AI Is the New Era of Sourcing

The buzz surrounding artificial intelligence (AI) in the supply chain isn't mere noise; it's evolving into a substantial dialogue—one that could spell the difference between triumph and defeat. AI is taking center stage, and companies are grappling with how to harness its power to enhance supply chain efficiency. To resist would be foolhardy.

The global artificial intelligence market is anticipated to experience significant expansion, according to projections from the market research community. A recent report by Industry Research Biz forecasts that revenues from AI in the supply chain and logistics sector will surge to $3.37 billion by 2029, compared to $1.71 billion in 2022. The research firm predicts an average annual growth rate of over ten percent. This growth is attributed to the diverse ways AI can aid supply chain and logistics professionals in tackling intricate challenges, automating tasks, optimizing decisions, improving performance and generating value. AI applications span various aspects of supply chain and logistics, including demand forecasting, inventory planning and management, production planning, predictive forecasting, supply network design, transportation routing, warehouse management, order fulfillment, customer service and risk management.

Recent research from Gartner highlights the correlation between AI adoption and supply chain performance. High-performing supply chains are leveraging AI at double the rate of their lower-performing counterparts. From demand forecasting to sales planning, AI adoption promises enhanced business performance. Notably, the greatest disparity between high and low performers lies in utilizing AI and machine learning for order management and fulfillment. (See chart below.)

AI is optimizing supply chain management, predictive maintenance and risk assessment, leading to cost savings and enhanced operational resilience. By automating repetitive tasks and augmenting human capabilities, AI enables employees to focus on high-value activities that drive innovation and competitive advantage. Moreover, AI-powered algorithms efficiently extract valuable insights from data, facilitating data-driven decisions with greater accuracy and agility.

Transitioning from conceptualizing an AI-driven supply chain to its implementation poses a multifaceted challenge. This involves familiarizing oneself with new technologies such as Large Language Models like ChatGPT, Bard and Llama and innovative tools like CoPilot, Dali and Gemini. Furthermore, organizations must reconsider workflows and provide employee training to effectively capitalize on these technologies. Recognizing that the intelligence of artificial intelligence depends on the quality of data provided by the organization, it's crucial to invest time and effort into ensuring that business intelligence inputs are maximally useful and clean.

Most importantly, AI holds the potential to revolutionize supply chain relationships. By harnessing AI, organizations can capture and analyze customer satisfaction data specific to the supply chain, enabling more effective and efficient responses to customer needs. AI offers a wealth of insights that enable organizations to gain a deeper market understanding and better serve their customers. By merging internal and publicly available data, AI expedites access to accurate information, promising a significant paradigm shift.

 Without AI, supplier sales inboxes become inundated with a deluge of inquiries, lacking distinction between automated junk and genuine, high-value customer requests. Through the deployment of chatbots, AI assistants and predictive analytics tools businesses can offer tailored experiences and nurture customer loyalty and satisfaction. AI also holds the capability to free up skilled sales teams to collaborate with customers and focus on proactively closing new business.

This approach not only benefits sales personnel by allowing them to concentrate on converting inquiries into business but also facilitates the efficient identification and prioritization of customer needs. Less complex queries can be redirected to junior sales associates or AI systems, ensuring prompt customer support. Most importantly, this strategy ensures that potential customers do not get lost in the shuffle and feel valued for their business requirements, thus mitigating discontent and burnout. The elimination of dissatisfied customers is invaluable for all stakeholders involved.

 Sales organizations operating within the global electronics supply chain must embrace artificial intelligence to enhance customer experience effectively. Merely experimenting with AI will not suffice; wholehearted adoption is essential to enable customers to fully leverage its benefits.

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