{"id":9698,"date":"2021-08-26T10:07:44","date_gmt":"2021-08-26T17:07:44","guid":{"rendered":"https:\/\/www.qad.com\/blog\/?p=9698"},"modified":"2025-04-16T11:49:29","modified_gmt":"2025-04-16T18:49:29","slug":"uncovering-the-promise-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.qad.com\/blog\/2021\/08\/uncovering-the-promise-of-artificial-intelligence","title":{"rendered":"Uncovering the Promise of Artificial Intelligence"},"content":{"rendered":"

[vc_row][vc_column][vc_single_image image=”9699″ img_size=”full”][vc_column_text]Because manufacturers are constantly pressured to increase productivity, deliver quality products, delight customers and achieve greater profitability and sustainability, they are turning to new technologies such as artificial intelligence. To remain competitive, the time for such digital transformation is now.<\/span><\/p>\n

However, barriers continue to exist and technology is not always being used to its full potential, as we learn in a <\/span>recent article<\/span><\/a>, <\/span>\u201cHow to Outsmart AI Business Challenges\u201d in <\/span>SCM Now Magazine<\/span><\/i> from the Association for Supply Chain Management.<\/span><\/p>\n

About Artificial Intelligence<\/span><\/h2>\n

In his <\/span>white paper<\/span><\/a>, \u201c<\/span>No Matter What You Call It: Industry 4.0 Means Manufacturing in Transition\u201d, <\/span>QAD\u2019s Glenn Graney, director for the Industrial and High Tech markets, <\/span>reflects on artificial intelligence:<\/span><\/p>\n

\u201cArtificial Intelligence (AI) is already transitioning from an academic exercise to an impactful business proposition. The practical adoption of AI through machine learning results directly from enhanced connectivity, smarter sensors, advanced analytics and super scalable systems.\u201d<\/i><\/b><\/p>\n

While we don\u2019t think that<\/span> AI is a dirty word<\/span><\/a>, we know that not all manufacturers have discovered the solutions promised by AI. Companies need to build the proper foundation to enjoy the explosive growth of AI, machine learning and similar technologies. Among other things, it takes best practices, simplified IT architecture, well trained teams and a proper IT investment \u2013 in other words, money, patience, planning and force of will.<\/span><\/p>\n

Barriers (and Solutions) to Implementing Artificial Intelligence<\/span><\/h2>\n

No technology advancement occurs unscathed. Manufacturers face four main challenges from achieving the promise of artificial intelligence. Below are some potential solutions:<\/span><\/p>\n

Fear of Missing Out (FOMO)<\/span><\/h3>\n

To avoid the dreaded FOMO, rather than <\/span>rushing to act on the hype surrounding AI, manufacturers need to start projects with a clear strategy. As in all things, a well-designed plan is critical and should start with building a portfolio of use cases that demonstrate the technology\u2019s value, identifying deliverables with deadlines. The plan should include route optimization, sales forecasting, product categorization, safety stock calculation, <\/span>supplier management<\/span><\/a> and warehouse management. It\u2019s critical to clearly outline the value proposition and KPIs to be measured along with goals and objectives. Estimate ROI based on project-related costs.<\/span><\/p>\n

Deployment Difficulty<\/span><\/h3>\n

Deployment is eased when manufacturers choose packaged applications from among the following three types, and it\u2019s important to build in change management plans for better user adoption.<\/span><\/p>\n