How Traditional Enterprises Can Supercharge Legacy Products And Operations With AI And Wide Data
– Anand Mahurkar, for Forbes Technology Council
Many traditional enterprises are looking to artificial intelligence (AI) to help drive digital transformation. That might mean supercharging a company’s own software or hardware products with AI capabilities that are being sold to their customer base and/or transforming their internal business processes. “Traditional” generally refers to organizations in
industries like manufacturing and retail that are operating with legacy technology solutions.
‘AI-ifying’ Legacy Hardware Or Software Products
Many times, traditional enterprises have not updated their technologies or infrastructure with AI. Many businesses are eager to add an edge to their software solutions like ERP or even hardware products like medical devices or scanners in hopes of invigorating sales and offering additional features to their loyal customers. These businesses are searching for an AI edge without having to go through the process of redeveloping products or enhancing features through timely and costly development processes.
The good news is that AI technologies such as computer vision (CV), machine learning (ML) and natural language processing (NLP) can be embedded into legacy software and hardware products to provide new features or even additional revenue opportunities. These can be “white- label products” that package together AI capabilities with an enterprise’s existing solutions, enabling the product to become smarter and more efficient. That means hardware products can literally be enhanced by offering features like a chatbot, content summarization or predictive analytics. To illustrate, adding NLP capabilities to a conventional scanner makes it “smarter,” as NLP customizes existing hardware to scan hundreds of pages with relevant summaries.
Using AI To Transform Operations
AI can also be used to modernize operations such as CRM or ERP solutions by embedding these with the ability to forecast sales, streamline inventory and add predictive maintenance properties to machinery. This can provide benefits such as adding more in-depth insights, leading indicators and recommendations.