Artificial intelligence (AI) is a technology that enables computers to handle tasks that usually require human brainpower, such as analyzing data, making decisions and solving problems.1
With AI, companies can automate repetitive processes to save time. They can also improve decision-making through data-driven insights and boost growth by making their operations more efficient.1
The technology has numerous applications and multiple benefits. However, getting the most out of it can be challenging if you are unsure exactly where or how to implement AI in business.
Read on to discover the use cases of artificial intelligence in different industries, why organizations should adopt it and how to use AI in business development.
How Is AI Being Used in Business?
AI can power business tools and automate processes for nearly any industry. Sectors that are benefiting now from artificial intelligence include:
Financial Services
AI-powered fraud detection and prevention tools can distinguish between normal and unusual payment processes. That way, they can instantly spot suspicious financial transactions.2
Additionally, AI tools can analyze borrowers’ credit payment history to predict their likelihood of defaulting or repaying a debt. Banks and other lenders can use this information to make loan decisions quickly.3
Manufacturing
AI can sift through production data to forecast or locate real-time equipment failures. It can then suggest repair options, the necessary spare parts or the required adjustments to make the machine functional again.3 Manufacturers can also use AI-powered computer vision to inspect products for defects.4
Healthcare
Doctors can use artificial intelligence to analyze X-ray images when trying to diagnose breast diseases or lung cancer. AI technology can also be trained to develop treatment plans, identify bone fractures and categorize tumors.3
Retail
Retailers use AI tools to optimize inventory management by tracking real-time stock levels and accurately predicting demand. They also utilize the technology to analyze customer data (purchasing history, browsing behavior, etc.) and then use the insights to tailor product recommendations and boost sales.4, 5
In addition to industry applications, AI has use cases in specific business functions. In sales, for example, AI tools can analyze shifts in customer preferences and then utilize the insights to forecast consumer demand.5
Additionally, customer service teams can offer 24/7 support through AI chatbots that provide personalized assistance anytime.3
Why Corporations Should Leverage Artificial Intelligence
After answering the question, “How is AI being used in business?” next is to understand the benefits of AI adoption in business:1
- Automates manual, tedious, time-consuming processes: This frees up human teams to focus on more critical business activities and saves on costs
- Speeds up and streamlines operations: For instance, AI tools can process large volumes of data faster than humans. It can also identify hidden patterns that may not be readily visible to human analysts
- Reduces human error: By automating repetitive tasks, which are prone to errors when done manually, AI minimizes mistakes in business processes
- Round-the-clock availability: AI-powered tools don’t need sleep, breaks or other limitations related to humans. They can work after business hours
Organizations that learn how to use AI tools in business development enjoy the above benefits in the real world. Here are some case studies:
- When Vistra Corp used AI to automate the continuous heat rate monitoring—a previously manual task in their power plant—operations became 2% more efficient after just three months. Improved efficiency led to millions in annual cost savings6
- An AI chatbot helped ING Bank offer immediate, tailored and 24/7 assistance to 20% more customers in the first seven weeks of use7
How to Use AI for Corporates Effectively
Below is a step-by-step guide on how to use AI in business.8, 9
Step 1. Identify Business Needs and Opportunities
When figuring out how to use AI tools in business development, you need to take a step back and consider where the technology could positively impact your operations. To achieve that, you can:
- Check processes that could be automated
- Identify operations with bottlenecks
- Find out where you could improve decision-making with data-driven insights
The aim is to discover AI use cases that can provide real value to your business.
Step 2. Develop an AI Strategy
After identifying where AI tools can help, the next step is to create a plan with clear objectives. Whether it’s reducing costs, improving customer service, streamlining data entry and data management or boosting productivity through generative AI tools, having specific goals will guide your AI implementation.
You’ll also need to consider the information required to train AI. Ensuring the data is accurate and relevant to your objectives is key to building an effective strategy.
Step 3. Start the AI Integration in Business Processes
AI integration in business doesn’t necessarily mean building your own tools from scratch. There are plenty of ready-made artificial intelligence solutions you can incorporate into your operations.
When considering how to implement AI in business, choose the tools that match your needs regarding feature requirements, ease of use, data security and privacy. Additionally, pick solutions that seamlessly interconnect with your existing software solutions.
Step 4. Pilot AI Projects
Before officially implementing AI systems in all your operations, it’s a good idea to experiment with a small project first. This allows you to test how well the technology works before rolling it out throughout the organization.
Step 5. Scale AI Systems Across the Organization
You can implement artificial intelligence company-wide after successfully experimenting with AI tools and making any necessary adjustments.
For instance, when Vistra Corp was figuring out how to use AI for business development, it first tested the technology in one power plant. Once the company got positive outcomes from the small-scale deployment, it implemented artificial intelligence across 26 other plants.6
Overcoming Challenges in AI Implementation
Artificial intelligence in business can make processes more efficient. However, successfully implementing it comes with several challenges: 10, 11
- Lack of in-house skills to deploy AI systems: Organizations can work with third-party AI experts, invest in training or hire AI talent
- Data privacy and security concerns: When training AI models with business data, there’s a risk of exposing sensitive information, especially if you use third-party tools that are not hosted in on-premise data centers. Only use AI tools that comply with your industry’s data protection and security regulations for data entry and data management tasks
- Data quality issues, such as inconsistency, inaccuracy and incompleteness: Poor quality data leads to unreliable AI insights. Before feeding data into AI tools, businesses can pass it through data cleaning and preparation software
Learn How to Use AI Solutions in Business With an Online MBA
Pursuing an online MBA from the Milwaukee School of Engineering (MSOE) can help you understand how to leverage modern business technology, including artificial intelligence.
Our curriculum, particularly for the online MBA in Advanced Business Strategy Using AI and Analytics, equips you with in-demand skills so that you can level up your career and become an expert in your profession. You’ll graduate with the expertise you need to qualify for positions you wouldn’t otherwise be eligible for. That could mean moving from lower to upper-level roles with greater responsibilities and higher income potential.
Ready to pursue a worthwhile MBA? Get started on your application today.
- Retrieved on October 14, 2024, from cloud.google.com/learn/what-is-artificial-intelligence?hl=en
- Retrieved on October 14, 2024, from stripe.com/resources/more/how-machine-learning-works-for-payment-fraud-detection-and-prevention
- Retrieved on October 14, 2024, from ibm.com/think/topics/artificial-intelligence-business-use-cases
- Retrieved on October 14, 2024, from cloud.google.com/discover/ai-applications?hl=en
- Retrieved on October 14, 2024, from ibm.com/think/topics/predictive-ai
- Retrieved on October 14, 2024, from mckinsey.com/capabilities/mckinsey-digital/how-we-help-clients/an-ai-power-play-fueling-the-next-wave-of-innovation-in-the-energy-sector
- Retrieved on October 14, 2024, from mckinsey.com/industries/financial-services/how-we-help-clients/banking-on-innovation-how-ing-uses-generative-ai-to-put-people-first
- Retrieved on October 14, 2024, from upwork.com/resources/ai-implementation
- Retrieved on October 14, 2024, from techtarget.com/searchenterpriseai/tip/10-steps-to-achieve-AI-implementation-in-your-business
- Retrieved on October 14, 2024, from forbes.com/councils/theyec/2023/10/25/10-hurdles-companies-are-facing-when-implementing-ai-and-how-to-overcome-them/
- Retrieved on October 14, 2024, from forbes.com/sites/garydrenik/2023/08/15/data-quality-for-good-ai-outcomes/