The best breaking news apps give you all the latest headlines from around the world. They also keep you connected to the local news that affects you and your community. They do this by using your location or a list of interests you set up. Some apps even feature...

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Use Cases For AI in B2B and HR



AI applications are transforming industries and allowing companies to take advantage of its superpowers. These applications include automation, data analytics, and natural language processing.
Artificial intelligence will be able to do almost everything that involves a business process, and do it better than a human.
The first business processes to get taken over by AI will be the ones that involve repetitive tasks, rule-based systems, and data handling.
1. Automated Customer Service
Automated customer service enables businesses to provide fast responses to repetitive and simple questions. This approach saves time and energy for human support agents, who can focus on more complex cases.
Another way AI can help with customer service is through data collection and analysis. This allows companies to get more insight into their customer experiences and understand how they prefer to be communicated with.
Customers have varied preferences, based on a variety of factors. Some prefer chatbots and self-service options while others want a live conversation with a support agent. In this case, AI can be helpful in providing a seamless transition between automated and human customer support.
2. Automated Inventory Management
Automated inventory management systems allow businesses to manage their stock and ensure they’re always stocked properly. They track stock levels across sales channels and locations, update information and notify when items need restocking or need to be replaced.
Automating your stock management also saves clerical errors and helps you keep accurate records of inventory and its lifecycle. This also reduces the number of stock outs, shortages and items falling out of warranty.
If your business is relying on manual methods to keep track of stock levels, you might be losing out on profits due to inaccurate data and a lack of timely restocking. These problems can lead to lost sales and customer loyalty.
Fortunately, many leading automated inventory solutions have been purpose-built to address the needs of modern companies. For instance, they can scan orders, process fulfillment tasks, print shipping labels, and more.
3. Automated Sales
Sales teams often find themselves battling against a long and complex sales cycle. This is particularly true when it comes to B2B customers, who need a lot of validation and hand-holding before they commit to buying.
AI can make these processes faster by analyzing the data that sales reps collect from their calls and interactions with customers. This will help them determine when to reach out and what kind of follow-ups to send to the customer.
Another area where AI can be used in sales is predictive forecasting. This could be done by combining historical data to create highly precise estimates.
This helps sales managers avoid the risk of overestimating a deal score or under-estimating their earnings potential. It would also make forecasting more consistent over time, which typically leads to happier sales reps and better revenue expectations.
4. Automated Human Resources
AI is a great way to simplify and automate a wide range of HR processes, from recruiting to onboarding to offboarding. In addition to helping improve efficiency, automating these processes can also reduce errors and free up employees’ time for more important work.
One of the most common use cases is recruitment. Companies rely on automated tools to sift through applications and identify profiles that meet their selection criteria.
Another example is employee data management. Robotic process automation can link employee records from multiple databases and systems into a single source of data, removing the need for manual entry.
AI can also automate a variety of payroll and time-tracking tasks, including verifying self-reports for overtime, leave, missed hours and other labor-related issues. Using RPA-based software robots to automate this process can reduce the need for human intervention, saving time and increasing accuracy.
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