Today, the business is entering a new era ruled by data. What was once the realm of science fiction, AI in business intelligence is evolving into everyday business as we know it. Though, it’s not a simple process for companies to incorporate machine learning into their existing business intelligence systems.
But as AI has gained momentum, prominent application providers have gone beyond creating traditional software to developing more holistic platforms and solutions that better automate business intelligence and analytics processes.
Here are the 7 Amazing applications of artificial intelligence in business,
1. Improved customer services
In case you run an online store, you’ve certainly noticed several changes in customer behavior. 30% of all online transactions now come from mobile. Although smartphone owners spend 85% of their mobile time in various applications, only five apps (including messengers and social media) hold their attention.
In order to encourage mobile app adoption, the world’s leading retailers like Macy’s and Target install beacons and turn to gamification. Facebook and Kik went even further and launched chatbot platforms. A chatbot (aka “bot” or “chatterbot”) is a lightweight AI program that communicates with users the way a human assistant would.
2. Evolution of marketing and advertising
New technologies have changed the way marketers have been working for decades. Using the AI Wordsmith platform, you can have a news article written (or generated!) in mere seconds. Facebook uses machine learning algorithms to track user behavior and improve ad targeting. Airbnb has developed a smart app to optimize accommodation prices taking into account lodging’s location, seasonal demand and popular events held nearby.
With Artificial Intelligence, marketers can automate a great share of routine tasks, acquire important data and devote more time to their core responsibilities — that is, increasing revenues and customer satisfaction.
3. Effective data management and analytics
By the end of this year, there will be 6.4 billion connected gadgets worldwide. As more companies start using IoT solutions for business purposes, the amount of data generated by smart sensors increases (and will reach 400 zettabytes by 2018). Thanks to Artificial Intelligence, we can boil this data down to something meaningful and gain a better insight into asset and personnel management.
Nearly 43% of companies access potential employees’ social media profiles. Now you can trust the task to a smart algorithm and save your HR’s time.
4. Workload automation
Thanks to the Internet of Things and AI solutions, companies can reduce operating costs, increase productivity and eventually create a knowledge-based economy. Smart programs will enable companies to use their resources more effectively.
General Electric fights machine downtime by collecting and analyzing data from smart sensors installed on its equipment.
5. Sales enablement
There are numerous ways for machine learning to enhance applications, including those from Apptus, which offer recommendations on actions that companies can take to boost their sales channels. Apptus says it specializes in the connection between a customer’s intent to buy and the realization of revenue by a company.
AI and machine learning platforms are getting better at predictive tasks, such as determining what customers might want based on the information that they are fed.
Medical laboratories and healthcare startups are using AI to develop imaging and diagnosis tools. Researchers have already developed software that can recognize a range of conditions from early-stage tumors to mutated blood sample DNA. According to the National Academy of Medicine, incorrect diagnoses are responsible for up to 10% of U.S. patient mortality, and close to 60% of medical malpractice claims. This leaves plenty of scope for AI technology to improve outcomes and reduce costs for providers.
7. Autonomous Transportation
Autonomous cars use sensory hardware, such as cameras, radar and lasers to track their surroundings as they move from point to point. The information gathered by these sensors must be processed and interpreted in real time so the vehicle can brake, accelerate and turn at the appropriate times. Similarly, the commercial use of unmanned aerial vehicles for package delivery will require AI assistance to detect obstacles and avert potential collisions without the need for direct human control.