Over the past year, Ecosystm has conducted extensive research, including surveys and in-depth conversations with industry leaders, to uncover the most pressing topics and trends. And unsurprisingly, AI emerged as the dominant theme. Here are some insights from our research on the Manufacturing industry.
Click here to download “AI in Manufacturing: Success Stories & Insights” as a PDF
AI is revolutionising production lines, supply chains, and product development in the manufacturing sector. Yet, many manufacturers find themselves stuck between ambition and execution. Those who bridge this gap will gain a competitive edge, driving innovation and leading the industry forward.
Despite the challenges, Manufacturing organisations are witnessing early AI success in these 3 areas:
- 1. Quality Control & Assurance
- 2. Supply Chain Management & Optimisation
- 3. Process Automation & Efficiency
Quality Control & Assurance
- Defect Detection. Identifying defects in products and improving quality
- Product Inspection. Implementing AI-powered vision systems to inspect products and ensure they meet quality standards
- Data Analysis. Analysing operational data and customer feedback to identify operations and product issues
“AI is the future of design. It streamlines the design process, leading to faster time-to-market and superior products.” – OPERATIONS LEADER
Supply Chain Management & Optimisation
- Inventory Management. Optimising inventory levels and reducing costs
- Supply Chain Visibility. Gaining real-time visibility into supply chain operations
- Demand Forecasting. Predicting demand for products to improve production planning and inventory management
“By leveraging AI, we’re not just optimising our supply chain; we’re pioneering sustainable practices to reduce our carbon footprint.” – CIO
Process Automation and Efficiency
- Process Optimisation. Identifying areas for improvement and potential operational bottlenecks
- Predictive Maintenance. Predicting equipment failures and preventing downtime
- Customer Feedback Analysis. Analysing customer feedback to improve design processes, products, and services
“Our goal is to build intelligent manufacturing plants. By proactively monitoring equipment health, we minimise downtime and maximise productivity – we have set a new internal standard for operational efficiency in the last two years.” – HEAD OF PRODUCTION
Over the past year, Ecosystm has conducted extensive research, including surveys and in-depth conversations with industry leaders, to uncover the most pressing topics and trends. And unsurprisingly, AI emerged as the dominant theme.
Here are some insights from our research.
Click here to download ‘AI in BFSI: Success Stories & Insights’ as a PDF
From personalised recommendations to streamlined operations, AI is transforming the products, services and processes in the BFSI industries. While leaders realise that AI holds significant potential, turning that potential into reality is often tough. Many BFSI organisations struggle to move beyond AI pilots because of some key barriers.
Despite the challenges, BFSI organisations are witnessing early AI success in these 3 areas:
- 1. Customer Service & Engagement
- 2. Risk Management & Fraud Detection
- 3. Process Automation & Efficiency
Customer Service & Engagement Use Cases
- Virtual Assistants and Chatbots. Delivering real-time product information and customer support
- Customer Experience Analysis. Analysing data to uncover trends and improve user experiences
- Personalised Recommendations. Providing tailored financial products based on user behaviour and preferences
“While we remain cautious about customer-facing applications, many of our AI use cases provide valuable customer insights to our employees. Human-in-the-loop is still a critical consideration.” – INSURANCE CX LEADER
Risk Management & Fraud Detection Use Cases
- Enhanced Credit Scoring. Improved assessment of creditworthiness and risks
- Advanced Fraud Detection. Easier detection and prevention of fraudulent activities
- Comprehensive Risk Strategy. Assessment of risk factors to develop effective strategies
“We deployed enterprise-grade AI models that are making a significant impact in specialised areas like credit decisioning and risk modelling.” – BANKING DATA LEADER
Process Automation and Efficiency
- Backend Process Streamlining. Automating workflows and processes to boost efficiency
- Loan & Claims Processing. Speeding up application and approval processes
- Invoice Processing. Automating invoice management to minimise errors
“Our focus is on creating a mindset where employees see AI as a tool that can augment their capabilities rather than replace them.” – BANKING COO
