What Generative AI Is and What It Isn’t … Hint, It’s Not AGI

Artificial intelligence (AI) transformed our lives and businesses by streamlining tasks and helping bring more natural and personalized conversations between business and customer. However, AI has a narrow scope of function and is designed for very specific tasks. It completes them exceedingly well—but can only operate within the parameters set.

Artificial general intelligence (AGI) is the pie in the sky pinnacle of AI advancement. AGI, if it had been achieved, would provide more extensive operations, learning, and adaptability. When AGI is presented with an unfamiliar task, it will find a solution. AGI can learn and adapt and possesses autonomous self-control—the ultimate artificial intelligence. So far, no true AGI systems exist. The machines aren’t rising. Yet.

Generative AI’s capabilities sit somewhere in between AI and AGI. Generative AI can create and innovate based on patterns it knows, but doesn’t have quite the level of sophistication of AGI, and isn’t as limited as traditional AI. Generative AI technologies, such as natural language understanding (NLU) with large language models (LLMs), can understand human languages and are great at creating new texts, answering questions, and even appear to think a little like a human.

However, there’s a lot of back-end manual input needed to create the scenarios and ensure fake information isn’t encountered. Generative AI is also really good at creating data—or fake information. Sometimes you hear this referred to as “hallucinates.” Boundaries and parameters need to be set to prevent your generative AI system from giving false information.

These rigors set processes needed to ensure the data used is relevant to your needs and that the system is only accessing the data knowledge required for your purpose. For example, if you’re an auto insurance company, you don’t need your generative AI bot accessing information from the Museum of Natural History. Establishing processes to control the data is essential when deploying generative AI technology.

Many people are concerned that generative AI is going to replace people. That’s a limited view of generative AI and its possibilities. Empowering people is better perspective. Utilizing generative AI with governance and thoughtfulness provides a foundation to transform your business by positively impacting the customer journey and providing advisors with the tools needed to respond quickly to customers’ ever-expanding expectations.

Focus On What’s Important

You may be asking yourself, how do I determine where to implement generative AI, and how do I make sure it’s impacting my business the way I want?

First, you need to determine what your goal is. You may say, “I want to make my customers happy.” Ok, but what business processes will impact that the most? Is it average call handle time? Deflection from voice to digital interactions? Or something else entirely? Determining what processes need to change, where gaps lie, and what will make the biggest impact is essential.

Utilizing a customer journey map is a great way to lay out the exact journey a customer takes when they contact your company. This will help bring to light where roadblocks are happening and where processes are falling short.

Once you’ve identified your customer journey and determined your specific goals, start looking at tasks within those processes that can be automated or enhanced with generative AI. Tasks that are repetitive, error prone, or time-intensive are prime targets: healthcare bill coding, quality and testing reports, procedure documents, software development documentation and unit testing, to name a few.

Avoid the Pitfalls

It’s easy to get carried away when looking for tasks to improve with generative AI that can help transform your business. Generative AI is not a magic wand. You want to avoid activities that require a judgment call, such as complex customer issues that can’t be solved with a menu of options, or determining the best development strategy for your project based on current resources and priorities. These are activities that require a human to take in information and decide. Generative AI doesn’t have the same creativity capabilities as a human. It’s driven by a data source, and as a result, generative AI can’t draw conclusions or make decisions for complex situations.

Limited scope tasks are also problematic. Generative AI is dependent on large data sources. When the data is limited, flawed, or compromised in any way, the output will reflect these problems.

You Need a Partner

Navigating the waters of generative AI and how to best implement it quickly, advancing technology across your organization, can be complicated. Leaning on a technology partner who understands process, data, and technology and how these affect various aspects of your business will help you achieve your expected results. Trying to go it alone may seem possible, but without the expertise of a partner who understands how to evaluate your current state against your primary goals, you could end up with a solution that’s not optimized and falls short of your finish line. Would you try to build an Iron Man suit by yourself? Or would you ask Tony Stark for some help?

Concentrix has the experience, knowledge, and proven models to walk you through the process step by step. We identify the areas that will be most meaningful to your business, advise on the technology that will help you meet your goals, build your specific solution, and run the solution so you can continue to focus on running your business. Learn more about the generative AI advancements Concentrix is making, and how we can partner to help you transform your business.