Top 4 Applications of Artificial Intelligence in Business
[UPDATED 2021] During the 2016 Tata Communications CEO Summit, Jack Hidary, advisor to Google X Labs and founder of the Clinton Global Initiative, gave a word of advice to companies having second thoughts about artificial intelligence. Mr. Hidary’s message was crystal-clear: you could either start incorporating AI in your business processes or lag behind your competitors.
Five years on, what’s the state of artificial intelligence in business, and how is it used across different verticals?
Artificial Intelligence in Business: 50% of Companies Adopt AI to Generate Value…
According to McKinsey’s The State of AI in 2020 report, half of the organizations have already incorporated at least one form of artificial intelligence into their workflows to produce value.
Increasingly, this value comes in the form of additional revenue streams and cost reduction: 22% of the respondents attribute at least 5% of their companies’ net income to the adoption of artificial intelligence, while 50% of companies claim AI helps optimize operational expenses.
However, AI adoption levels vary significantly across industries and parts of the globe, with high-tech and telecom companies from the USA, Western Europe, and Asia reporting higher artificial intelligence penetration rates and greater usage of advanced AI solutions, such as deep learning.
…But Things Aren’t Looking as Bright on the ROI Side
Through 2020, enterprises reportedly invested $50 billion in artificial intelligence solutions. Yet, only 53% of AI projects eventually move from prototypes to production; out of the remaining projects, just 11% bring a positive ROI.
There are several factors undermining enterprise AI initiatives:
- Technology roadblocks, including wrong choices of an architecture pattern, inaccurate or insufficient training data, and failure to balance out algorithm accuracy and explainability
- Lack of DevOps and MLOps skills preventing businesses from deploying AI solutions company wide
- Wrong perception of AI capabilities and potential use cases
- Ethical issues, such as the algorithms’ inherited bias and workflow automation leading to massive reductions in employee count
AI in Business: Top 4 Use Cases
Currently, most AI applications in business revolve around:
- Analyzing heterogeneous operational data stored in siloed IT systems and leveraging this data to detect and eliminate inefficiencies
- Automating back-office operations and fastidious tasks — in offices, at warehouses, and on the factory floor
- Implementing advanced customer analytics and personalization tools to boost the efficiency of marketing campaigns and grow sales
- Operating end-user devices and industrial equipment via voice interfaces
Workflow Automation
While some experts claim AI could take away 30 million jobs in the USA alone, the current state of artificial intelligence does not allow companies to blindly trust critical tasks to smart software and robots. Instead, qualified employees monitor and adjust AI-driven systems’ performance, teaching algorithms to make responsible, well-informed decisions.
Ultimately, AI’s value lies in the automation of mundane and potentially dangerous tasks, such as drilling rig inspections, heavy lifting jobs at fulfillment centers, and updating information stored in disparate IT systems.
Engie SA, an electric utility company from France, uses drones and AI-powered image processing software to monitor its infrastructure. Brick-and-mortar stores across Europe are rolling out autonomous shopping systems to minimize customers’ interactions with staff and other shoppers. And Amazon implemented 200,000 mobile robots across its warehouse facilities to save employees the trouble of walking ten miles or more daily.
Data Management and Analytics
With artificial intelligence, businesses can glean insights from historical and real-time operational data to better manage their assets and staff and reduce operating expenses.
General Electric, for instance, reduces machine downtime by collecting and analyzing the data produced by equipment sensors. Another example comes from Fama, a Californian company that helps HR specialists scan potential candidates’ social media profiles to detect inappropriate content and measure their culture fit. And a leading retail company tapped into artificial intelligence to help business users generate all kinds of reports without sending a service request to the IT department.
Personalization
From product recommendation engines suggesting new music and TV series you might like to AI chatbots helping users boost self-esteem, artificial intelligence is paving the way for more meaningful and personalized interactions with technology. And it doesn’t come as a surprise that marketers leverage the new super-power to launch targeted ad campaigns and grow sales.
This way, Samsung parsed social media data ahead of a new smartphone launch to figure out what features users were excited about the most — and built their entire promotion campaign around those insights. Another example comes from General Electric: the company harnessed AI to monitor customer complaints on social media and redesign one of its trucks before launching the new model.
Voice Interfaces
Consumer electronics companies became the early adopters of smart assistants that help users orchestrate devices and search things on the Internet by issuing commands in natural language. In the past few years, automotive brands like BMW and GM have been integrating Alexa into in-vehicle infotainment systems. And industrial equipment manufacturers are beginning to swap dashboards and physical controllers for highly intuitive voice interfaces.
The growing adoption of artificial intelligence in business will most likely lead to the elimination of non-natural user interfaces. Nest thermostats, for example, use reinforcement learning to remember a homeowner’s preferred settings and adjust the temperature accordingly.
The COVID-19 pandemic has accelerated digital transformation across all industries. Not surprisingly, businesses are turning to artificial intelligence, cloud computing, and the Internet of Things to optimize operations, reduce costs, and boost productivity. The results, as you remember, may depend on a company’s maturity, size, location, and area of expertise. However, 73% of enterprises that continue experimenting with artificial intelligence after initial failure register sizeable returns on their AI investments.
