"Hey Siri, how can my business use AI?"

Despite what we see in movies or on TV, the artificial intelligence (AI) of today has a long way to go. According to a White House report on artificial intelligence, we probably won’t see machines that can exhibit intelligence comparable or exceeding that of humans, but that AI will be able to reach and exceed human performance on more and more tasks. Then again, I did say probably… In this article, we’ll dive into what AI is, how it works, and how it can be applied – realistically – today.

What is AI:

Artificial intelligence is a software that uses and analyzes data, algorithms and programming to complete tasks, anticipate problems, and learn to adapt to a variety of circumstances with or without supervision. There are multiple types of AI, of which we’ll expand upon in a future article. For our purposes, it’s important to know that there are four subcategories of AI: weak AI, strong AI, specialized AI, and general AI.  These classifications depend on how AI is being applied.

Weak AI is designed to be seen as a representation of human thought or interaction, ex. Siri, or chatbots but is composed of a set of programmed responses and supervised interactions.

Strong AI is more unsupervised than weak AI and uses clustered or association data to “teach itself” and anticipate user needs to run tasks.

Specialized AI is programmed for specific tasks, and only can manage one task at a time.

General AI is not limited to one task like specialized AI, and it is able to learn multiple tasks and functions. General AI consists of machine and deep learning.

AI has advanced rapidly, a change that can be attributed to three major factors: the access to big data, improvements in machine learning algorithms, and greater computing power and the increase in cloud-based services. Therefore, as our technology improves, our ability to expand AI improves as well.

Uses of AI:

Despite what we’ve seen in sci-fi movies, there are many everyday uses of AI that don’t involve piloting a spaceship. However, transportation, like self-driving cars or services like Uber or Lyft, is one of the more well-known modern applications of AI. AI’s use in the field extends beyond that, and is used to collect data from many sources to optimize and adjust shipping routes for trucks, or simplifying a company’s distribution network.

In healthcare, AI is on the rise. Currently, AI is used to collect general patient data, or conducting more in-depth patient data research to find cures for disease like Parkinson’s or understanding how to manage asthma. Additionally, AI is even assisting in procedures like administering anesthesia or aiding during medical procedures. In the entertainment industry, be it by services like Netflix or Amazon, AI plays a prominent role in their central operations and their consumer draws. Machine learning algorithms are able to analyze user activity and compare it to others’ to find new products users would like, and are intelligent enough to recognize when to use a product as a gift or differentiate between different user preferences on one account.

Some industries, like finance or business, have already integrated AI into their business models. In finance, AI is used to manage investments, anticipate changes in the stock market with predictive analytics, and AI-powered robots can be used to trade, or track account activity to help financial advisors customize their services. In terms of gathering data, companies can use AI-based natural language processing tools to pull data from social media and collect financial data. In the financial sector, AI can cut costs and save time. In business, AI is notably used in customer service, by 24/7 chatbots, to automate processes and transfer data, resolve billing issues and update records as needed, running predictive analytics for consumer preferences, and to protect against fraud and manage other security measures. Both industries use AI-powered programs for fraud detection.

In manufacturing, the concept of “cobots”, which are robots that cooperate and work with humans in factories are slowly being trialed and introduced in the hopes of making the physical manufacturing process cheaper and safer. Additionally, AI algorithms can streamline supply chain by detecting demand by geographic and socioeconomic segments of a region and predict market demand. This will allow manufacturers to produce more accurate inventories, cutting down on time wasted and unnecessary expenditures.

Integrating AI into Your Business

The first step to integrate AI into your business is to identify the problems that you want to solve with AI, and how you can add AI into your existing services or into your company infrastructure. It’s important to have this in mind before venturing into the world of AI – just because it exists doesn’t necessarily mean that your business model needs it. The specifics of how AI will affect your business vary by industry, so it’s important to account for that when think of AI.

Future advancements in IT will be driven by AI and its ability to manage and analyze data, which will ultimately lead to better business opportunities. However, to manage the massive amounts of data that stem from AI, businesses will need a strong understanding of data science, experts in AI, predictive modeling, data administration and other techniques in order to optimize their use of AI.

AI works best with good data that’s conditioned and conceptualized, which allows the AI to make decisions, learn and take the appropriate actions. Therefore data and data storage should be a huge consideration in your AI plan. AI consumes a lot of data and needs a lot of place to do so, so look into different data warehousing solutions.

To make the change to AI seamless, incorporate AI in ways that will make daily tasks easier, not harder. Echoing past sentiments, make sure to make sure AI fits your business’ needs and can be a force for good for your employees.

Trends & AI:

1)     Organizational Problems? Solved! Once AI software is programmed, the learning capabilities of AI can be used to analyze and process information that data management professionals were once obligated to do manually, which allows organizations to solve problems faster and allows those vital employees to focus on other tasks.

2)     Real-time streaming will become much more common and companies will be able to process data in real time to understand what’s happening right now. Organizations that want to lead the field will have powerful databases that can process large quantities of data sets quickly.

3)     Natural Language Generation where text can be produced from computer data, which can be applied to customer service, report generation, and summarizing business intelligence insights.

4)     Speech Recognition where human speech can be transformed and transcribed into formats that can be processed by computer applications.

5)     Machine Learning Platforms which provide algorithms, development and training toolkits, and can be deploy models into applications, processes and other technologies.

6)     AI-optimized Hardware which are specifically designed and architected to efficiently run AI computations.

7)     Decision Management engines can insert rules and logic into AI systems and be used for initial setup, training exercises, and ongoing maintenance and tuning.


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