Few terms are as widely discussed and poorly understood as artificial intelligence (AI). Over the last 60 years, AI has been subject to speculation—whether from market analysts or science-fiction authors. Now that the AI market has reached maturity, AI is continuously changing how we work with each other. For business leaders, knowing what AI is and how it elevates human performance is essential.

The days of limiting AI to playing chess and computer games are behind us. Today, people use AI in every facet of their daily lives, whether it’s powering smarter search results, real-time image recognition, or self-driving cars. Simultaneously, businesses are using AI for a wide variety of applications, from identifying employee skills gaps to detecting financial anomalies. Organizations that continue to rely on outdated and manual processes risk falling behind.

Forrester reports that the global AI software market will double from $33 billion in 2021, to $64 billion in 2025. The majority of that growth will come from business applications infused with AI.

In this article, we first define the term artificial intelligence and the different types of AI. We then outline the main business benefits that are motivating companies to adopt AI. Finally, we outline the importance of ethical AI, and how AI techniques will define the future of the global marketplace. As AI research continues to accelerate, so too will the competitive advantage of businesses that leverage AI.

Artificial intelligence is the ability for machines to perform tasks traditionally seen as requiring human intelligence.

What Is AI?

Artificial intelligence is the ability for machines to perform tasks traditionally seen as requiring human intelligence. These functions include solving problems, making decisions, and understanding language. As with any other major technological innovation, the goal of AI is to improve human lives and enhance productivity.

There are many popular terms related to AI, such as machine learning, natural language processing, and deep learning. Sometimes people use these terms interchangeably, particularly machine learning and artificial intelligence, but there are key differences. Here are some quick definitions of different AI technologies to help clarify the distinctions.

  • Machine learning (ML) is a subfield of AI intended to train machines to learn and adapt without direct instruction. Machine learning models rely on data and self-modifying methods to identify patterns and make predictions or generate content. Those ML models can then continuously refine themselves to generate stronger future outcomes. A notable example is chess computers, where AI systems now far outstrip human ability.
  • Natural language processing (NLP) is a form of machine learning focused on enabling machines to understand human language. That comprehension then facilitates computers to generate their own written and verbal outputs, often using large language models. This branch of computer science is critical for speech recognition, translation, and sentiment analysis. If you’ve ever interacted with a chatbot, you’ve seen NLP in action.
  • Deep learning is a type of machine learning that enables computers to model complex patterns within data sets. Inspired by the human brain, deep learning uses multiple layers of neural network processing to analyze large amounts of information. This is useful in empowering computer vision, the process by which machines decode visual imagery.

The Types of Artificial Intelligence

One of the most popular methods for classifying AI is to compare its functionality with human performance. While there are already numerous business applications for AI, this comparison shows the potential future scope for advancement. Early adopters will see major benefits further down the line as computing power continues to increase. The four main types of AI are:

  • Reactive: The oldest recognized form of AI, reactive AI can only respond to stimulus based on its existing programming. As such, it lacks the ability to store memories and learn from experience.
  • Limited memory: Building on reactive AI, limited memory AI can learn from historical data to perform specific tasks. The majority of modern AI falls into this category, sometimes referred to as weak AI.
  • Theory of mind: The next proposed evolution for AI, often referred to as strong AI. Theory of mind AI will be able to understand human needs and emotions and adjust responses accordingly. At this point, AI will perform tasks and make decisions with the same aptitude as humans.
  • Self-aware: The speculative final stage of AI development, as frequently seen in science fiction. Self-aware AI would mirror the ability of the human mind to perceive itself. Rather than responding solely to human emotions, it would have emotions, thoughts, and feelings of its own.

How AI Impacts Enterprise Organizations

As we look ahead to future AI developments, it’s critical that businesses recognise the massive changes that have already occurred in the global workplace. HR has shifted to a skills-based economy. Finance has embraced touchless transactions. And IT must now manage tools for a distributed workforce while keeping up with emerging laws and compliance guidelines.

In each instance, AI enables businesses to better address past, present, and future change.

In the Workday report “AI IQ: Insights on Artificial Intelligence in the Enterprise,” 1,000 senior decision-makers were surveyed about artificial intelligence. Of those leaders, 99% stated that they believed there were clear benefits to investing in AI and ML. But what functions should companies be looking to support with artificial intelligence?

Here's a breakdown of six key areas where AI is already supporting organizations:

  • Automating manual and predictable financial transactions and processes
  • Scheduling workers based on availability and skills and predicting hiring needs accordingly
  • Analyzing employee comments and feedback to identify themes and sentiment
  • Identifying relevant skills from candidates and existing employees quickly and easily
  • Scanning expense receipts and invoices to process large amounts of data
  • Identifying anomalies in the general ledger for quarter close

For each of the above areas, AI automates manual processes to assist employees and drive efficiencies. Rather than removing human input, the future of AI relies on humans and machines working in partnership. In this method, AI provides data and recommendations, while humans remain in control of the major strategy and decisions. This human-machine collaboration is known as the  “human-in-the-loop” approach, and is critical for the long-term success of AI.

According to Workday research, 94% of enterprise companies are investing in AI technology.

What Are the Benefits of AI?

With AI becoming the market standard across industries, it’s important to understand the reasons driving its adoption. According to Workday research, 94% of enterprise companies are investing in AI technology. The question is, why are employers dedicating so many resources to AI?

At this point, the benefits of AI are far from speculative. PwC found that 54% of executives stated that AI solutions had already increased productivity in their business. By automating tedious and repetitive work, you allow employees to prioritize larger-scale problems across the business. PwC further predicted a 26% boost in gross domestic product for local economies from AI by 2030.

In its “State of AI in the Enterprise” report, Deloitte identifies companies with a high level of AI deployment and strategy as “transformers.” Within this group, respondents report positive impacts across company culture:

  • 56% report significantly improving collaboration across business functions
  • 45% “strongly agree” that their employees believe AI technologies will enhance their performance and job satisfaction
  • 44% “strongly agree” that their organizations actively work to nurture, train, and retain AI-skilled professionals

The Importance of Responsible AI

When Alan Turing proposed the “imitation game” in 1950, the goal was to evaluate the power of artificial intelligences. Later renamed the Turing test, the imitation game was designed to assess whether a computer could demonstrate human-like intelligence. However, Turing didn’t account for whether or not someone created that AI responsibly.

The recent explosion of interest in generative AI has brought the debate surrounding responsible AI to the fore. With consumer AI now writing academic essays, creating fake images of public figures, and mimicking musician’s vocal styles, a major question mark hangs over the trustworthiness of AI technology.

In the 2024 Global Study “Closing the AI Trust Gap,” Workday surveyed 1,375 business leaders and 4,000 employees worldwide. Results indicated that 70% of business leaders and 66% of employees believed that AI should be developed and used in such a way that easily allows for human review and intervention. That need for transparency and accountability are major factors guiding Workday AI development.

AI is still a nascent marketplace, and, as with any new development, it’s important to put safeguards in place. At Workday, our commitment to responsible AI directly reflects our core values, focusing on our employees, customer service, innovation, and integrity. In doing so, we aspire to achieve the following goals:

  • Amplify human potential
  • Positively impact society
  • Champion transparency and fairness
  • Deliver on our commitment to data privacy and protection

PwC found that 54% of executives stated that AI solutions had already increased productivity in their businesses.

What AI Means for the Future of Work

As businesses look to the future of AI, the decisions made now will define each company’s future success. Those that succeed will have AI embedded natively into the foundation of their products, ensuring they evolve together organically. Here’s how AI is already impacting the future of work across HR, IT, and finance:

  • HR: Any approach to managing talent that doesn’t take advantage of AI will be limited. Without AI, businesses lack a comprehensive view of their organization, forcing managers to deal with significant skills gaps, and leaving employees with unclear career paths. AI surfaces critical skills insights in real time, which helps managers with their talent strategy, and generates personalized employee growth plans, helping to increase talent retention.
  • IT: As businesses continue to expand, IT infrastructure needs to evolve with them. Businesses should not view AI as just another add-on; rather, they should pinpoint areas where AI can offer the highest value. Selecting products with embedded AI avoids the need to navigate poor integrations, connects previously siloed systems, and provides a major impact on organizational efficiency and productivity.
  • Finance: The future of finance is fully digital and intelligently automated, rendering mundane tasks obsolete. AI will empower businesses to process high-volume transactions faster with increased precision and greater accuracy. By identifying anomalies quicker, and providing financial professionals with accurately summarized data, AI has a major measurable impact in closing the financial books faster.

With more than 65 million users on the same version of Workday, only our customers have the trusted HR and finance data necessary to realize the potential of AI. For more information on how Workday can support you in the new world of work, read about our innovations with AI.

More Reading