The Role of Artificial Intelligence in Business Processes

The corporate world is witnessing the dawn of a new era in business and technology that’s on par with the rise of the Industrial Revolution and the digital age.¹ Looking into the future, it’s clear that adopting and understanding artificial intelligence (AI) is critical for organizations seeking to prosper.²

Whether small or large, a business can use AI to find its competitive edge.³

In this post, we’ll examine how artificial intelligence can be applied to business processes and how organizations use it to boost competitive advantage. We’ll also explain common hurdles in implementing AI and how Milwaukee School of Engineering (MSOE) can position you to contribute to your field using AI.

What is Artificial Intelligence in Business?

Artificial intelligence (AI) in business is when you use computer-based operating systems that can mimic human activities to support employees in their roles.⁴ Unlike traditional software solutions that follow a predefined set of instructions to execute tasks, AI uses algorithms to perform tasks that typically require human intelligence.

Key AI Technologies

AI is increasingly becoming critical in business, with AI tools and use cases popping up across multiple industries. However, AI’s most prevalent applications in business involve:

• Machine learning: Technology that enables computers to learn in ways that are similar to humans⁵
• Natural language processing: AI models that allow computers to comprehend and generate human language⁶
• Computer vision: Tools that empower computers to interpret and analyze visual information from the world and execute tasks such as object detection and image recognition⁷
• Robotic process automation: AI models that automate repetitive tasks by mimicking human actions within software applications⁸
• Deep learning: Technology that uses neural networks to simulate human brain functions to allow AI to handle complex tasks⁹

The Importance of AI Technology in Modern Business Processes

Businesses are already using different AI technologies in three ways:

• Enhancing productivity
• Reducing costs 
• Improving decision-making

Enhancing Productivity

Organizations use AI to automate repetitive, mundane tasks to allow employees to focus on more complex, value-driven activities. This increases business output in less time, making organizations more efficient. A recent study by the National Bureau of Economic Research measured the impact of AI on productivity and found that customer support agents using generative AI to guide their conversation saw a nearly 14% increase in productivity.¹⁰

Reducing Costs

AI reduces the need for manual labor in repetitive tasks, which can cut down on payroll expenses. It also optimizes processes to mitigate human errors, which can lead to reduced resource wastage and more efficient material and energy utilization.

Improving Decision-Making

Around 25% of decisions organizations should make aren’t made because leaders and/or decision-makers lack the time, capacity and visibility into business processes to make the best decision at the right time.¹¹ With AI, business leaders can gain visibility into their processes, analyze data, collect useful information and assess complex data to make more informed decisions.

Examples of Artificial Intelligence in Business Applications

Today, AI and business are almost synonymous. Organizations are using AI to succeed in competitive business markets in various ways. But how is artificial intelligence used in business?

Customer Service Chatbots

Companies increasingly use AI-powered chatbots and virtual assistants to handle basic customer inquiries about their products and services.¹² When the issue is complex, the bots automatically escalate it to human agents, reducing the stress on support teams.

Predictive Analytics

AI-driven predictive analytics tools are becoming critical for organizations to analyze historical and real-time data. Predictive analytics allows companies to forecast trends, customer behaviors and potential risks.¹³

Automated Inventory Management

AI’s integration into inventory management has reshaped supply chain operations, improving efficiency and decision-making.¹⁴ Businesses are using AI in inventory management to:

• Forecast demand
• Automate order placement and reordering 
• Optimize stock by monitoring inventory levels, sales trends and other relevant data in real time 

Improving inventory management helps organizations meet customer demand and enhance customer satisfaction.

What Are the Ethical Concerns Surrounding AI?

While artificial intelligence for business is progressing rapidly, people are raising concerns about its use, accountability, ownership and long-term implications for humanity. In fact, the White House recently invested $140 million to guide the development of responsible AI.¹⁵

Here’s a highlight of the most pressing ethical issues surrounding AI.

Privacy, Security and Surveillance

How well AI performs hugely depends on the availability of large volumes of personal data. However, the increased use of personal data has raised concerns about how companies collect, store and use users’ data. Take, for example, China’s facial recognition technology, which the government uses for its extensive surveillance network. Critics are raising concerns that China is using it to repress a certain ethnic group.¹⁶

To address such concerns, an organization can prioritize human rights and privacy when implementing AI. A business can adopt robust safeguards to prevent unauthorized access and data breaches while minimizing surveillance.

Bias and Discrimination

AI systems can be trained with data that has societal biases leading to algorithms that perpetuate unfair or discriminatory outcomes in critical areas such as:

• Criminal justice
• Lending
• Resource allocation
• Hiring

Consider a company that uses an AI system to screen potential hires’ resumes. If the historical data used to train the AI system is gender- or race-biased, it will discriminate against candidates based on gender or race.

Overcoming Challenges in AI Adoption

Despite its considerable potential, many organizations struggle to adopt and integrate AI into their processes. However, the right strategies can help businesses overcome these hurdles.

Skill Gaps

Today, the demand for AI skills exceeds the supply, putting most human workers and organizations at a competitive disadvantage. To bridge the skill gap, a business can develop in-house training programs that equip the existing workforce to work with AI technologies.

Ensuring Data Quality

AI is as good as its training data. Inaccurate or inaccessible data can limit even the most advanced AI models. Organizations can implement strict data quality controls and invest in technologies that enhance data enrichment and cleaning to provide AI with the high-quality data needed to succeed.

Managing Ethical and Legal Considerations

AI presents unique ethical and legal challenges, including decision-making biases, methods of data collection, data security and privacy concerns. To combat these issues, companies can establish and adhere to strict AI ethics policies and ensure they comply with the relevant laws and regulations.

Innovate in the AI Era with a Next-Gen Online MBA from MSOE

When you’re looking to stay innovative in the AI era, getting an online MBA from MSOE can be the right next move. Our curriculum, particularly for the online MBA in Advanced Business Strategy Using AI and Analytics, will prepare you to lead as an AI-savvy business professional in your field.

The AI and analytics specialization prepares you to make data-driven decisions through courses in predictive analytics, data visualization and more. This specialization imparts the in-demand and often hard-to-find skills employers are looking for.

Ready to pursue a worthwhile MBA? Get started on your application today.