Artificial Intelligence has dominated every corner of human life. Artificial Intelligence is the key to success for every enterprise today. In today’s dynamic era of Artificial Intelligence, every enterprise is keen to reap the enormous benefits of Artificial Intelligence. They anticipate more effective, accurate operations and revenue management by use of Enterprise AI.
The advantages of using AI as the primary tool have become a need of the hour for every enterprise. A complete transformation is feasible with this trending technology.
As a leading software development company in the California, serving many Fortune 500 companies and businesses, we offer our quality services in Enterprise AI.
Let us have a look at the complete know-how of this type of AI with genuine use cases. We will get familiar with the base to the top edge of this technology.
With AI, Enterprises can get smart answers to many out-of-the-box questions useful for their processes and outcomes. AI brings in effective and data-driven decision-making for every enterprise resulting in a great deal of time-saving and resource management. This enhances the overall efficiency and profit margins of the enterprise. Human error becomes history by the use of such advanced technology and platforms for the enterprise.
What is Enterprise AI?
It is nothing but a perfect mix of a machine and tailored software. It can behave, understand, and interact just like a human mind with software designed as per the enterprise's needs.
For example, whenever you visit an online shopping or buying website, a customer support chatbot starts to chat with you. It is designed or developed for dedicated customer support and guidance, to make them easy and comfortable for their buying journey. It caters to vital information, the customer always seeks. These chatbots are real-time examples of customer relationship management.
USA’s share on AI market
As per the latest statistical data, 35% of companies are currently taking benefits from AI and 42% of companies are planning to explore AI implementation. The USA is leading the AI market to date. The global enterprise artificial intelligence (AI) market size has been recorded around USD 7.02 billion in 2022 and the expected reach is around USD 270.06 billion by 2032.
Now, let us elaborate on the difference between Regular AI and Enterprise AI.
The difference between Regular AI and Enterprise AI lies in its intent for use. Enterprise AI solutions emphasize high-value, specific user cases on a larger scale. Enterprises consume a high amount of data for this. Enterprise AI capabilities are more than Regular AI with the size and type of data it processes. It integrates with the existing systems and tools. It not only serves answers but also automates many processes and designs solutions.
In today’s highly competitive and demanding business environment across the globe, enterprises face challenges in the implementation of the Enterprise AI platform. Some realistic challenges in the implementation project are always there as the other side of the coin.
Some of the challenges are here for our better understanding.
Primary Challenges While Adopting Enterprise AI Platform
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- Resources Management: Every enterprise going for an AI project for their business, must hire an in-house expert team or outsource an expert AI technology solution Partner. It is essential for the installation, daily monitoring, and further servicing and maintenance of the same. The knowledge and reliability of the AI experts is the vital factor.
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- Compatibility: The actual issue that arises while implementing or adopting the AI project in the enterprise is mismatching with the existing systems and tools. If the enterprise system is not smart enough for AI use, then the design of a suitable ecosystem or system environment becomes the major challenge for the success of the project.
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- Industry-centric regulations: In the case of the type of industry, sometimes regulations related to the processes become a hurdle for implementing AI. For example, in a financial company, data handling policies and rules are user role-based. These kinds of regulations create limitations for the advanced tools and technologies implementation and usage.
For a deep understanding of enterprise AI capabilities as a technological platform, we will mention some exclusive use cases.
Banking Industry –
Fraud Detection Use case: This is the most conventional use case we use in the Banking Industry. Today, all banking transactions happen worldwide in large numbers with respective bank Credit and Debit cards. The transaction data includes the last 4 digits of the card number, the amount of the transaction, the name of the cardholder, etc.
In the enterprise AI platform, the machine learning algorithm is made with the detailed study of particular data sets and data patterns. Many data instances for fraud transactions are added within the data model with properly trained data. It is studied and analyzed within the data science structure. Whenever a fraud happens, the anomaly-based algorithm of this system raises an alarm and notifies of fraud on the card transaction.
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E-Commerce Industry –
Today, E-Commerce is the fastest-growing industry for online purchases of consumer goods and services, also. Predictive analysis-based machine learning algorithms are used in this industry.
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- Product recommendation on purchase history: The predictive algorithm studies and suggests similar purchases for some particular product or category to the buyer. This is based on the analysis of the buyer’s earlier buying search history or search behavior. Also, the similar buyer’s history is used for the prediction or suggestion of a similar product or service category.
- Shipping models: Predictive Analysis helps in identifying the expected shipping mode for the purchaser by studying earlier purchases/ purchaser’s purchase history. It also gives product stock data by studying the purchaser’s data or patterns to make sure the particular item is available in the nearby warehouses for deliveries.,
- Pricing: The Ecommerce Industry applies AI for price optimization by applying discounts on fast-moving trending items, and products and earning good margins on less-moving products, and items.
Energy Industry –
Anomaly detection is very useful in the Energy System. It is the process of identifying offbeat data patterns from the regular or expected system behavior. Anomaly detection gives earlier detection alerts for peculiar situations such as malfunction of various energy equipment, unusual energy demands, fault detection on the grid, and grid failures.
This helps in saving energy losses, waste, and marginal time savings on operations and maintenance. The predictive maintenance alerts help in optimizing operational frequency. It also helps in ensuring power grid reliability.
Conclusion
The hidden potential of enterprise AI lies in many advantages. The opportunities are endless. The growing AI technology has huge scalability for automation, innovation, and development to ease the business processes with phenomenal growth assurance and ever-increasing market share in coming years. Enterprise AI solutions are the need of the hour.
At Internet Soft, we are always keen to serve our esteemed customers with such high-level technologies in time and as per their needs.
Need assistance or have questions? Reach out us at sales@internetsoft.com.
ABOUT THE AUTHOR
Abhishek Bhosale
COO, Internet Soft
Abhishek is a dynamic Chief Operations Officer with a proven track record of optimizing business processes and driving operational excellence. With a passion for strategic planning and a keen eye for efficiency, Abhishek has successfully led teams to deliver exceptional results in AI, ML, core Banking and Blockchain projects. His expertise lies in streamlining operations and fostering innovation for sustainable growth
