Application of AI in Business

by Mason School Online Programs Blog | August 20, 2024

Businesses are increasingly using AI applications to optimize their daily operations and drive their high-level strategy. AI capabilities such as machine learning, natural language processing, computer vision and large-dataset analysis allow these applications to mimic human intelligence and decision-making—or, in some cases, exceed them—at least in limited use cases.

This article will cover the application of artificial intelligence in business, including how it can lower costs and increase productivity while driving strategic decision-making.

Key Applications of AI in Business

According to the global consulting firm McKinsey & Co., artificial intelligence business applications extend to almost every industry. Some of the most widespread use cases include the following:

AI in Customer Service and Support

With high turnover rates and stress levels, customer service and support jobs can benefit from AI applications that can reduce volume and increase efficiency. Natural language processing allows AI customer service chatbots to interact with people using everyday language. AI applications can automate many routine support tasks, such as tracking orders or answering FAQs. These applications should supplement rather than replace human workers. They'll help businesses do more with fewer workers and free up human talent to focus on more complex or high-value tasks.

AI for Marketing and Sales

McKinsey estimates that AI applications in marketing and sales could reach a value of $2.6 trillion. AI-driven data analysis can uncover trends in customer data to make marketing campaigns that provide a hyper-personalized experience. These applications can provide seamless engagement allows customers to switch between multiple channels without losing their progress.

Businesses can also use AI to generate effective data-driven marketing strategies based on consumer behaviors and market trends. Additionally, by automating repetitive tasks, AI applications can increase marketing and sales teams' productivity.

AI in Supply Chains and Logistics

The supply chain is another sector that McKinsey highlighted as a major area of impact, with the value of AI applications expected to reach $2 trillion.

According to EY, an international professional services firm, 40% of supply chain organizations are investing in generative AI. Because they can interact using natural language, these applications make it simple for business leaders to ask questions that can inform their demand forecasting, product planning and risk management.

AI for Financial Services

The financial industry is one of the most highly regulated due to its critical and sensitive nature. AI business applications in finance are used to detect anomalies that could indicate fraud, money laundering, or cyber threats. AI advisors can provide personalized investment advice based on a customer's goals and risk tolerance. AI tools can also automate many aspects of compliance to increase productivity and reduce human errors.

AI in Human Resources

The research and advisory company Gartner is already seeing widespread AI adoption in HR and expects it to continue to grow as HR leaders use AI to perform time- and labor-intensive tasks while generating actionable insights. HR teams can use AI tools throughout the employee lifecycle. These tools can perform data analysis to determine the most effective recruiting channels. Once employees are hired, they can handle mundane onboarding tasks and provide personalized training plans. Through natural language processing, generative AI tools can also help create HR content.

AI for IT and Cybersecurity

Bad actors are already using AI technology to launch cyberattacks on a massive scale, but IT teams are using it to counter these threats and shore up their cyber defenses. AI tools can monitor network traffic to detect early signs of unauthorized access. They can also pre-emptively flag potential scam emails. AI-powered security tools can perform automated penetration testing to find weaknesses in an organization's system, and they can scan codebases to find security flaws before applications are deployed.

AI in Product Development

New product development can significantly impact a company's growth and long-term success, and AI can contribute by providing in-depth data analysis to achieve an optimal product-market fit.

Once a business establishes that there's strong demand for a product, AI applications can speed up iteration and reduce time to market. Instead of spending weeks on a prototype or mock-up, AI tools can create them in hours. They can also scan and then analyze data on customer sentiment from multiple sources for faster and more accurate feedback loops.