What is artificial intelligence (AI)?

The megatrend of artificial intelligence is, arguably, having more impact on businesses today than any other technology. But what is artificial intelligence (AI)? According to American computer scientist and one of its founding fathers, John McCarthy, artificial intelligence (AI) “…is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.”

The dictionary definition: AI is the capacity of a computer, robot, or other programmed mechanical device to perform operations and tasks analogous to learning and decision making in humans, such as speech recognition or question answering.

AI disruption is impacting every industry and business size with the promise of more productivity, revenue, and business growth. They’re benefitting from task automation, which can be help employees be more productive. It’s being used to improve customer service, cybersecurity, fraud management, supply chain operations, and more. They can even use it to write code or create website copy.

Let’s take a quick look at the history behind this phenomenon to better understand what AI’s evolution.

Can machines think? That is the question British computer scientist Alan Turing posed in his 1950 paper, “Computing Machinery and Intelligence.” He introduced the Turing Test as a way of assessing a machine’s ability to exhibit intelligent behavior on par with a human. From there, AI journey has been:

• 1956: The program Logic Theorist was presented at the Dartmouth Summer Research Project on Artificial Intelligence, hosted by John McCarthy and others. It mimicked how humans solved problems
• 1957-1974: As computers were designed to store more information, AI research and use grew.
• 1980s: AI algorithms and funding expanded.
• 1982-1990: Additional investments in AI furthered its research, but it became less of a focus for engineers and scientists as funding ceased.
• 1990s-2000s: Private exploration of AI helped it to meet milestones.
• 1997: IBMs Deep Blue defeated the reigning world chess champion and Dragon Systems released its speech recognition software on Windows.

Now, AI is everywhere. It’s your smartphone’s voice assistant and facial recognition technology. It’s the “algorithm” behind your social media feed. It’s the engine behind ChatGPT, which generates text, and Midjourney, which generates artwork. AI powers your email spam filter, your favorite search engine, and self-driving cars.

The Biden Administration is examining how AI can be used to predict new variants of the SARS CoV-2 virus to inform vaccine and drug development efforts and in climate change mitigation efforts. From businesses to governments across the globe, leaders are striving to better understand how AI works, its capabilities, and how it might play a role in improving safety, productivity, operations, and a host of other functions.

Artificial intelligence uses computers and machines to mimic human decision making and problem solving. AI systems ingest huge datasets, look for correlations and patterns, and make predictions about future states. The goal is to perform operations and tasks that would otherwise be done by a human.

AI has many subcategories. They include machine learning, deep learning, neural networks, natural language processing, natural language generation, computer vision, and more. Some stand on their own, while others work within other subcategories. Let’s take a look at each:

Machine learning: the ability of a computer to learn to perform tasks without being explicitly programmed. Instead, computers learn by analyzing large datasets. An example is facial recognition.

Deep learning: “Deep learning” and “machine learning” are sometimes used interchangeably, but deep learning is actually a subset of machine learning. While machine learning requires human intervention to process data, deep learning does not. Deep learning is comprised of neural networks (see below). Examples of deep learning include self-driving cars and ChatGPT.

Neural networks: Another subset of machine learning. Neural networks are designed to take a pattern of data and generalize from it, much as would the human brain, even if the data are “noisy” or incomplete. Neural networks, which can be hardware or software systems, improve their performance by trial and error. An example of a neural network is when an e-commerce site personalizes the customer’s shopping experience.

Natural language processing: (NLP): It’s a subset of AI. Machine learning and natural language processing have some overlap since NLP often requires machine learning to be used effectively. NLP enables computers to comprehend the written or spoken word. Smart assistants such as Siri, Alexa, and Cortana use NLP to recognize speech.

Natural language generation (NLG): the use of AI programming to produce written or spoken narratives from a data set. Smart assistants such as Siri, Alexa, and Cortana use NLG to generate their responses.

Computer vision: a robot analogue of human vision in which information about the environment is received by one or more video cameras and processed by computer. It’s used by robots to navigate, to automate production lines in a factory, etc.

AI and its subcategories are often intertwined. Whether you choose one subcategory or combine several, AI has the power to create a world of possibilities. Let’s see how it can benefit business.

AI has been around a while, but the broad, upfront adoption of it to solve business challenges is new. Potential benefits across all industries are vast. They include routine task automation, supply chain optimization, fraud detection in credit cards and insurance claims, and much more.

How can you use AI in your business? Here’s what some AI tools can help you do:

• Peer into the future. AI can help you predict potential equipment failure on the manufacturing floor, recommend products your customer is likely to purchase, or help manage stock levels.
• Provide a helping hand. Save your staff time by automating tasks such as claims processing, customer service interaction, and inventory tracking. Customer-service representatives can use AI chatbots to resolve customer requests. Manufacturers can use AI tools to flag problems on a production line, freeing up staff to solve larger problems.
• Share expertise. What if you could capture expert knowledge and provide it to others in a digestible format? Sales directors can use AI tools to re-create the successes of sales staff and share that knowledge with a global sales team.
• Gain a deeper understanding. What do your customers want, and why do they want it? AI can help answer that question. Regional retail directors can understand how competitor price changes, promotions, and customer service ratings affect sales. Fleet managers can get to the heart of why vehicles are consuming too much fuel.
  
• Simulate outcomes. AI enables simulations that allow testing of nearly all potential scenarios before decisions are made. Executives can see possible outcomes resulting from acquisition of suppliers. Event coordinators can analyze millions of scheduling possibilities to identify best choices to maximize participation.

Artificial intelligence is data intensive. It requires fast access and speedy transfer of data; in other words, a modernized network built with fiber connectivity and security. An outdated network (often built on copper) with slow speeds, high latency, or unreliable connectivity reduces processing times. What’s more, most AI applications need to provide real-time or near-real-time data. Reliable, secure, high-speed connectivity is a must.

Business fiber

Business fiber is the king of bandwidth. Fiber optic technology uses cables made of glass or plastic strands. This transmits light, which is faster, more efficient, and highly secure when compared to copper.

Since high-speed connectivity is a must for artificial intelligence, fiber fills the bill. Business fiber has upload speeds as fast as downloads up to 1Tbps. It has lower latency (as little as 7-13ms). It creates less signal loss over greater distances. You can easily upgrade speeds without expensive hardware upgrades.

In short, fiber can transmit more data, which makes it ideal for powering data-intensive AI.

Dedicated vs. shared internet access

Businesses typically use fiber as a dedicated access to avoid competing with other users for their bandwidth, but fiber may also be delivered as a shared access.

Dedicated internet access is an internet connection that is not shared with any other subscriber. Shared internet access, as the name suggests, is an internet connection where the bandwidth is shared among multiple subscribers.

When it comes to AI, dedicated internet access is the better choice:

• No data or speed throttling
• No unpredictable reliability
• Lower latency
• Symmetrical download and upload speeds

Want to know more about business internet connections? Learn about your options.

5G

5G technology is the fifth generation of wireless communication technology used in cellular networks. It’s designed to offer significant improvements in speed, latency, capacity, and network efficiency compared to its predecessor, 4G LTE. In fact, 5G can deliver up to 100 times higher bandwidth compared to 4G networks.

These higher data speeds and reduced latency help make artificial intelligence more powerful and efficient. 5G allows AI algorithms to be more accurate, which helps them learn and improve.

The combination of 5G and AI is creating new business opportunities. Together, they have the ability to handle a large amount of information in a short time frame—5G by transmitting this information at very high speeds and low latency, and AI by using efficient algorithms, reducing operational complexity.¹

The combination of AI and 5G is revolutionizing entire industries. Industrial manufacturing, automotive and transportation, and retail and wholesale trades are the three key markets that will be most impacted. But the combination of AI and 5G will also help boost the productivity of other industry sectors, including healthcare, media and entertainment, agriculture, government affairs, financial services, construction, and energy.²

Cloud connectivity

Migrating to the cloud can help organizations reap the full benefits of artificial intelligence.

Cloud computing enables AI applications and offers scalability, flexibility, and cost effectiveness. An AI cloud platform relies on cloud connectivity for AI to move data from machines and applications to the cloud.

Cloud providers such as Amazon Web Services (AWS), Google Cloud, IBM Cloud, and Microsoft Azure are now rolling out their own AI services. How do you choose the right cloud platform for AI? You’ll want to ask the following questions.

• Does the cloud platform have tools for specific AI tasks such as computer vision, natural language processing, speech recognition, or machine learning?
• What is the cloud platform’s scalability and reliability?
• Is the cloud platform secure and compliant?
• What kind of customer support does it have?
• Does the cloud platform fit your budget?

Whichever AI cloud platform you ultimately choose, know that the combination of AI plus cloud is like a superpower. They enhance each other, leading to efficient data management, cost benefits, and improved executive decisions.

AI has a symbiotic relationship with a variety of other technologies. Combining it with the Internet of Things (IoT) or SD-WAN can make both stronger.

Internet of Things (IoT)

The Internet of Things (IoT) is the network of devices, vehicles, appliances, and other objects equipped with computer chips and sensors that can collect and transmit data through the internet. IoT is concerned with how devices interact with each other.

Integrating Internet of Things and artificial intelligence can create many benefits. IoT devices can use AI algorithms to process and interpret data in real time, which enables accurate decision making. In industrial automation, for example, AI-powered IoT devices can monitor machine performance and, using predictive analytics, proactively detect issues beyond the scope of the device itself and anticipate possible failures. From that information, AI can be pre-directed to create an alert that maintenance is needed. AI-powered IoT devices play a role across industries—in smart healthcare, smart energy management, and the development of autonomous vehicles.

SD-WAN

Software Defined Wide Area Network (SD-WAN) moves network traffic management away from hardware and premises to software in the cloud. SD-WAN helps optimize costs and application performance. Its underlying technologies include direct internet access, wireless, broadband, and Ethernet. SD-WAN is the next step from multi-protocol label switching (MPLS), as it’s more efficient and environmentally sustainable since it doesn’t rely on hardware and integrates with the cloud. It’s more productive, as it can carry unlimited data. It’s also more secure and the routing is more flexible. All of these attributes make it the ideal companion to AI.

When paired with AI, SD-WAN can become even more robust. It can conduct real-time analysis of network traffic, looking for patterns and anomalies and help technicians speed resolution time. 

The AI revolution has begun in earnest. It has the power to transform just about every industry, but let’s look at a couple of use cases.

Manufacturing

Artificial intelligence is revolutionizing productivity, efficiency, and automation in manufacturing.

AI in manufacturing can enable continuous operations. For example, it can help factory floor personnel quickly identify a particular machine that’s operating outside of preferred boundaries. When this occurs, real-time adjustments can be made to prevent downtime.²

Factory floor personnel can use AI as a kind of maintenance companion. AI can digitize paper instruction manuals or provide step-by-step, real-time instructions based on the problem at hand.³

When it comes to defect detection and inspection, AI-enabled visual inspection can help human inspectors see issues that they may otherwise miss. In some cases, it can replace the need for on-site personnel. This can shorten inspection time and improve accuracy, reducing recalls and rework. This translates to significant cost savings.³

AI in manufacturing can also eliminate repetitive tasks, freeing up workers to be productive elsewhere.³

Transportation

The U.S. Dept of Transportation (U.S. DOT) is greatly interested in artificial intelligence for the transportation industry, including autonomous vehicles, intelligent traffic management, and predictive maintenance.

The U.S. DOT launched Data for Automated Vehicle Integration (DAVI) to identify, prioritize, monitor, and—where necessary—address data exchange needs for automated vehicles (AV) integration across the modes of transportation. Access to data is a critical enabler for the safe, efficient, and accessible integration of AVs into the transportation system. Lack of access to data could impede AV integration and delay their safe introduction.³

AI can be used to assist in reducing traffic congestion and making roadways safer. It can analyze real-time traffic data from cameras and IoT devices. This data enables AI to identify patterns to control traffic light systems. By having a comprehensive view of traffic activities, AI can help reduce safety risks and traffic accidents.

Predictive maintenance aims to optimize vehicle health, limit downtime and expense, and extend the life of the vehicle. Just like in manufacturing, AI can augment predictive maintenance through data generated by IoT devices and a vehicle’s maintenance history to alert the need for maintenance.

Artificial intelligence offers benefits across industries. While it’s powerful in its own right, when integrated with other technologies, AI can help business leaders be a powerful companion for their employees. It efficiently and effectively uses data to learn and advance operations faster, thereby improving overall efficiency and productivity with the added benefits of reducing maintenance and repair costs.

However, for AI to function, it needs a secure, reliable fiber network and cloud connectivity that can manage the load of data it generates and consumes.

AT&T Business provides the reliable, secure network to enable AI. We also offer products and solutions that help support it—IoT, 5G, and more. And our knowledge in industries enable us to help customers discover and activate use cases for AI.

See how ultra-fast, reliable fiber and 5G connectivity protected by built-in security give you a new level of confidence in the possibilities of your network. Let our experts work with you to solve your challenges and accelerate outcomes. Your business deserves the AT&T Business difference—a new standard for networking.

Learn more about AT&T Business networking solutions and business internet solutions or contact your AT&T Business representative to connect with an expert who knows business.

¹Malik Saadi, Dimitris Mavrakis, 5G and AI: The Foundations for the Next Societal and Business Leap (Oyster Bay, New York: ABI Research, 2020), page 4. https://www.hsdf.org/wp-content/uploads/2021/04/5g-and-ai-report.pdf

²Beth Stackpole, “For AI in manufacturing, start with data,” MIT Management Sloan School, June 28, 2023, https://mitsloan.mit.edu/ideas-made-to-matter/ai-manufacturing-start-data

³“Data for Automated Vehicle Integration (DAVI),” U.S. Department of Transportation, May 20, 2020, https://www.transportation.gov/av/data