AI/ML 2021- By now, most organizations have experimented with implementing a machine learning (ML) solution or playing with prototypes of artificial intelligence (AI) algorithms. While the use cases of AI/ML have been exponentially increasing, many organizations — including commercial, nonprofit and government agencies — have not factored AI/ML into their business strategy.
AI/ML applications bring about the convergence of analytics, data science and automation that accelerate successful digital transformations and fuel business outcomes. This has also led to indirect benefits like improving customer or citizen services and boosting top-line growth. According to McKinsey, “AI could potentially deliver an additional economic output of around $13 trillion by 2030, boosting global GDP by about 1.2% a year.”
Every organization is challenged to remain competitive in the market, increasing revenue and reducing operating costs. AI is the single most powerful tool that organizations are using to make informed decisions, drive new lines of revenue, attract new customers and optimize costs of business operations.
As you look forward to your organization’s goals for 2021, implementing AI/ML systems might be something to consider. They provide the following benefits not just for this year but in the future as well:
1. Increase organizational performance.
In the context of AI increasing organizational performance, a question to consider is, “How is AI automating a manual process or improving interdepartmental processes?” There are several use cases of AI-related technologies — such as ML, deep learning and natural language processing (NLP) — that could be used to produce reliable, relevant, dynamic and intelligent information that can help with decision making. One example is the use of NLP-based chatbots in customer service that can be used to answer most questions by a customer and, in case of a complex query, can seamlessly pass it on to a human representative. They also offer backend integrations with APIs with their case management or ERP systems.
2. Reduce operational costs.
As companies work toward regaining their foothold in a post-pandemic world, one of the key focus areas would be to reduce operating costs. In general, the increased adoption of AI can be attributed to automating manual or statistics-driven tasks that save time on repetitive tasks and increases focus on high-value jobs. Use cases of machine learning that most commonly led to cost decreases are optimization of inventory or pricing, contact-center automation and claims processing.