“AI is almost free.” I hear this a lot when people promote the exciting aspects of AI.

Artificial intelligence is not free; it’s actually quite costly. That fact remains the same whether you run your AI systems on-premises or on a public cloud. The vast amount of storage and computing power required doesn’t vary if you leverage that stuff as a cloud service or through purchased hardware; the price tag will be high either way.

To enter the world of artificial intelligence, a hefty initial investment is required before the higher operational costs even come into play. The initial phase involves setting up training data feeds, acquiring appropriate data, model storage (cloud and not cloud), and high-end computing systems to border high-performance computing (HPC) platforms.

Enterprises won’t typically have this type of infrastructure on hand and will need to rent it as a utility from a public cloud provider or purchase a lot of hardware and data center space. Of course, this also comes with the expense of keeping expertise around these systems to deal with the endless array of updates and technology refreshes.

So, is AI worth the investment right now? How about in the future? Let’s look at some reasons to invest in AI and reasons to delay a decision.

Improved Efficiency and Productivity

One of the primary advantages of AI is its ability to enhance efficiency and productivity. AI- automation can streamline repetitive and time-consuming tasks. This frees up humans to focus on higher-value and more creative activities.

This could be customer support automation with NLP-enabled chatbots that optimize supply chain logistics or an AI system that analyzes vast amounts of insurance data for actionable insights. The result is that AI can reduce operational costs while improving efficiency…if applied correctly.

The downside of looking for the value of efficiency and productivity is that it often leads to an over-application of AI, such as generative AI. It becomes a part of the applications deployed to support the business but needs a valid reason for its presence. We’ve figured out how to do it, but why are we doing it? Companies must take time to create metrics that prove value.

Enhanced Customer Experience

AI can play a pivotal role in providing a better customer experience. By leveraging AI, companies can gain a better understanding of their customers. This includes anticipating their needs and personalizing interactions. But we’ve all had good and bad automated customer service experiences, be it IVR systems that send us into an endless loop of prompts…bad. Or an app that saves us time by anticipating what coffee we will order…good.

Natural language processing based on AI and sentiment analysis enables AI-enabled systems to analyze customer input (passive or active) and provides tailored responses to enhance customer satisfaction and loyalty. AI-powered recommendation systems, like most e-commerce Web sites, also help businesses offer personalized product suggestions that drive sales and increase customer engagement. Often, without the customer filling in a profile, working only with the interaction pattern.

Justifying the Investment in AI

Back to justifying any investment in AI on-premises and within public cloud providers. Here are a few core metrics that need to be understood:

How you define value is critical to the investment justification of AI

This is different for all enterprises. Some greatly value agility, others value customer satisfaction more, and others value innovation above everything else. What’s important here is to define the enterprise’s value drivers before looking at what AI can do to enhance them.

Enterprises must focus on what contributes to business value in terms of using AI or the degree to which we want to leverage this technology in net-new or existing systems. Value weight is rarely considered in AI decisions, and enterprises often end up with investments that bring little value back to the business or, more often these days, negative value.

Have a realistic understanding of what AI costs

AI isn’t free. AI increases the cost of development by 50 percent on average. This includes most AI system augmentations, the addition of AI into existing business systems, or building net-new systems using AI.

AI systems operations’ costs typically double when considering the specialized skills and tools required. Again, we can justify these additional expenses if the value objectives are met. But too often, they become a cool-sounding system that actually removes value from the enterprise.

Look into the future to predict how AI values will change over time

It’s perfectly justifiable to make an investment that won’t return value in the first few years but will provide other discounts later. A case in point is an investment in innovations, such as AI-enabled supply chains that typically return value after their 3rd year of operation. The trick is to be farsighted enough to understand this technology’s potential over time, which means predicting the future of markets and customer personas.

REFERENCE:Is AI Worth the Investment? | eWEEK

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