Whenever there is a digital transformation in business, the words ‘artificial intelligence’ (AI) and ‘automation’ circulate much more frequently. Businesses that prioritize machine learning algorithms and processes allow employees to work smarter and do more to put the business at a technological advantage. How exactly does this technology enable your business to get there? Here’s what you need to know.
AI vs. Automation - The Benefits
Conversations about digital transformation sometimes use the words ‘artificial intelligence’ and ‘automation’ interchangeably. However, there are significant differences in the use of words.
- Artificial Intelligence is technology built to be able to mimic what a human can say, think and do. Machine learning is a simple subset of AI and is a technical process that finds patterns in data, then predicts probable outcomes from it.
- Automation is software that follows pre-programmed ‘rules’, and is meant to let machines perform repetitive, monotonous tasks.
Through the use of AI, businesses can make smarter decisions on where to better automate their processes. A study by ServiceNow shows companies with more than 20% revenue growth are 61% automated on average and others with flat or negative growth are only 35% automated. Other conditional benefits include increased productivity, better business efficiency, and better employee task delegation on issues such as company growth. Automation helps mow down all sorts of data the same way termites chow down on wood. The next few sections will cover the key areas AI and Automation impact business.
Business Operations
A business that uses automation software and a powerful CRM help create more efficient customer interactions and increase overall productivity. For internal departments like Accounting, workers can use automation for syncing bank feeds and integrating payments. This dramatically reduces the workload of clerical and bookkeeping staff, while allowing businesses more timely access to accurate financial information. A research study done by Xero, a New Zealand based software company, suggests that by 2020, accounting automation tools will be commonplace for finance professionals to help them add value to businesses. The end result will be a more efficient, cost-effective business and a more productive workforce.
Customer Service
As markets move globally, customer service is needed 24/7. Agents cannot maintain 24/7 coverage without putting up additional costs for a business. Most companies are starting to look for ways to balance between tasks an agent can accomplish, and those that can be handed off to intelligent solutions. As a result, chatbots provide a cheaper, more scalable alternative for customer service. Chatbots will still need assistance for more complex issues, so utilizing both bots and agents will significantly boost your overall customer service.
Smart Processes
Machine learning shifts the control of influence from leadership to the flow of data. Automation has greatly reduced the time it takes to do many manual processes. Tasks like categorizing tickets, recommending solutions, and sorting inventory can easily be managed with machine learning. The more data a company has to work with, the more the machines learn, the smarter and more accurate their algorithms become. Machines do most of the ‘heavy’ thinking and employees can focus on more complex tasks.
Data Visualization
With big data comes big data visualizations. Our brains process visual information faster and more wholistically than with text. Workers can develop different types of infographics – such as terrain models and demographic charts – using AI assisted software to chunk down complex data sets and make things easier to interpret.
KPI Tracking
With the help of AI, typically in the form of bot assistants operating within large sales ecosystems, salespeople can better review and measure performance data to help reduce the number of hours spent on non-essential tasks.
Consumer Insight
AI allows marketing and sales teams to better spot trends within areas that have huge data sets, such as sales activity across sales cycles, consumer activity, and the buyer journey. Companies can design working practices that are more successful based on research and analysis and can target their audience more accurately in their campaigns. In 2017, Salesforce conducted a study of marketing leaders worldwide, and the results showed that more than 60% of marketers envision leveraging AI to create dynamic landing pages, websites, programmatic advertising and media buying.
