacturers have traditionally focused on field service operations, supply chain and vendor management. This can create a perception that investing in AI for CX is less critical.
However, as competition increases and customer expectations evolve, manufacturers are beginning to recognise that CX has a broader role to play beyond just customer support. Good CX has the power to improve field service operations, vendor management, quality control and supply chain management. Furthermore, leveraging AI for CX can directly impact their bottom line–whether that be by reducing the cost of service with intelligent bots, improving churn with intelligent insights that predict at-risk customers, or identifying cross-selling opportunities with intelligent agent copilots. In fact, nearly 80% of CX leaders in the manufacturing industry believe that only organisations that adopt AI at scale will survive the competitive pressures of the next few years, according to Zendesk’s CX Trends Report 2025.
Take Siemens as an example. Europe’s largest manufacturing company deploys AI agents to automatically respond to high-volume requests that previously required assistance from human agents. Their AI agents proactively send a copy of invoices to a customer and identify what else the customer is asking to automatically preempt some of those questions with appropriate responses. They also automatically populate tickets with data following a customer interaction, so it’s all captured when a human agent next opens the ticket. The integration into back-office systems such as document and contract management means that customer data can now easily be accessed and provided to a customer through the agent or AI. These benefits are helping further streamline the customer journey, as well as increasing efficiencies and reducing the workload of agents.
2. What challenges do manufacturers face in adopting intelligent CX tools?
One of the key challenges is integrating intelligent CX tools with legacy systems. The manufacturing industry is often characterised by complex, legacy systems that have been in place for many years. Manufacturers need to ensure that any new technology seamlessly integrates into their current workflows without disrupting operations, and may even require a complete redesign of those workflows. This calls for careful planning, investment and often a cultural shift within the organisation.
Another major challenge is the skills and knowledge gap within the workforce. A study by MIT Technology Review Insights highlighted the shortage of specialised skills and talent as the biggest challenge manufacturer’s face in scaling AI use cases. The lack of expertise can create uncertainty about how to effectively implement and utilise these tools to enhance CX. That’s where purpose-built AI-powered CX tools come into play. Intelligent CX solutions, like Zendesk, built on large, CX-specific datasets can be deployed quickly to deliver immediate value. Those with low-to-no code requirements reduce the need for heavy resource investments. Stanley Black & Decker implemented Zendesk three weeks before their massive Black Friday sales, and had their global support teams up and running across all channels after only a single day of training. This resulted in a 500% increase in regional sales year-on-year and a 300% increase in agent efficiency. Efficient workflows also allowed the team perfect adherence to its 1-hour first response time SLA.
Despite these challenges, the potential rewards of adopting intelligent CX tools are significant. Our 2025 CX Trends Report found that globally, manufacturing CX leaders who embrace AI in CX are 2.3 times more likely to report positive ROI than those who do not. As many as 75% of them already report a positive ROI from their AI tools in CX. When manufacturers successfully navigate these challenges, they can achieve significant benefits that enhance both customer satisfaction and business outcomes.
3. What is the role of AI-powered CX in tackling demand-supply issues in manufacturing?
AI-powered CX can play a critical role in addressing demand-supply issues in manufacturing. These tools can enhance forecasting, improve responsiveness, and optimise operations. Manufacturers gain real-time insights into customer needs and behaviours, helping them swiftly adapt to changes in demand and make informed decisions about resource allocation and production adjustments. Having real-time data enables manufacturers to respond proactively rather than reactively.
AI’s ability to analyse large amounts of data, such as historical customer data and market trends, allows manufacturers to forecast demand patterns more accurately. They can also better understand purchasing patterns and adjust their supply chains accordingly, minimising overproduction or shortages.
Intelligent CX tools, such as advanced chatbots and agent copilots, enable manufacturers to quickly respond to customer queries surrounding product availability, order status, or supply chain disruptions, improving KPIs like first contact resolutions and enhancing customer satisfaction.
Ultimately, AI-powered CX tools improve visibility and communication with a broad range of stakeholders from vendors and suppliers to customers, helping manufacturers keep them informed, better manage expectations, and adjust production in real-time. This reduces friction caused by supply-demand imbalances, resulting in an agile manufacturing process and a seamless customer experience.
4. How can manufacturers build better customer relationships with AI?
Customer trust is the foundation of lasting relationships, and this is built by consistently delivering high quality products, services and support. In practice, this can be done through effortless field service operations and robust quality control processes.
AI-powered CX tools can transform field service operations by enabling manufacturers to optimise scheduling, resource allocation, and real-time communication. With AI, manufacturers can analyse vast amounts of data to predict service needs and proactively schedule maintenance. This predictive maintenance not only minimises downtime for customers, but also ensures that service technicians arrive equipped with the right tools and parts, improving efficiency and reducing time spent on-site. Technicians can also make use of these AI-powered tools to access customer histories, product details and troubleshooting guides on the go, allowing them to provide personalised service that addresses specific customer concerns, resulting in improved satisfaction and trust.
Taking it one step further, when AI is deployed in self-service tools like chatbots and help centres, manufacturers can provide around-the-clock assistance to help customers find answers faster. Generative AI can turn the most frequently used product documents into help centre articles, empowering customers to search and troubleshoot on their own. Offering faster, more accurate resolutions builds trust over time.
AI also plays a critical role in quality control processes. Manufacturers can analyse production data in real-time to identify early signs of quality issues. This proactive approach enables manufacturers to address potential defects before they reach the customer, thus improving product reliability and customer satisfaction. This also applies to its customer interactions. AI-driven quality assurance allows manufacturers to gather insights and feedback from all customer interactions to identify recurring issues and service quality lapses to make informed decisions about improvements needed. This demonstrates to customers that their feedback is valued and taken seriously.
By optimising processes, proactively addressing issues and enabling real-time, accurate support, manufacturers can leverage AI to build better customer relationships that ultimately achieve greater loyalty and business success.
5. What is the role of CX in vendor management? How can manufacturers leverage this to their benefit?
Manufacturers often operate in complex global supply chains, where vendors play an important role in maintaining operational efficiency, cost control, and supply chain stability. Vendors directly impact production processes, quality and, ultimately, customer satisfaction, making vendor management a strategic priority.
A strong CX approach ensures smooth communication and issue resolution between manufacturers and their vendors, fostering greater transparency while reducing friction. AI-powered CX tools can streamline vendor interactions, automate workflows and execute business procedures independently, freeing up human agents to handle higher-value, complex tasks that require a level of critical thinking and judgment that only a human can provide. Additionally, AI-driven analytics can also help track vendor performance, monitor service level agreements, and identify potential risks before they impact production.
By applying the same CX principles used for customers—responsiveness, consistency, and proactive support—manufacturers can improve supply chain performance to drive better business outcomes.
