Using AI to Maximize Business Potential: A Guide to Artificial Intelligence for Non-Technical Professionals

Categories: AI and MLTechnology

From virtual assistants like Siri and Alexa to self-driving cars and generative AI platforms like ChatGPT, artificial intelligence (AI) and its subset, machine learning (ML), are changing how we live, work, and play.

In the five years McKinsey has been tracking AI use worldwide, adoption has more than doubled, although its use in business organizations has held steady between 50-60% for the past few years. While the first-mover advantage has passed, there’s still plenty of opportunity to gain a competitive advantage by implementing AI to help your business be more agile, responsive, and innovative than others in your field.

If you’re still on the fence about adopting AI for your business or are searching for new ways various AI technologies could benefit your business, read on. In this post, you’ll find a comprehensive overview of what exactly AI is and why it matters, a timeline of AI milestones, the advantages and disadvantages of various AI technologies, and how it’s being used in different businesses today. 

What is Artificial Intelligence?

Artificial intelligence enables computers to simulate human thought processes and behavior, such as making decisions, solve problems, understanding language, recognizing images and faces, and more. Using constantly learning and adapting algorithms, AI systems can provide near-human accuracy and dramatically scale operations across many tasks and industries.

AI is one of our most significant technological advances, and its applications are becoming increasingly widespread. Businesses of all sizes are taking advantage of AI’s potential to improve customer service, increase efficiency and productivity, reduce costs, make better predictions about markets or customers, automate time-consuming and redundant tasks, analyze vast amounts of data, and develop new products and services faster than ever before. 

Recommended reading: AI’s Impact on Software Development: Where We Are & What Comes Next

In addition to being an effective tool for improving efficiency and productivity, intelligent systems can anticipate user needs and provide tailored solutions quickly and accurately by leveraging deep learning algorithms.

Additionally, AI can help organizations identify trends in data faster and more accurately. With access to large amounts of data from both inside and outside a company’s own network, AI can uncover insights that would otherwise remain undetected. This enables companies to make better decisions about allocating resources and gain a competitive edge in their industry. AI is fast becoming essential for any business looking to stay ahead of the competition.

A Brief History of AI Development

Artificial intelligence has come a long way since its inception in the 1950s. Some of the key dates in AI development include:

1956: The term “artificial intelligence” was coined by John McCarthy at the first AI conference at Dartmouth College.

1967: Frank Rosenblatt created the Mark 1 Perceptron, the first computer utilizing a neural network. It was able to quickly learn through continued experimentation. 

1980s: Symbolics Lisp machines are commercialized, and neutral networks using the backpropagation algorithm became common in AI applications.

1997: IBM’s Deep Blue defeated world chess champion Garry Kasparov.

2008: Google achieved significant advancements in speech recognition technology, which it incorporated into its iPhone application.

2011: Apple introduced Siri, a virtual assistant powered by artificial intelligence, to its iOS operating system.

2018: Google launched BERT, a natural language processing engine that made it easier for machine learning applications to translate and understand conversational queries.

2022: OpenAI released ChatGPT, a conversational AI that utilizes a large language model.

2023: Microsoft has recently released a new AI-powered version of its search engine Bing, which utilizes the same technology as ChatGPT. In response, Google has introduced its own conversational AI called Bard, creating competition in the market.

Thanks to advances in machine learning models such as deep neural networks and reinforcement learning algorithms, AI technology is constantly improving. These milestones in AI development demonstrate AI technology’s increasing sophistication and capabilities and its potential to revolutionize various industries.

Types of Artificial Intelligence

There are two main categories of artificial intelligence: narrow AI and strong AI. Narrow or weak AI focuses on specific tasks and can be used for language processing, facial recognition, and natural language understanding. On the other hand, strong AI or artificial general intelligence (AGI) has the potential to emulate human-level intelligence across a wide range of skills and tasks.

Weak AI (Narrow AI)

Weak AI, also known as narrow AI, is artificial intelligence that focuses on one specific set of tasks and is limited to the task for which it was designed. It cannot be applied to different problems. This makes it ideal for applications where speed and accuracy are essential, such as language processing, facial recognition, and natural language understanding.

One of the most significant advantages of weak AI is that it can quickly process large amounts of data while making fewer mistakes than humans. Businesses can use weak AI to automate mundane tasks or uncover insights from large datasets more accurately than manual labor. Additionally, weak AI can be trained rapidly due to its narrow scope.

Strong AI (Artificial General Intelligence)

Strong AI or Artificial General Intelligence is the next step in artificial intelligence. It refers to machines that can perform a specific task and possess a human-like level of understanding and reasoning. 

Unlike weak AI, strong AI has the potential to think for itself and solve complex problems without needing any kind of external programming or instruction. This means it can learn from its environment and even develop an understanding of its capabilities without human intervention.

Deep Learning vs. Machine Learning

Deep learning and machine learning have become increasingly popular in recent years as companies of all sizes seek to leverage the power of AI for their businesses. But what’s the difference between deep learning and machine learning? While both are branches of artificial intelligence that use algorithms to learn from data, there are essential differences between them.

Machine learning focuses on identifying patterns in data and using those patterns to make predictions or decisions. 

Deep learning takes this concept further by using layers of “neurons” to simulate how a human brain works and improve its ability to recognize patterns. This allows for much higher accuracy when making predictions or decisions based on data.

Deep learning is often used for tasks such as speech recognition and natural language processing, which require understanding complex relationships between words and concepts — something machine learning alone cannot do. 

Machine learning and deep learning each have unique advantages that make them useful for different applications. Companies should consider carefully which is best suited to their needs before investing in either technology. With the right guidance, companies can seamlessly integrate these AI capabilities.

Advantages of Using AI in Business

The advantages of using AI are numerous; here are some examples.

Personalization: AI can help businesses personalize customer interactions by analyzing customer data and tailoring marketing and sales efforts accordingly. This can lead to better customer experiences and increased customer loyalty.

Enhanced decision-making: AI can analyze vast amounts of data quickly and accurately, providing insights that can inform business decisions. This can lead to better decision-making and more informed strategies.

Cost savings: AI can help businesses save money by automating tasks and reducing the need for human intervention. For example, AI-powered chatbots can handle customer inquiries and support requests, reducing the need for human customer service representatives.

Improved efficiency: AI-powered systems can automate repetitive and time-consuming tasks, allowing employees to focus on higher-value tasks. This can lead to increased productivity and efficiency in the workplace.

Competitive advantage: Businesses that adopt AI early on can gain a competitive advantage over their peers by leveraging the technology to improve their operations, products, and services.

Predictive analytics: AI can be used to analyze historical data and identify patterns and trends. This can help businesses predict future outcomes and make more accurate forecasts.

Fraud detection: AI can detect fraudulent activities and transactions in real time. This can help businesses prevent financial losses and protect their reputation.

Improved customer service: AI-powered chatbots and virtual assistants can provide round-the-clock customer service, responding to inquiries and providing support at all hours.

Automation of complex tasks: AI can automate data analysis, financial modeling, and supply chain optimization tasks to save time and reduce errors.

Improved cybersecurity: AI can detect and respond to cyber threats in real time, helping businesses protect their data and infrastructure from cyber-attacks.

AI Disadvantages & Limitations

Despite the numerous benefits of artificial intelligence, there are also some potential drawbacks. One of the most prominent disadvantages is that AI systems require significant amounts of data to function correctly. This means that if a company does not have access to enough data, it may not reap AI’s full benefits.

AI-powered systems can sometimes make mistakes due to errors in programming or incorrect data input. This could lead to problems such as inaccurate customer service information or even security breaches if sensitive information is compromised due to an AI system’s mistake.

Overall, while AI offers numerous advantages for businesses, companies must consider the potential benefits and risks of using these systems before investing time and money into developing one. GlobalLogic can help you assess where to incorporate AI technology and help with the transition management.

How Businesses Use AI in Various Industries

Intelligent automations can augment and amplify the best of human performance, enabling a business to scale and grow at a rate that would otherwise be impossible. 

As Sanjeev Azad, Vice President of Technology here at GlobalLogic, shared with CXO Today recently, “Contact-center automation, customer segmentation & service analytics, business process automation and services optimization, predictive maintenance and remote assistance, risk modeling and analytics, and fraud detection and analytics are few businesses use cases where adoption of AI is playing a significant role.”

  • GlobalLogic Intelli-Insights helps companies in all industries activate the power of their data by providing pre-defined standard AI apps and custom app-building capabilities inside our AI-powered data analysis platform. This digital accelerator enables companies to quickly transform data into actionable insight without having niche data science skills in-house. 

Here are several more examples of how companies use AI to their advantage in different industries.

Finance

In finance, AI is used for fraud detection, risk assessment, regulatory compliance, investment strategy, and more. Anywhere data can be analyzed and used to make predictions and decisions, AI can help. 

You can read about a specific application of AI in fintech here. In this example, a well-trained machine learning model constantly analyzed market data and made appropriate portfolio adjustments to continuously improve performance.

AI is being used to help insurers identify and mitigate risks by analyzing data from various sources, including social media, weather reports, and satellite imagery. Using AI to analyze customer data and predict future needs or behavior can help banks offer personalized services and products. It works to detect fraud and prevent financial crimes, saving banks money, and can automate repetitive tasks such as data entry for companies in insurance, investments, fintech, cybersecurity, and more.

Healthcare

One of the most impactful ways AI is used in healthcare is in diagnostic imaging. AI algorithms can analyze CT scans, MRIs, and X-rays to process results faster and detect anomalies that may not be visible to the human eye. AI can help doctors diagnose diseases earlier and more effectively manage patient care by analyzing patient data to predict disease progression and identify potential complications.

AI is used to develop personalized patient treatment plans based on their medical histories and genetic makeup. It’s also valuable for creating new drugs and treatments, and analyzing clinical trial data to help researchers identify new treatments and therapies. 

Check out other ways AI is used in healthcare here:

Click to read How Digitization Is Changing Medtech, Life Sciences, and Healthcare

 

Media

AI is used in the media industry in various ways, from content creation and audience targeting to creating personalized news feeds and analyzing social media data to determine what topics are trending.

AI can be used for transcription, translation, and image and video analysis tasks. Major media and entertainment brands have used AI for video encoding, augmented reality projects, and analyzing and predicting consumer content.

Recommended reading: AI is the Future of Media

Retail

AI is used in the retail industry in various ways, such as personalized customer experience, inventory management, and supply chain optimization. For example, retailers use AI to gather data about their customer’s preferences and behaviors and then use that data to offer personalized product recommendations and promotions. AI-powered chatbots also provide customer service and support.

Additionally, AI optimizes inventory management by predicting demand and ensuring that the right products are available at the right time. AI is also used in supply chain optimization to improve logistics, reduce costs, and increase efficiency. Here is a case study of how AI was used to create a next-gen retail product that blends online and in-store shopping.

Manufacturing

AI is used in the manufacturing industry in several ways. One of the most common applications of AI in manufacturing is predictive maintenance. By using sensors and data analysis, AI can predict when a machine is likely to fail and schedule maintenance before it does. This can save companies money in unplanned downtime and repairs.

AI can also optimize production processes by analyzing data on everything from raw materials to energy consumption to identify opportunities for improvement. Additionally, AI can improve quality control by analyzing data from sensors and cameras to identify product defects and anomalies as they are manufactured. 

Today’s business landscape is changing rapidly, and those that can take advantage of AI have the edge over their competitors. By leveraging AI’s power, businesses can better understand their customers and increase productivity while reducing costs and creating new efficiencies.

Final Thoughts 

Artificial intelligence is a potent tool for businesses of all sizes. AI can help streamline processes, improve efficiency, and save time and money. Additionally, AI can provide real-time insights into customer and user behavior to inform marketing campaigns or product development. 

Businesses need to take advantage of these benefits to remain profitable in the long run. While a wide variety of AI applications are available, it’s essential to thoroughly assess each before deciding which suits your company. Training employees on how to use these tools effectively to get the most out of them is also critical to the success of each AI implementation.

GlobalLogic developed our AI/ML Center of Excellence to help customers make informed decisions about and implement AI to increase business efficiency, continuity, and profitability. The best practices, tools, and proven processes available via our CoE are based on our extensive experience helping customers transform their businesses with AI-powered solutions and developing AI products.  

 

Get in touch today and see how we can put this experience and expertise to work for you.

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A woman with dark hair and a white sweater sits at a desk in a brightly lit office reviewing data displayed on her dual monitors, in this image representative of how AI is used in business.

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Kimberely Livingston

VP, Marketing

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