Enterprise AI vs Generative AI: They are the two sides of the same coin applied as foundational tools

Digital Transformation is the top priority in every sector and this continues to endure at a fast pace. Organizations that are more relied on manual operations are gradually changing their ways, adopting automated ones. This undeniable trend is the incorporation of Artificial Intelligence. Apparently, companies have approved AI and they are investing in it. More importantly, Enterprise AI and Generative AI have been the two sides of a coin. The argument  Enterprise AI Vs Generative AI brings up the question of what are the differences between them. A machine learning and artificial intelligence application for everyday business activities is referred to as Enterprise AI. While Generative AI leverages machine learning and artificial intelligence to make the machines synthesize the content available content in the web and make it to generate fake content like audio, video, text, and images. Enterprise AI benefits to society differ from Generative AI benefits.

Generally, AI incorporates other techniques to learn, synthesize, and conclude. Overall, AI processes should outperform human activities.

Enterprise AI Vs Generative AI: Techniques

As mentioned earlier Generative AI and Enterprise AI both work differently but the purpose serves the same i.e., simplification of human tasks. The techniques certainly used by both of these technologies are very much different. Techniques used by Generative AI are Generative Adversarial Networks (GAN), Transformers, and Variational auto-encoders. GAN uses two neural networks called discriminators and generators that mine contrary to each other to search for symmetry among the networks. Transformers in Generative AI are trained to educate about the image, audio, text, language, and also about the classification of data. The transformers including Wu-Dao, GPT-3, and LAMDA quantify differently based on the significance of input data.  The input data is processed into compressed code before the decoder gives the actual information from the input code. It all happens in variational auto-encoders.

While in Enterprise AI the techniques such as Heuristics, Natural Language Processing, Machine Learning, support vector machine, Markov Decision Process, and Artificial Neural Networks are used. One of the prominent techniques used in enterprise AI is Heuristics, a technique based on the trial-and-error method this technique would suit best for solving complex business problems in the enterprise. NLP is a technique known for voice assistants that have the ability to capture text, process it, and convert it into audio. This popular technique is widely used in Microsoft word to ease enterprise activities. The artificial neural network (ANN) technique works similarly to the natural neural network. This technique certainly assists enterprises to fetch complex patterns from the given dataset. Machine learning possesses to learn from prior experiences and is overtly programmed to perform certain tasks of an enterprise. Markov Decision process technique is basically on the basis of the decision-making process. The technique indicates what actions are to be taken by the machine in what instance, and at what time.    

Enterprise AI Vs Generative AI: Challenges

Although Generative AI is protuberant at the same time troublesome. Generative AI could be used to commit a crime by faking the genuine person. The mimicking of a genuine person may disrupt the workforce. A few mischievous people use this technology to imitate others. This could be the outcome of blackmail, revenge, ransom, and so on. Also, one of the biggest challenges is people are misusing rather than benefitting from this technology. Mostly people are using it to create fake stories, which creates trust issues on AI.

The adoption of Enterprise AI in the organization is not as easy as one thinks. Along with the adoption, challenges must also concern the budget, because the integration of enterprise AI is an expensive affair, though it comes with many perks. Considering this fact, many small-scale industries are worried to implement Enterprise AI.

Generative AI and Enterprise AI benefits

As mentioned previously, Generative AI assists in automating tasks rather than manual tasks. This helps the business to save effort, time, and money. It ideally improves the efficiency of the task. The major takeaway of this technology marketing companies can use it to make instant images accurately that are relative to the text and get the brand hype. With guaranteed efficiency, the technology also promises improved quality. The generated audio, video, images, and text will be appealing and of high quality.

Customer support can be mentioned as one projecting aid from Enterprise AI. Customer support could be the best thing to work on to drive sales. This can happen through Enterprise AI, which encourages for the implementation of virtual chatbots, customer behaviour monitoring, and customer-business interactions. Today's businesses get wealth generation from marketing. So, Enterprise AI revolves around working on marketing strategies that would be challenging otherwise with traditional techniques.