How artificial intelligence can improve your business processes
How artificial intelligence can improve your business processes
Businesses around the world are always on the lookout for ways to improve their profits. They need more and more efficiency and optimization. Artificial intelligence is, as you might expect, plays a key role in helping businesses improve their processes.
Big data companies are pioneers in exploiting AI for improving business processes. However, even small businesses can benefit from everything that machine learning algorithms have to offer. Artificial intelligence can be used to speed up processes, make them easier to go through or make businesses more profitable.
Examples of AI in Business Processes
AI for Business Process Automation
Process automation refers to using technology to automate any process and often remove the human factor altogether. Every business has several boring and repetitive tasks. Such tasks scream to be automated. Even though robots often come to mind when automation is mentioned, it can also refer to simple software that is capable of replacing humans in a specific task.
Examples of process automation in businesses are many. NASA used several RPA (Robotic Process Automation) systems to automate payments, spending, and HR. They were satisfied with the results, and they plan on deploying more complicated systems. In terms of complexity, RPA systems were always the easiest to implement. Even Jim Walker, the leader behind these projects, didn’t think they were too complicated, “So far it’s not rocket science.”
AI for Cognitive Insight
Cognitive insight implements big data to learn more from plain data. It often relies on deep learning and machine learning algorithms. In most cases, the data comes from your customers/users, and artificial intelligence tries to learn from it. The goal is to make customers more satisfied by learning what they want.
Examples of cognitive insight are very famous. Amazon collects big data about its customers and pulls it through machine learning algorithms. It’s the secret behind their eerily precise suggestions on what to buy next.
AI for Cognitive Engagement
The final type of AI in business applications is cognitive engagement. It involves employee and customer interactions using natural language. These AI models combine emotional intelligence with machine learning, and they work in real-time. Its goal is to make communication, data collection, and customer interactions simpler.
Credits: How To Improve Customer Service With Chatbots | by Richard McGrath - Chatbots Magazine
Famous examples include customer service bots that can replace humans partially or even entirely. Such systems need to feature natural customer interactions and prevent the user from realizing he’s speaking with a machine. It needs to appear realistic and showcase emotional intelligence.
How AI Can Optimize Business Processes
Since artificial intelligence is practically applicable to any scenario, there are many ways in which it can help optimize business processes. Deep learning and machine learning algorithms only need big data to work. If you can provide it, you can benefit from its potential. Here are some ways artificial intelligence can help your business:
Optimizing sales and marketing with AI
Artificial intelligence is great for enhancing sales. It can help retailers organize their inventory, plan their store layout, and predict what their customers want to buy. AI can help sellers figure out which items they need to put on sale. It assists businesses to target ads to the proper people and helps them understand why behind the buy.
Content generation with AI
Alibaba has deployed a tool named AI-CopyWriter. It can write engaging and informative copy in no time. Writing is not the only thing artificial intelligence can help generate. Combined with everything from the first point, it can create ads, promo videos, and flyers to improve your company’s sales.
Credits: Alibaba Says Its AI Copywriting Tool Passed the Turing Test - Adweek
AI in Manufacturing
Manufacturing already features automation and robotics in abundance. Even though artificial intelligence is often mentioned together with robotics, traditional robotics doesn’t feature AI in its core sense. Robots don’t do big data analysis, and they don’t learn while working.
Artificial intelligence can change that. The motivation behind powering robotic process automation with machine learning is to integrate robots with humans in the supply chain. We can refer to it as intelligent automation. The goal is to have humans working together with robots in the same workplace. Robots can use computer vision to work properly around humans, and they can learn from their interaction to prevent accidents from happening. Intelligent automation can help make robots more common in many applications.
Credits: Robots and Workplace Safety - HSI
AI in Recruitment
Imagine how many job applications Google receives when they post a job opening! Reading them one by one would take many people and too much time. Of course, artificial intelligence can help here as well. Artificial intelligence companies like Pymetrics specialize in AI-powered recruitment. Algorithms perform data analytics on all job applications. It can help determine unsuitable candidates and eliminate them. It can save time, money, and remove the subjective factor in decision making.
AI in Security
Finally, security aspects should not be forgotten in a supply chain. Deep learning methods can be useful for various security-related business applications. Businesses that work with plenty of financial transactions need to make sure their money and data are safe.
AI can help as AI security systems have proven to be better in detecting hackers and fraud attempts. AI models can train to detect fraud or hacking attempts. This way, when an actual attack occurs, AI security systems can recognize the attacker sooner and react promptly.
Future Applications of AI in Business
No matter how far we think we’ve come, the future is often brighter. AI has come a long way, but there are still improvements to be made. Artificial intelligence companies are working on new solutions to advance humanity. It especially applies to silicon valley companies like Google, Microsoft, IBM, etc. Here are some possible future applications:
- AI on Chip
Business applications like natural language processing and computer vision are becoming more and more popular. It’s only a matter of time before silicon valley companies start shipping chips that specialize in popular data analytics algorithms. With enough computing power, most algorithms will run in real-time! The supply chain will no longer exist without some AI implemented.
- AI in Combination with Other Emerging Technologies
5G technologies are slowly spreading throughout the world. They offer opportunities to revolutionize app and AI development. 5G fuels the IoT, and the Internet of Things is something that just can’t exist without AI. With fast transfer speeds, AI algorithms can shift to data centers to improve speed and keep your device idle.
Blockchain technologies offer a fantastic, decentralized approach to finance, contracts, and other sensitive processes. The combination of AI and blockchain is still on hold, but the future might bring some exciting breakthroughs in this field.
Artificial intelligence is developed by data scientists, but they work for businessmen. The core motive behind every business is to make a profit at the end of the day. It’s the reason why many AI applications are related to retail and service-providing industries. Even Google, which we know as a tech company, earns its money through advertising. Businesses need AI to improve their daily routine. AI can help with sales, marketing, process automation, and much more. Every business process can be optimized. If you can speed it up, make it cheaper or make it better, AI can probably help. Some
In the future, Silicon Valley companies will probably step their game up. There are exciting new technologies that can exploit AI in the best way possible. Most businesses hesitate to step in now because of high AI development costs. Not everyone can afford to buy data and rent a data center. However, when enough new artificial intelligence companies form, these technologies should be available to everyone.