The Top 6 Ways AI Is Improving Business Productivity
Using AI for business is becoming increasingly prevalent in the enterprise world, and it’s being used for many different operations and tasks. However, it has the biggest impact when used to increase business productivity.
The current generation of artificial intelligence, which is heavily supported by big data and machine learning platforms, is starting to worm its way into the average workplace. When implemented effectively, it has the potential to reduce operational costs, improve output and productivity, and boost employee satisfaction by taking over many rote and undesirable tasks.
Gartner reports that enterprise use of AI has grown over 270% during the past four years. The technology is used for many purposes, from marketing and consumer research to employee experience and staff recruitment. And yet, business productivity stands to benefit the most from its adoption.
Here are the top six reasons why.
1. Predictive Sales
With the help of AI, businesses can focus on leads with the greatest potential for success. How?
In practice, the idea is simple, but it requires the support of advanced algorithms and AI-powered solutions to sift through massive datasets. It’s no secret the average business is amassing huge stores of customer and behavioral data. Putting this information to use can mean the difference between a competitive edge and continued failures.
AI can be used to identify patterns and trends within this data, as well as for image and object recognition, all of which can be used to recognize customers who would be more willing to support the business and its products or services. Imagine knowing whether or not a customer will pull the trigger and buy before they even visit a store or online storefront.
The systems analyze customer and market data, historical sales details, common behavioral patterns, and so on. Then, they build customer profiles that help predict, with great accuracy, what a client or consumer might do going forward. (Read also: How AR/VR Will Up the Sales Game.)
2. Reviewing and Extracting Information
A rote and undesirable side of any business involves poring over hundreds of documents, papers, and statistics to create valuable insights. In the past, for example, a business would have to collect, analyze, and notate customer invoices to find popular products.
That’s no longer necessary, as digital reporting systems present this information faster and more effectively. But AI and machine learning tools are the next steps in that evolution. They can unlock hidden insights within that digital content by reviewing and extracting critical information that the human eye might have glossed over.
Simply put, AI can be used to collect information from documents to reduce review times and improve operational efficiencies by informing future decisions and events. The technology is already being put to good use in the legal and management industries to aid in contract intelligence.
As a process, it automates the extraction of relevant information that’s often buried in documents. The result is a more effective review and deployment process with a greater quantity of actionable insights to leverage.
Through an automated document review application that Deloitte developed, one team was able to increase the scope of their contract review process by up to 150,000 documents.
3. Leveraging Smart Chatbots
Customer service solutions require a lot of back-and-forth between agents and customers, especially in the initial stages. AI, or more specifically, smart chatbots, can be deployed to handle many of those low-level communication steps, which takes the stress away from employees.
Chatbots can collect names, account details, and basic information about the problems customers are having. If the chatbot cannot provide direct assistance, that information is then relayed to a human rep, who can take over from there.
AI can also be used to create always-on support solutions that tackle simple tasks and problems after hours. A customer might need help finding a support document or tutorial, for example, and the chatbot can direct them appropriately.
Babylon Health has implemented chatbots seamlessly, using them to collect basic patient information and health symptoms, and then compare that against a database. Afterward, patients are given some information on the next steps they should take, as well as potential causes to their problems.
If the discussion needs to escalate, the chatbot will connect patients to on-call doctors and physicians. (Read also: Top 20 AI Use Cases: Artificial Intelligence in Healthcare.)
4. Implementing AI Tools
Offering general support through AI tools can boost employee satisfaction, which leads to higher productivity. Automation can be used to replace rote and what would otherwise be considered unproductive tasks, for example, allowing workers to spend time doing what they enjoy more.
These same AI tools can also be leveraged in many unique ways to improve the employee experience. When enmeshed with the internal culture, they can improve employee buy-in and enhance the day-to-day for workers. AI can even be utilized before an employee is hired, by implementing tools that help with the recruitment process.
One tool might recognize when an employee goes above and beyond, for instance, and flag them for a promotion or award. Another might ingest customer reviews to find employees that have been mentioned, by name, consistently.
5. Automated Call Management
AI can also be used for call management to direct calls to the right people. There’s almost no reason to have your workers sitting by the phone waiting for communications to come in.
A forward-facing system can do that, similar to chatbots, to collect basic information from clients and customers and then direct them to the appropriate department or professionals. In fact, this is one of the best examples of automating repetitive work.
It benefits your call service teams, as well, freeing them up to work with elevated concerns, as opposed to answering every call that comes in regardless of priority.
6. Real-Time Operations
Traditionally, it would take time to assess and extract insights from incoming data, especially customer reports. In the past, you would have a team dedicated to doing this, who would review invoices, sales information, and much more. When they did come up with something, it would be essentially delayed.
AI and machine learning can be used to do this much faster, and almost instantly in many cases. The data flowing in is constantly being analyzed and processed to create real-time insights and inform direct action, or creating alerts about suspicious activity or implementing cybersecurity measures. It does this without the same prejudices a human may consciously or unconsciously hold that influence decision-making, although machine bias is a problem that has been recognized and needs to be combatted.
This significantly improves business productivity by allowing you to pivot and make decisions based on contextual and performance data almost instantly. AI for IT operations, or AIOps as it’s called, can help security teams identify and react to events faster than ever. (Read also: MLOps: The Key to Success in AI Enterprise.)
Imagine this same method for dealing with supply chain issues, product and inventory shortages, customer sentiment, dealing with social media posts and strategies and much more.
AI is the Future of Business
AI has a lot to offer the business world. And there are many benefits to go along with its adoption, from more accurate, real-time operations to improved employee satisfaction and better customer service opportunities.
What’s more, the technology will only get better from here on out as more companies realize its potential and unlock new use cases.