Four ways artificial intelligence can streamline business processes

From the Internet of Things to sales and marketing, artificial intelligence is having an impact on the way companies do business. Here are 4 ways artificial intelligence is revolutionizing businesses right now.

Today, artificial intelligence (AI) is everywhere. While the technology is still in its infancy, there is no doubt that AI will soon play a central role in almost all areas of business. Evidence of this fact is the presence of artificial intelligence in several applications, although its current capabilities only scratch the surface of everything it can do.

From the Internet of Things to sales and marketing, artificial intelligence is having an impact on the way businesses do business. Here are 4 ways artificial intelligence is revolutionizing businesses right now.

1. Stable development of the Internet of Things

Heavy industry is one of the earliest industries to adopt Internet of Things technology. From tracking parts lifecycle to quality control, IoT plays a central role in manufacturing and supply chains. Typically IoT devices transmit usage data to a control center, which ingests these data sets for further analysis.

While this sounds great, there are some limitations. First, collaboration is difficult when a control center has access to multiple data sets. For example, IoT devices connected to industrial pumps will generate data sets measuring flow output and component quality. These data sets are monitored by different teams, making setting alerts for usage thresholds challenging.

Artificial intelligence changes this by allowing businesses to create custom alerts for different teams within the organization. It also solves the problems surrounding large amounts of data. The human eye takes hours to verify and parse these data sets. Artificial intelligence can process data instantly and quickly alert operators to improper use or potential risks.

Startups like Sternum are increasing this observability by using artificial intelligence to simplify the work of those building IoT.

Sternum has developed an AI-based learning engine that uses user-defined trace data to create profiles of desired device behavior and highlight important and anomalous patterns. Once the device is connected, the system begins collecting data and, after a brief learning period, begins acting as a second set of eyes, providing alerts about unusual activity that could take a human operator hours, or even days. To discover.

Thanks to these advancements, enterprises can unleash more of their IoT devices to collect larger data sets and better apply lessons learned from analytics.

The result is a safe operating environment that produces results with optimal efficiency.

2. Simplify the B2B SDR process

B2B sales are indispensable to the success of enterprises in these fields. However, B2B representatives face significant challenges. First, the buying cycle is long and involves multiple stakeholders. Interpreting purchase intent can be challenging as sales terms can change from product demo requests to callbacks. For example, a competitor may release new features that cause more problems.

While businesses can’t change the length of the customer buying cycle, they can give sales reps more firepower during the sales process. AI-assisted sales is now a game-changer for B2B sales, and SDR is better suited for it.

Predictive AI can now provide sales reps with buyer intent predictions based on their previous behavior. By measuring engagement on marketing materials and conversations, AI platforms can guide sales reps in determining the challenge level of closing a sale.

Complementing predictive artificial intelligence is prescriptive artificial intelligence. The former provides sales reps with action items based on what happened, while the latter processes data in real time to provide sales reps with a way forward. It provides sales reps with a way to close deals.

Platforms like Demand Science can track prospect behavior and identify gaps in a business’s current sales process. The result is a smooth customer experience and more opportunities to convert into sales. In some cases, AI platforms even use natural language processing to engage potential customers when sales reps are not around.

So prospects stay engaged and sales reps can follow up with additional information to help close the sale faster.

3. Support more customer self-service

Chatbots represent artificial intelligence in the customer service field for some time. However, recent developments have pushed AI further up the customer service chain, helping businesses reduce less important customer calls and helping service representatives prioritize important customer calls.

Artificial intelligence can now interact with customers through multiple channels. The humble chatbot has become more powerful, answering complex customer questions than ever before. For example, an AI chatbot powered by Dialpad can retrieve data from previous conversations, customer order data, and dispute conversations to provide insights into status and more.

The platform also interacts with customers through voice channels. For example, customers can dial a number and have common queries resolved by entering information that the AI ​​processes and delivers through voice. The result is lower call volume and more efficient customer service.

AI is also good at detecting when a customer wants to talk to a human, rather than interact with a bot. Often, customers have difficulty retrieving a phone number or email that allows them to contact a person. Artificial intelligence can quickly provide this number as an answer to a simple question.

4. Reduce the complexity of accountants

Accounting is a very mysterious field, and the smallest mistake can complicate the problem. Big companies are afraid to risk restating financial results for fear of brand damage and other repercussions, including plummeting stock prices.

Currently, artificial intelligence embedded in accounting platforms can automate bookkeeping and clerical tasks, such as accounts payable matching. For example, once a payment clears, AI will classify it based on the correct journal entry and match payment receipts with invoices and purchase orders.

So accountants have all the information they need at their fingertips. More complex platforms, such as the one being developed by Vic.ai. AI will go one step further and automate accounting entries. The result is less paperwork for accountants and more time to analyze financial performance.

Artificial intelligence also makes reporting easier. CFOs looking for financial insights into their performance can request data in natural language and receive a customized report that digs deeper into the data.

Artificial Intelligence has just begun

The artificial intelligence revolution has begun, and we are witnessing the biggest step forward in technology. While time will tell where business will go, there is no doubt that AI is here to stay and bring efficiencies to everyday workflows.

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