Business applications of Artificial Intelligence (AI) range from the obvious to the outlandish.
Here we look at 9 examples of AI used in business today. This is not intended as a complete list, but an overview of different business verticals and how they are using AI today.
1. Marketing: Predictive Analytics in the B2B Sales Cycle
AI is being used today to help predict and uncover data that will inform optimal sales and marketing strategies, based on past customer interaction patterns. This allows businesses to improve lead generation, connect with customers at key times in the buying cycle, drive up conversion rates and increase revenue.
Companies are using AI to predict customer behavior by analyzing historical data from across their sales and marketing channels, including web traffic, content engagement and lead quality scores. This allows them to target customers with the highest likelihood of purchasing at each stage in the buying cycle, resulting in increased revenue.
2. Finance: Investing Overnight vs. In a Decade
Investment is one area where AI and predictive modeling is already having an impact. However, we're still in the early stages of applying this technology to financial applications like investing - a pursuit that's traditionally been both highly complex and painstakingly slow (who hasn't left their stocks on autopilot for a few months before checking back in?).
We are only at the beginning of building this type of product. A significant amount of work remains before we can reach our long-term vision. As we've discussed elsewhere, quantitative trading is already having an impact on how investment decisions are being made today - and it may be a lot sooner than you think. Our team here at Manifold is working hard to bring algorithmic trading to the retail investor with our innovative platform.
3. Manufacturing: The Death of 'One Size Fits All'
Industrial manufacturing has been a particularly fertile area for AI adoption because machines benefit significantly from the ability to process external data and adapt their behavior accordingly. This is particularly true for manufacturing robots, which are most commonly found in automobile assembly plants or electronics factories.
Manufacturing robots have been adopting AI and Machine Learning for some time now. For instance, companies have combined probabilistic machine learning with perception systems to create a hardware-software platform that can learn to identify defects and other issues in real-time - a capability that can help optimize the manufacturing process and reduce waste.
4. Education: Smart Classrooms, Student Success & Lifelong Learners
The use of AI in education is fascinating to watch because it's currently one of the more promising applications for this technology in the consumer space. These systems are being designed to adapt to each student's learning patterns and predict what they need to learn next.
We've already seen impressive results from AI-powered tutoring systems in the consumer space - like Chinese startup Duer, who has developed an interactive chatbot that can give users personalized English lessons via text message.
But this is a technology that is still in its infancy. Of course, AI will eventually be used to implement smart classroom applications, but it's not there today. Here are a few interesting examples of the future potential for using AI in education:
5. Customer Service: Now with Enhanced Emotion Detection & Cost Cutting
The promise of voice-based customer service has been around for years now. However, because of the significant challenges presented by natural language processing and speech recognition - among other factors - those promises have yet to materialize in a meaningful way.
In 2021, we will see AI deployed into customer service applications that can improve our experience across industries like travel, financial services and healthcare at scale. These applications are designed to adapt to each user's speech patterns and provide a more personalized experience.
In addition, we will see AI used to identify the emotion in callers' voices (i.e., their tone of voice) - an ability that can be extremely valuable for identifying frustrated or angry customers who may need additional support. This is already being done today by companies like CallMiner, whose AI platform can analyze customer service calls to identify "hot-button" moments and use them to predict how customers will respond in the future.
This is a technology that's still in its infancy, but has high potential for providing cost reductions on the order of 30-40%+ through the use of AI-powered chatbots.
6. Autonomous Driving: A Year of Public Safety & Regulatory Challenges
Autonomous driving will be the story, with companies like Tesla leading the charge to release technology that has the potential to save tens of thousands of lives on our roads every year. It's also easy to see how autonomous driving will change the way we live - and how our cities are designed.
But this technology is still in its infancy, and will be for some time. Industry leaders are just starting to test their self-driving cars on public roads (and they're doing it very carefully), but these are fundamentally different vehicles than what most of us drive today. We can expect more highly publicized accidents in the news this year - which will increase skepticism of autonomous driving.
This technology also has a long way to go before it can be considered safe for use by consumers, and it will take massive investment from companies like Google, Tesla and Uber to get there. This is a technology that's clearly disruptive but it's also going to require a lot of public discussion this year.
7. Chatbots: Is This the Year That They Finally Take Off?
Chatbots were one of the most talked about technologies in 2019, but after years (and billions) spent on R&D by technology companies and media organizations, usage rates have picked up.
We've seen hundreds of chatbot failures in the past years, but there's still a lot of belief in this technology- particularly among entrepreneurs and VCs. Some people believe that the messaging wars happening today will make chatbots mainstream soon.
8. Machine Vision: In 2021 AI Will Begin To See ... Everything
Today, most people associate AI with machine learning and image recognition. In 2021, it will become clear that we are entering a new age of visual perception where AI systems will be able to understand the world around us in 3D - using not just visual data but also contextual cues like GPS coordinates. This technology is foundational for many other use cases for AI (including autonomous vehicles).
Machine vision is also being used to identify pedestrians and suspects in surveillance images by companies. Adoption of this technology remains slow due its cost but we expect growth rates to accelerate as prices drop.
9. Business Intelligence: AI & Deep Learning Will Transform BI Use Cases
2021 may go down as the year that "Big Data" became "Big Info." We're beginning to see organizations make progress in harnessing all of the data they have at their disposal, but we still have a long way to go.
The use of AI and machine learning platforms like Google's AutoML to create custom predictive models that are optimized for specific business processes. This has the potential to unlock a lot of value across all industries, and we're seeing early adoption in retail and e-commerce use cases.