AI will fundamentally change the workplace. In the near future, AI enabled machines will be involved in everything from onboarding customers and employees, through to customer service. We are at the very beginning of this journey. The biggest changes are being felt at the largest companies.
A 2019 report by Gartner revealed that enterprise use of AI has grown over 270 percent from 2014 to 2019. It’s also had an impact on staff recruitment, consumer insights, marketing, and improving unified communications as a service.
Indeed, AI gives business owners and managers a lot to get excited about. In this article, we’ll look at some of the ways that AI is helping in the workplace. Let’s get started.
Faster data analysis and reporting
AI can feel very abstract. There’s a good chance you are having a hard time imagining how AI is used in the workplace. As you can see from the chart below, AI is primarily being used by businesses for data analysis.
AI can speed up and improve the speed and analysis of data analysis by identifying patterns or analyzing trends without making mistakes. Two industries where AI is causing disruption are the fields of accountancy and law. This makes perfect sense given both fields based on analyzing large data sets, which need to be interpreted based on a clear set of underlying rules.
The legal services market is worth an estimated $1 trillion globally. One example of how AI is being used is in the process of contract reviews, a core part of the legal services market. Several startups are looking at how to use a combination of machine learning and Natural Language Processing to analyze contracts and determine which sections of a contract need to be reviewed.
In the field of accountancy, AI is being used by some companies to run company audits, invoice management processing, and expense management. This is just a snapshot of how companies use AI in the fields of data analysis and reporting.
Improved customer support
AI plays a major role in customer support. The technology is being utilized on hosted phone systems to improve customer relations. For example, many phone calls to a business are dealt with by auto-attendants that route calls to relevant departments.
Secondly, AI helps businesses prioritize calls and customer support inquiries. Using natural language processing, AI will scan an email or assign a call to an agent based on the importance. For example, a jewelry company could prioritize a customer support inquiry regarding a missing shipment, over an inquiry regarding a return.
For a company dealing with thousands of email support inquiries a day, this ability to prioritize support inquiries is hugely important. It can directly impact profits and have a significant impact on the overall quality of support customers feel like they are receiving.
Aside from methodically routing calls, AI is being used to help customer support staff answer common complaints. Answers and information regarding commonly asked questions are stored in online databases. AI programs, using natural language processing, interpret and anticipate customer support problems on a call and provide relevant information to the support staff. This helps the staff answer questions faster and more effectively, which improves the quality of customer support.
Below are some stats that emphasize just how important AI is in customer support:
- 51% of customer support agents that are not using AI say they spend most of their time on mundane tasks. This is compared to 31% of agents that use AI
- High performing service teams are 3.2 times more likely to have a defined AI strategy
Even the execution contracts now benefit from automation. Smart contracts rely on automation to record and verify provisions automatically. Instead of having customers go through exhaustive means of returning a damaged product or getting a refund for a canceled show, AI in smart contracts expedites the process and sends them their money back.
Many complex processes have now been automated thanks to AI. Think about how long it takes to do most manual tasks, even those as simple as research of filling out application forms. Technology has streamlined these actions and has greatly reduced the amount of time on mundane, repetitive tasks. AI technology has taken this one-step further.
A good example of how much time can be saved is given in an interview conducted by McKinsey, Leslie Willcocks, Professor of Technology, Work, & Globalization at the London School of Economics. A large insurance company automated the process of managing premium advice notes using AI. A repetitive task that used to take two days to complete is now completed in just 30 minutes, thanks to process automation.
This process does take some intelligent programming. It also calls for human workers to monitor how the system works independently properly. However, once the system is operating, it is a huge time saver, allowing the company employees to focus on other more valuable tasks.
A day-to-day example of how you could use process automation is scheduling a meeting between colleagues, or with clients. Setting up meetings can take a lot of back-and-forth emails to set up. However, with the necessary information from attendees, the process can be left to AI-powered scheduling assistants.
Cybersecurity is a rapidly growing sector of the economy. This is understandable given how many companies are transferring some or all of their business operations to the cloud. Unfortunately, it is experiencing a major talent gap. The industry expects that there will be an estimated 3.5 million unfulfilled jobs in the sector by 2021.
AI is already playing a role in helping to deal with cybersecurity threats. AI security can help problems by scanning a system for suspicious patterns. Its effectiveness is staggering, with 61% of companies reporting that cyberattacks would have been overlooked without the aid of AI.
The effectiveness of AI is understandable. In an industry where labor shortage is an issue, it is worth considering some of these stats that come from a survey of security analysts:
- 73% reported that a single investigation could take days
- 54% said many critical alerts go completely uninvestigated
- 30% of priority alerts never get investigated
This is clearly a problem. Utilizing AI, the software can identify, predict, problem solve, and learn about cybersecurity threats with minimum human supervision. These programs use machine learning to identify, then solve problems and find better and more effective ways to handle issues.
Instant Translation Services
AI is also transforming workplace communications by allowing employees who speak different languages to understand each other in near-real-time conversations easily. AI services being developed by companies like Microsoft, Amazon, Google, and others can automatically translate for both parties in a conference call.
A prime example of this is Google translate. It has become one of the most popular methods of translating foreign languages. You can see how effective this system is, and how rapidly it is improving every time you open Youtube and activate the captions.
What you access, depending on what you are watching, is both a transcription service and a translation service. These are features that are incredibly useful for video conferencing calls, and more.
The technology in this sector has made big strides in the past few years and is only going to keep improving. Researchers have allowed humans to have input on how to improve translations as AI systems are now being taught to make subtle language differentiations such as formality, tone, and subtext.
Productivity is improved when employees are freed from redundant and mindless tasks. Scrolling through calendars to look for open meetings times can be delegated to a bot. Ditto with build reports in spreadsheets to look for insights.
AIs have also improved the process of building information modelling (BIM), which is used to streamline the design, implementation, and construction of projects. Supercharged BIMs have been utilized by architecture and construction companies for analyzing their future building designs. They are able to catch possible obstacles and issues that were once hard to spot. And this is just one of many ways productivity has been improved by AIs.
While AI can directly improve employee productivity, it also comes with some critical, indirect benefits. Perhaps the greatest of these relates to increasing work satisfaction and employee happiness, which numerous studies have shown to be essential to peak performance.
The most obvious way it does this is by taking on the mundane duties that employees resent. Yes, the routine admin and coordination tasks that keep people busy without giving them something back. Take staff scheduling, for example. Too many people per shift lead to a duplication of tasks and get employees irritated. But too few workers per shift lead to a feeling of being overwork. Both lead to the same thing: disgruntled employees.
Workforce management solutions like Ximble examine a range of data points to anticipate future demand. In this way, AI is helping to recommend the right number of workers.
Most of the fear around AI is fear of the unknown. When employees aren’t familiar with the changes, their first instinct is naturally going to be apprehension. AI holds huge potential to improve employee productivity but needs the trust of employees to work. They need to be assured that AI is there to help and not kick them out of their jobs. By teaching the benefits and how to operate and improve the program, staff will be able to focus on the efficiency of their new workflow.
Since 2013, the number of jobs that use AI has increased by 450 percent. However, this has not led to a mass drop in employment. Instead, AI has fundamentally changed the types of jobs that are being done. Businesses have also come to share this outlook. A PWC study said that 72 percent of business decision-makers consider AI as a key tool for allowing humans to focus on more meaningful work.
Sam O’Brien is the Senior Website Optimization & User Experience Manager for EMEA at RingCentral, a global UCaaS systems provider. Sam has a passion for innovation and loves exploring ways to collaborate more with dispersed teams. He has written for websites such as Hubspot and UC Today. Connect with him on LinkedIn.Photo by Franck V. on Unsplash