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With much debate around the application of AI in user research, we set out to establish how rather than replace researchers, these new technological capabilities are set to elevate research, while helping to make some of the more time consuming ‘research admin’ tasks a thing of the past.
In today's fast-paced world, research and knowledge sharing are critical for teams and organisations looking to drive innovation and growth.
Yet the abundance of information can often be overwhelming, making it challenging to locate and consume valuable insights efficiently. This is where Artificial Intelligence (AI) comes into play, which is revolutionising the way organisations leverage their existing knowledge.
With much debate around the application of AI in user research, we set out to establish how rather than replace researchers, these new technological capabilities are set to elevate research, while helping to make some of the more time consuming ‘research admin’ tasks a thing of the past.
So what’s AI set to revolutionise first when it comes to supercharging your research findings?
In this post we summarise the key findings from our recent conversations with research and design leaders around research and AI, and share some of the AI solutions being developed to streamline the research process.
The process of reading through lengthy research reports (both for researchers as part of a research review, or stakeholders searching for existing insights) can be an overwhelming and time-consuming experience, often leading to repeated research or the misuse of information.
AI-powered natural language processing (NLP) techniques can speed up this task by automatically summarising extensive research documents. By utilising algorithms that identify key concepts, extract salient information, and generate concise summaries, AI enables its users to quickly grasp the core findings and potential implications of a study.
This technology not only makes it easier to digest extensive research reports, but can also help to encourage wider engagement in research across an organisation - helping to build a shared understanding across teams, and surfacing new opportunities for collaboration.
Wordtune is a tool that teams can use to summarise lengthy PDFs and docs, with an add-in that can be used with Microsoft Word to summarise documentation, right where you work.
One of the key challenges in research is organising and categorising vast amounts of knowledge. Building a taxonomy for research, and how to make this valuable for non-researchers as well as researchers, has become a hot topic within the industry.
AI algorithms can assist researchers with building or refining taxonomies by suggesting tags for research reports, and the insights within these. By analysing content, context, and semantic relationships, AI models can identify and classify key concepts, methodologies, and topics, amongst a whole host of other predefined criteria unique to your organisation.
An AI-assisted approach to tagging enables researchers to build, test, and improve the quality of the research taxonomy, which can result in the discovery of new themes and connections across their research findings that may have otherwise gone unnoticed.
Bob DuCharme recently used ChatGPT to turn a flat vocabulary list into a hierarchical taxonomy. You can take a look at the output here.
Locating specific insights within a multitude of apps and reports can be a particularly laborious task, particularly given the recent explosion in research tools making it harder for teams to quickly build the bigger picture surrounding their customers, and their objectives.
AI-powered search algorithms, combined with advanced text mining techniques, can expedite the process of locating relevant insights. By understanding the context and intent of a search query, AI models can identify and extract specific information from research documents, such as key findings and recommendations – enabling researchers to unlock the most relevant and actionable data quickly.
This capability improves productivity for both researchers and stakeholders, enabling researchers to spend more time on analysis and less time searching through vast quantities of data. It also helps wider stakeholders to make more timely insight-driven decisions.
Camille Mathieu recently used ChatGPT to write a Python script for extracting text and metadata from PDFs, using just a few lines of code, with no formal development experience.
The ability to identify and group similar insights across multiple research projects is a core part of conducting any comprehensive literature review, which researchers can use to discover new patterns and themes in their existing knowledge base. But this takes time.
AI models equipped with clustering algorithms can automatically group related findings based on their similarities. By analysing the content, language patterns, and topic distributions, these models can identify common themes, emerging trends, and knowledge gaps within a specific domain.
Researchers can explore AI-generated clusters to help them develop a holistic understanding of an organisation’s knowledge base and identify potential areas for further investigation, as well as identify existing opportunities that might be hidden in their existing knowledge base.
Imagine being able to automate the process of consolidating all of the insights you already hold that support the advancement towards a specific customer, team, or business objective.
With the rise in adoption of generative AI solutions like ChatGPT, how we are able to interact with, and extract value from our data has dramatically evolved. As a result, more researchers are considering how they can use this technology to hold interactive conversations with their research documents.
By integrating natural language understanding and generation capabilities, AI models can engage in meaningful dialogues with researchers. Conversational AI will allow researchers, wider teammates and stakeholders alike to engage with research in an entirely new way. The ability to ask your knowledge base questions, seek clarifications, and explore research findings in a more interactive and intuitive manner will soon be a widely adopted reality.
Such technology fosters a dynamic and interactive approach to research, which will help researchers to query their knowledge base in a more natural and efficient way – helping teams to streamline research projects and decision making.
ChatPDF is a tool that allows people to chat with any PDF (or URL). All of your data is kept confidential in a secure cloud storage and can be deleted at any time.
The integration of AI into the world of synthesised research data has immense potential to transform the way we access, analyse, and utilise knowledge.
It’s important to note that AI will not replace the need for researchers, particularly when it comes to empathising with users and turning raw data into insight. But AI can absolutely provide useful ideas to help researchers maximise the impact and value of their insights, while streamlining the administrative side of research and knowledge sharing.
From summarising complex reports to engaging in conversations with our research documents, AI empowers researchers and stakeholders to navigate through, and better utilise vast amounts of information more efficiently.
And by leveraging AI technology, researchers can gain deeper insights into complex problems and unlock new opportunities for innovation.
As AI continues to advance, we can only expect to see the launch of even more sophisticated and powerful tools, capable of further augmenting and elevating our research capabilities – enabling us to push the boundaries of knowledge management, and significantly improve productivity across research-driven organisations.
At Dualo, we understand the value of leveraging existing knowledge to help teams improve their research process, which is why we’re releasing a roadmap full of AI features (like those mentioned in this post) throughout the rest of this year.
We're looking for more teams to help us with the design and development of our 'AI Assistant'. So if you’re excited by the idea of using an AI-powered knowledge repository and would like to help us to make this a reality, get in touch today.
I'm one of the Co-Founders of Dualo, passionate about research, design, product, and AI. Always open to chatting with others about these topics.
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