How is AI Really Being Used?

AI is an excellent fit for tasks that are high-volume, repetitive, and data-driven. In areas like predictive maintenance, anomaly detection, data extraction, and demand forecasting, AI systems can often operate with minimal human input. These applications benefit from AI’s ability to analyze large datasets quickly and consistently, making them ideal for automation in industries like manufacturing, logistics, and cybersecurity.

However, many use cases still require human involvement due to the complexity, ethical stakes, or need for contextual understanding. Fields like healthcare, customer service, financial trading, and autonomous vehicles benefit from AI’s speed and pattern recognition but rely on humans for nuanced judgment, decision-making, and oversight. Artificial intelligence can augment the work of professionals by flagging potential issues or offering recommendations, while humans provide the final validation or empathy where needed.

A Deeper Look: How People Are Using AI Today

A recent Harvard Business Review article, “How People Are Really Using Gen AI in 2025,” offered a detailed look at how everyday users are applying generative AI (Gen AI) tools like large language models (LLMs). The work was based on research that analyzed a wide range of Reddit and Quora threads, forums, and articles to capture the top 100 real-world Gen AI use cases of the past year.

One of the most significant trends this year is the rise of emotionally driven use cases. Therapy and companionship emerged as the number one application, highlighting AI’s growing role in mental health support. Two other newcomers to the top five were “organizing my life” and “finding purpose.” The article’s author noted that it underscores how users are turning to AI for help with introspection, productivity, and life planning. It represents a shift from task-based to emotionally resonant AI use. Essentially, more people are seeking not just functional help but also guidance, clarity, and emotional support.

While technical applications like enhanced learning, content generation, and coding assistance still rank highly, the dominant theme this year is “Personal and Professional Support.” Users are employing AI for everything from generating meal plans to writing appeal letters and creating travel itineraries.

Professionals are leveraging AI to improve productivity at work, as exemplified by Microsoft Copilot’s integration into the workplace and EY’s deployment of AI agents for tax tasks. Meanwhile, some of the softer use cases, such as boosting self-confidence or engaging in meaningful conversations, reveal a new depth in how people interact with these systems.

Despite this enthusiasm, the article also acknowledges a growing sophistication and skepticism among users. Concerns about over-reliance, data privacy, memory limitations, and political bias reflect a more nuanced understanding of AI’s benefits and drawbacks. Some users celebrate the efficiency and empowerment AI offers, while others worry about its implications for critical thinking, especially in education.

See also: Agentic AI Marks a Turning Point for Business – But Not Without Real-Time Dynamic Access to Business Data

A Look to the Future

Looking ahead, the article points out that the most anticipated evolution is agentic AI. AI agents are software programs that use artificial intelligence to autonomously perform focused tasks, learn from data, and interact with their environment without continuous human intervention.

Such agents have the potential to transform the way companies operate, driving efficiency, improving safety, and unlocking new business opportunities. Most importantly, AI agents can bring advanced capabilities, including real-time data analysis, predictive modeling, and autonomous decision-making, available to a much wider group of people in any organization. That, in turn, gives companies a way to harness the full potential of their data.

Perhaps the most interesting future application of artificial intelligence is the field of collaborative AI agents. Rather than operating as autonomous systems, they communicate and coordinate with each other to achieve shared or complementary goals. That ability to function as teams or networks rather than isolated systems could, in the near future, enable smarter decision-making, greater efficiency, and more resilient operations.