10 Use Cases for AI in Business Today

10 Use Cases for AI in Business Today

With the ability to quickly analyze massive amounts of data, businesses can increase customer interactions and drive workflow-process efficiencies.

From voice-enabled assistants to facial recognition, proactive listening and virtual reality, the artificial intelligence sector is booming. According to Tractia, a market intelligence firm that focuses on human interaction with technology, annual worldwide artificial intelligence revenue will grow from $3.2 billion in 2016 to $89.8 billion by 2025

Artificial intelligence (AI) devices utilize machine learning algorithms, which are given sets of data. The devices are then asked to use that data to answer questions. As an example, if you provide a computer with photographs, some of which say, <this is a cat> and some that say, <this is not a cat>, you can then show the computer a series of new photos, and it will begin to identify which photos are cats.

Related: How AI Will Improve Health Care In The Next 20 Years

Machine learning then continues to add to the original teaching set. Every photo that the computer identifies—correctly or incorrectly—is added. The program effectively grows smarter at completing its task over time.

10 Widespread AI Use Cases

Many technology experts emphasize that AI capabilities are not yet ready to match human skills. The primary use-cases for 2018 will involve helping organizations make decisions on massive amounts of data.

Here are a 10 use cases of where AI is poised to play a key role in the business world today:

  1. IT Security: AI can analyze millions of files and identify which ones contain malware. AI can also look for end-user patterns in how data in the cloud is accessed to report anomalies and predict security breaches.
  2. Financial Trading: Based on historical trends, AI can predict when to buy and sell securities and then execute trades at high speeds and high volume so investors can lock-in their preferred buying and selling prices.
  3. Healthcare: Machine learning algorithms can process more information and spot more patterns to understand risk factors for diseases in large populations.
  4. Insurance: Firms can anticipate customer needs by identifying life events and predicting how those events impact insurance needs.
  5. Marketing: This area of AI is already well-developed and will continue to expand. Businesses can deliver personalized digital ads, email, direct mail and coupons—based on end-user Internet activity.
  6. Fraud Detection: AI can spot potential fraud cases across many different fields of online credit card transactions. The technology compares millions of transactions and distinguishes between legitimate and fraudulent activity.
  7. Personal Assistants: Google, Amazon and Apple personal assistants are already popular in the home. Conversational interfaces will also become increasingly common when interacting with technology in a business environment as voice-enabled interaction is added to on-screen dashboards.
  8. Customer Service: Machine learning algorithms with natural language processing can stand in for customer service agents, authenticate customers by their voice, and quickly route them to the information they need or a person.
  9. Legal: Natural language processing can also translate legalese into plain language for clients and help attorneys sort through large volumes of information to prepare for cases.
  10. Manufacturing: Wi-Fi and networked devices can capture data from the supply chain as well as product design, development, production, delivery and customer touch-points to build database insights that improve workflow-process efficiencies.Enhance your IT career by learning how to automate with Python. Get started  with this free Python guide.

AI Success Requires a Clear Strategy

As the number data-management use cases continues to expand, many businesses are beginning to make serious investments into the development and integration of AI. The technology was somewhat over-hyped in 2017, but 2018 should see real progress towards achieving the potential that AI has to offer. The rapid robotization of human functions has already been perceptibly felt in automotive industry, and the growth rate of AI-based systems is predicted to jump from 8% in 2015 to 109% in 2025.

At the same time, it’s important to realize AI will not transform every business right away. While Amazon, Google, Apple, Facebook and the auto industry may make AI look easy, companies without deep technology experience and resources won’t immediately see the same results.

But in 2018, we will begin to see more real use-cases of the power of AI among smaller businesses. As more money pours into AI projects and as the speed of technological change continues to increase, many business leaders are bound to act on the potential for change with an increasingly-urgent priority. Losing out to the competition in leveraging AI for delivering value to customers can be a strong motivating factor!

As is the case with all new technologies, some AI projects will fail. In addition to the technology challenges, workforce buy-in and the ability to manage the data feeding into AI will heavily influence the level of success a business can achieve. The projects most likely to flourish are those backed by a clear strategy and targeted results tied directly to the bottom-line.

Comments are disabled in preview mode.
Loading animation