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Analysts, compliance officers and academic researchers are using AI tools to make their research process more efficient and find new insights from large volumes of data.
In our latest blog, we look at some of the main ways AI is transforming research, and explain why a Responsible AI model is the best way to overcome the risks of the technology.
Research is a critical task for any organization seeking to make new discoveries, gain greater understanding of a topic, and identify risks and opportunities. Valuable insights can be found in a broad range of data sources such as news, legal, financial, ESG and company data, and much more. But the exponential rise in available data means it is no longer possible for analysts to manually search through all relevant sources themselves. Instead, organizations are using AI tools to rapidly surface insights and trends from large data sets.
AI tools have created new opportunities for organizations by transforming all kinds of research tasks across a range of industries, including:
As well as expanding the avenues of research that are possible, a major benefit of AI is simply to make existing research workflows more efficient. By rapidly screening high volumes of data and summarizing the most relevant results, AI streamlines complex tasks and saves time. 69% of professionals are already using generative AI to assist with daily (and often repetitive) tasks like due diligence, according to the LexisNexis Future of Work Report 2024.
Unsurprisingly, more and more organizations are bringing in AI tools to power their research. In 2024, an Oxford University survey of over 2,000 researchers across a wide range of disciplines found that 76% have already used AI to support their research. Machine translation and chatbots were the most common tools used. Of those researchers, 67% said AI has benefited them, and over a third cited the benefit of saving time for researchers.
MORE: The AI Checklist: 10 best practices to ensure AI meets your company’s needs
However, AI tools also have some significant risks which could affect researchers and undermine confidence in their findings. This is a serious problem because research forms the basis for critical decisions taken by organizations, companies and governments. Risks include:
The best way for companies to overcome these risks and exploit the opportunities of AI for research is to implement a comprehensive and strategic Responsible Business approach. The core idea of Responsible AI is that AI and the data powering it should be developed and deployed in a legally compliant and ethical way. Every AI initiative should be weighed against principles of Responsible Business before it is implemented. This model gives assurance to research analysts that AI is supporting their research with greater accuracy and full compliance with data protection and privacy standards.
Some companies have shared how they use Responsible AI methods to improve their research outcomes. For example:
MORE: 5 steps to developing an ethical approach to AI
Nexis+ AI is a new, AI-powered research platform that combines time-saving generative AI tools with our vast library of trusted sources. Nexis+ AI saves time on core research tasks like document analysis, article summarization, and report generation. It can help drive forward your capacity to summarize and report in a responsible way, drawing on LexisNexis®’ credibility as an established data provider for over 50 years.
Download our toolkit, including the ebook Responsible Business: An Ethical Approach to Maximizing the Value of AI, to learn more about the how your company can realize the potential of AI while staying ahead of evolving regulations.