Three ways AI-ifying your organization can reap tremendous results – by Anand Mahurkar

AI offers a host of possibilities, and successful execution can lead traditional enterprises into a new era of digital transformation.

Data has been both a friend and foe for enterprises since the early 2000s. Most executives understand the power of data, but the sheer vastness of an organization’s data stores—which can easily reach the petabyte level—contributes to a general state of information overload. As such, traditional enterprises are struggling, and commonplace IT terms like “data lakes” and “data warehouses” are now jokingly referred to as “data dumping grounds.”

The challenge today is how to invigorate these “data dumping grounds” into intuitive recommendations and predictions. This is where an artificial intelligence (AI) strategy comes in,
offering a way to collect and unify relevant information so that it becomes actionable and insightful.

For example, AI can galvanize an organization’s supply chain management analytics. Once a company embarks on an AI journey, it will have to commence a wide data strategy. This includes collecting and unifying data from the internal ERP and CRM systems, along with data from external sources such as news and social feeds. Once all the data is collected and processed, it can provide the company with insightful predictions about the cost of raw materials, help the organization automate resource planning, and even suggest optimal inventory based on demand forecasts.

Let’s look at three specific ways AI can propel a company into a true digital transformation.

1. AI REDUCES COST

The most visible evidence of cost-reduction observed from “AI-ifying” systems is in operations and customer support. In the United States, customer service call centers charge $26-$30 per hour—and more for specialists. In-person customer service can cost anywhere from 8 to 12 times this amount. But AI can help reduce these costs in multiple ways.

First, AI can power a call center system to detect early anomalies and patterns that may reside with—for example—product defects that can lead to issues, and either prevent problems before they occur or alert the consumer and company in advance.

Secondly, conversational computing—perhaps better known as interactive chatbots—can help save time and money when organizations enable them to address customers’ most common questions quickly. Meanwhile, other customer service representatives can spend more time and energy answering customers’ more complex inquiries. In either case, customer satisfaction and retention are improved, and the company is able to save up to five times the amount it takes to acquire a new client.

Finally, once an issue is detected, the AI can rapidly check system inputs and outputs to determine the cause. Analytics offering predictions and recommendations can then be provided to the organization via its ERP systems, or even spreadsheets.

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