How AI and human collaboration transform research

Discover how AI and human expertise combine to perform high-quality research.

Research has always been critical for informed decision making, but the explosion of data and tighter deadlines have made the process increasingly challenging. With artificial intelligence (AI), you can make the process simple and quick by streamlining workflows, locating reliable sources faster and supporting high-quality outcomes.

In-depth research, also called “deep research,” involves analyzing vast datasets to generate useable insights. While essential for critical decisions, the traditional process can be time-consuming and labor-intensive. AI simplifies this by automating data collection, organizing information and identifying patterns. It also enhances data visualization, making findings more accessible with visuals such as graphs.

While AI can help with deep research, it cannot replace the essential human portion. Human researchers are essential for interpreting nuanced topics, validating accuracy and ensuring data is used ethically. The human mind is needed for critical thinking and narrative building around research and data.

The best way to use AI in research is by creating workflows that use AI tools with plenty of checking and oversight by subject matter experts. AI can be used for tasks like data gathering and visualization, while humans should be in charge of making decisions about framing and evaluating outputs. This ensures that AI-gathered data and generated insights are accurate, meaningful and aligned with research goals. Here’s an example.

What does AI research look like in practice?

Consider this scenario: you are tasked with conducting research for a bridge construction project. Using AI-powered databases, you analyze the properties, costs and sustainability of materials like steel and concrete, while predictive analytics assess their performance under environmental conditions. Generative design software helps you explore optimized bridge concepts, and natural language processing tools review and summarize local regulations to ensure compliance. To evaluate environmental impact, you use AI modeling to identify potential risks to ecosystems and suggest design adjustments to mitigate harm.

To ensure accuracy, you cross-reference data from multiple sources, such as academic journals and government reports, while consulting industry experts for additional insights. AI-driven alerts keep you updated on advancements like smart infrastructure technologies, which you incorporate into the project.

By collaborating with AI in this way, research can become more efficient and more accurate. AI excels in handling repetitive tasks so human researchers can focus on the portions that need human decision making. AI can be a very capable research assistant, but it remains just that. In all research projects, you are still the head researcher.

If you are interested in learning how to use AI to streamline your research projects, contact the AOE team. We have team members who are experienced in AI who would be happy to talk with you.