Examples of AI software in business (2021 edition)
Updated: Aug 13
There are many ways to leverage AI software in business. Find out exactly how with examples ranging from marketing to healthcare and e-commerce to manufacturing.
Artificial intelligence has faced some resistance over the years, mainly because it’s been shaped out to seem like a threat to job security and privacy. But it isn’t; in fact, AI is the only way forward for businesses. Many organizations have increasingly begun to adopt and embrace this truth as they notice that all technology is an ally to the workforce, not a threat.
The pandemic has further proven the value of AI. Mount Sinai Hospital in New York was the first of many to successfully use an AI model to diagnose COVID-19. Mount Sinai researchers reported that their AI model diagnosed COVID-19 as accurately as an experienced radiologist.
In other industries, AI is steadily enhancing business processes, automating repetitive tasks, and creating better experiences for customers and organizations alike.
In this guide, we’ll cover examples of how AI software is currently being used in business. We’ll also offer suggestions of AI software that caters to small and mid-size businesses within the specific use-case.
Sales and marketing
At its core, AI software gathers and analyzes vast amounts of data points from current and past experiments to find patterns. In sales and marketing, these patterns are customer buying behavior.
To businesses leveraging AI, these insights are used to make predictions on a prospect’s likelihood to become a customer. In this way, salespeople and marketers can spend more time focusing on leads who are likely to become customers instead of spending hours on leads who are very unlikely ever to convert.
AI software also helps salespeople and marketers gain insight into where prospects are in the buyer’s journey. If the prospect isn’t ready to convert and needs more nurturing, AI software can provide valuable recommendations for the type of content that would interest them.
Additionally, taking notes, entering notes into a CRM, and organizing notes can generally be a tedious, time-consuming process for salespeople. AI can solve this problem with various solutions, including:
Automatically transcribe calls: AI can help transcribe sales calls so that your salespeople can more quickly go through the call to catch any important thing they might’ve missed.
Avoid duplicate leads: AI can merge duplicate leads to reduce the possibility of multiple salespeople reaching out, which could turn a customer off and create tension between coworkers (who gets the commission?).
Auto-populate lead data: AI can scan emails and business cards to auto-populate lead data.
Convert handwritten notes into text: By merging AI and OCR, salespeople can enter their handwritten notes into the CRM in seconds rather than manually typing each word one by one.
Organizations that leverage AI for sales and marketing today include College Forward, Harley Davidson, and U.S. Bank.
AI software solutions for sales and marketing
Clientelligent (for wealth and investment managers)
Whether you’re writing emails, SEO articles, sales letters, news articles, and much more, AI software can help.
For example, AI software can help you write SEO-friendly articles by:
Entering a specific keyword
Analyzing trends in the top 10-20 search engine results on Google and a few other search engines.
And then recommend topics, headers, and words to use. The software can even suggest how many times to use certain words and phrases.
Other AI writing software can detect and correct passive voice, grammatical errors, and even the tone of your writing. (Think of Grammarly or even your basic Word Processor spellchecker.)
Organizations using artificial intelligence for writing include the Washington Post, eToro, Discover, and Close.com.
AI software solutions for writing
AI seeks to help clinicians in many areas, but ultimately healthcare professionals still make the final call. During the pandemic, AI companies skyrocketed in the healthcare field, addressing not only issues of diagnoses and effective care, but innovating solutions to common healthcare problems.
One example of AI at work in healthcare relates to respiratory diseases. Even today, doctors use a stethoscope and largely rely on their ears to hear slight abnormalities in breath sounds. It’s not uncommon for slight variations to go unnoticed.
From here, AI can help in multiple ways. One way is to train a machine learning model on visual data of how the sound waves of a healthy lung look. When the model is exposed to an abnormal sound wave, the model performs badly, signifying there’s something wrong.
AI further considers additional factors such as vitals, symptoms, and risk factors before suggesting the probability of a patient having respiratory issues.
Other ways AI software is used in healthcare include:
Improving screening for tuberculosis
Helping detect prostate cancer and breast cancer
Helping predict avoidable falls, wandering, and hospital admissions in early dementia patients, saving caregivers and patients a lot of money, but most importantly, contributing to less stress
Detecting the possibility of anemia by using images of a patient’s eye.
Providing a doctor feedback on their consultation process. (AI mimics the mentoring process that junior doctors generally receive and makes specific recommendations based on thousands of previous consultations from more experienced doctors.)
AI software solutions for healthcare
Customer experience is probably one of the simplest and widespread uses of AI today. Think about automated chat bots, email marketing platforms, and even insight analytics to gather data on how customers feel about your product or service.
For example, Airbnb leverages AI to make it easier for future guests to browse through homes. Future guests who are picky on bathrooms can search specifically through pictures of bathrooms or any other specific room. Additionally, customers can search by specific amenities (e.g., washer and dryer).
Another example of AI at work includes Coca-Cola. Coca-Cola uses machine learning (a subfield of AI) to improve OCR reading for their proof of purchase promotions. They’ve increased engagement by making it easier to participate. Customers only have to take a picture of their bottle cap, and OCR automatically detects the 14 characters.
Before this, customers would have to manually type all 14 characters, which created too much friction and resulted in less participation. Customers inadvertently helped train the machine learning model over time by correcting the wrong characters.
AI software solution for improved customer experience
Imagine a woman halfheartedly entering a store at the mall, unsure if it’s her style. Then all of a sudden, within a matter of seconds, the employees completely rearrange the front display mannequin into the perfect outfit for her.
The customer loves the mannequin’s sunglasses, shoes, watch, everything. She makes multiple purchases on the spot. The customer is happy because she spent less time shopping and loves her purchases. The store owner is happy because they made money. Everyone wins.
Although this type of experience likely won’t happen in a physical retail store, it’s already happening in virtual stores.
Everyone by now is familiar with Amazon’s famous recommendation system, but most people don’t realize it’s powered by AI (machine learning, to be specific). Most e-commerce business owners don’t realize that Amazon also offers a fully managed ML service so they too can create personalized experiences for their customers.
With the average attention span ranging from 8-12 seconds, potential customers lose interest when the first few items they lay eyes on don’t intrigue them. AI gathers volumes of data such as potential customer’s browsing history and past purchases to decide which items to put on display first. Additionally, this helps boost upsells and cross-sells.
Besides Amazon, other organizations that use AI software for retail and e-commerce include Sephora, Macy’s, and Yamaha.
AI software solution for e-commerce
Recommendations AI by Google
When inventory demand is steady, it’s easy to calculate order size. However, if your business is affected by seasonal fluctuations or if your business holds many marketing promotions, you likely have an idea of how complex demand forecasting can be.
According to McKinsey, machine learning can help reduce inventory forecast errors by up to 50%.
The power of AI can also streamline the supply chain by enabling equipment to self-diagnose problems and order parts independently, reducing the need for manual inventory management and allowing managers to focus on more important aspects of business growth.
AI software solutions for the supply chain
AssetFlo (best for warehousing, manufacturing, oil & gas, airport, and parking lots industries)
Extending the useful life of fixed assets with preventative maintenance powered by AI is just one way AI contributes to the future of manufacturing. Anomaly detection algorithms notify operators when equipment isn’t behaving normally, which reduces unplanned downtime, improves productivity and saves businesses from costly repairs.
According to McKinsey in the same report stated above, AI-powered predictive maintenance can reduce annual maintenance costs by up to 10% and annual inspection costs by up to 25%.
AI software solutions for manufacturing
Financial planning is beginning to improve through AI-powered Robo-advisors. Robo-advisors use big data to analyze trends and make investment decisions for clients based on their risk-tolerance level, goals, and a few other answers to a set of questions. AI-powered Robo-advisors also have the capability of rebalancing portfolios, improving fund management, as well.
Additionally, AI software can help with bookkeeping and accounting-related activities such as improving cash flow forecasts and automating invoicing, reconciling accounts to bank statements, and entering transaction information into accounting software.
And on the back-end of finance businesses, AI also helps detect fraud and identify risky borrowers when it comes to credit and loans.
Organizations that leverage AI include Stripe, QuickBooks, Betterment, Schwab, and
AI software solutions for finances
Expex (automated bookkeeping solution)
PredictNow.ai (no-code ai solution for traders)
Succession Systems (bolsters compliance programs in relation to trading)
One of the most common uses of AI software is chatbots. These bots help customer service workers with repetitive questions such as “how much does X plan cost?”. This way, human workers have more time to answer the more complex questions and to offer more thorough support.
AI can quickly route users to their answers, which reduces wait times, especially during off-hours. Customers inadvertently help train the chatbots with negative and positive ratings.
AI can further personalize answers by segmenting users. Sample queries that lead to different answers are “Paid user? Yes or no?”, “Tag: Enterprise or small business?”.
AI software solutions for customer service
IBM Watson Assistant
Tips to effectively adopt AI
Cultural buy-in has been a significant cause of friction for widespread AI adoption. Fear that AI is here to replace jobs causes a lot of resistance and tension with employees.
A way to overcome this obstacle is to start with small projects to gain employees’ buy-in slowly. Once employees realize that AI is there to support them, they’re more likely to be on board for future, more significant AI projects.
Another factor to consider is transparency, specifically with customers.
For example, AI-powered chatbots and fraud detection may frustrate customers when things go wrong. However, explaining to customers through blogs or emails the reasons behind why transfers are flagged, for example, helps them understand more about how AI works and how it’s there to help them, not upset them.
No AI experience on your team? No problem.
A big goal for many AI companies is the democratization of AI. Once upon a time, only massive organizations could afford the luxury of AI. Now, AI has become available to organizations of all sizes, even those with no AI experts on staff.
Organizations can start small with drag and drop or no-code AI where, as the name suggests, no coding is necessary because the solutions come pre-built. Solutions like Amazon Personalize allow you to start leveraging AI within days.
Searching for AI-based solutions and want to know more? Contact us to learn more.