Through their discoveries, User Researchers increase confidence and clarity for organisations. But knowledge is only as valuable as our ability to make use of it. It’s time to welcome the new age of knowledge management for research teams - one that’s powered by artificial intelligence.
Through their discoveries, User Researchers increase confidence and clarity – helping to drive better decisions, and fuel innovation and growth across an organisation. Yet knowledge is only as valuable as our ability to make use of it.
“We can’t answer all of the questions, all of the time” is what we hear so often from researchers trying to balance doing new and innovative research, with responding to organisational demands for insights.
The reality is that the demand for insight often outstrips our capacity to deliver it. And in the fast-moving world of user research, where knowledge acquired quickly becomes vast and varied, teams that aren’t able to efficiently query what’s been done before risk falling behind.
It’s time for a new way to search for insights, a new way to engage stakeholders, and a new way to track and understand the return on investment for research. It’s time to welcome the new age of knowledge management for research teams - one that’s powered by AI.
“Every UX professional urgently needs to learn how to use AI in his or her work to avoid obsolescence next year.” Jakob Nielsen
So many valuable insights are documented in research reports, used once and thrown away, often ending up locked away in a shared drive, with no repeatable value. It’s an industry-wide problem, and a huge challenge for research teams.
When insights get trapped in research reports and artefacts, they start depreciating in value. To further compound this, without good insight visibility, researchers will always be at risk of losing time and wasting effort, either through searching for historical insights, responding to stakeholder requests, or repeating previous research. This is all time that could be spent actually doing new research, making better recommendations, and adding more value to the business and its customers.
Until now, the best solution in a researcher’s arsenal to respond to demands for insight was to trawl through previous docs and slide decks, wade deep through their analysis tools, or spend hours, if not days, attempting to navigate the company shared drive.
But in today’s fast-paced product world, people need (and expect) immediate information. Your teammates and stakeholders can’t wait days, or even hours, for an answer to a critical question - because inaction costs opportunity, and sometimes this costs more to the business than the occasional risky decision not backed by research.
This is not a new challenge. It’s one that research teams have faced for many years, and continue to battle against today - but how can researchers continue to provide value in an “I need this right now” world, when the very nature of research requires as much thoroughness and certainty as possible?
The answer lies in unlocking the very insights researchers have worked so hard to discover and making these more immediately accessible and reusable for the entire organisation. In other words, supercharging the knowledge retrieval process, and consequently supercharging decision making, innovation and growth.
And with the support of AI, the world of knowledge management for researchers has never looked more promising.
Data and knowledge management has been highlighted as one of the eight pillars of user research by Emma Boulton, and also talked about more recently by Emily DiLeo, as a way to create "a seat at the table" for research teams.
The integration of AI into the world of knowledge management and insights has immense potential to completely transform the way organisations utilise user research, and is set to streamline the research and decision making process across all research-driven industries.
Advancements in AI technology will also enable researchers and stakeholders alike to engage with research insights in an entirely new way, opening up the possibility to literally hold two-way conversations with your knowledge base.
Insight management platforms in 2024 will provide people with the superhuman ability to remember and retrieve absolutely everything that's been documented in your knowledge base, simply by asking it a question.
Researchers using AI to support their knowledge retrieval efforts will be able to instantly respond to those difficult questions within meetings, and use their newfound knowledge management capabilities to elevate themselves and their team as a strategic partner to product teams and leadership across the organisation, taking their research to new heights.
The promise of the delivery of insights at your fingertips, in a way that’s easy to consume, linked to the source, and trackable, will be key to realising this future state of knowledge management for user research.
“The execution of UX projects will undergo a transformation with AI tools... It's not AI that will snatch your job, but the individual leveraging AI to outpace your performance.”
Jakob Nielsen
One of the primary benefits of using AI to support your knowledge management efforts is the ability to search across thousands of documents and pages, using natural language, and receive an answer to your question in just a few seconds.
This takes us beyond simple keyword search, to help people find insights when they don’t know exactly what they’re looking for - a common use case for both researchers and stakeholders.
At Dualo we call this Q&A (Question & Answer), and the concept leverages generative AI and large language models (LLMs) to enable users to ask questions to their entire knowledge base and retrieve answers that are generated using their existing insights.
This frees users from exhausting manual searches for insights, and the time saved will enable teams to focus on more impactful work and strategic thinking – drastically shortening the decision-making process within organisations and also streamlining the product delivery lifecycle.
Generative AI can go beyond just providing answers. It’s able to allow anyone asking questions to your knowledge base to dive deep into the sources cited by your AI assistant.
The transparency provided by this technology ensures that users are able to understand the full context and origin of the information that’s provided in response to the questions asked.
Unlike research analysis tools that use AI to synthesise raw data or arrive at new insights, it’s like having a knowledgeable companion guiding you through what can feel like a labyrinth of insights that your company already holds, making your research request journey both more informative and enlightening.
Your researchers and stakeholders will also be able to ask further questions to any answer provided (think of this as a chatbot within your knowledge repository). And if your AI assistant isn’t able to work out a clear, well-sourced answer to your questions, it will let you know by telling you that it hasn’t found anything in response to your query.
Understanding the questions being asked about the insights discovered across an organisation will enable teams to not only improve the user research process, but start more effectively targeting individuals with highly personalised insights that are directly relevant to them and what they’re currently working on.
Imagine leveraging AI to unlock a full view of the questions being asked by both researchers and stakeholders, helping teams to understand exactly what information people are seeking to help them with their decision making.
This approach will help researchers to close the loop between requests for insights and how these insights are utilised across the organisation - enabling a better return on investment on research for both the team and the business, through being able to track the end-to-end lifecycle for research insights.
The ability to query your existing knowledge base for patterns, gaps, and opportunities is a game-changer for any research-driven organisation.
Researchers will be able to use AI to uncover previously unseen patterns in their synthesised research data, which will help them to shape a more effective and impactful research strategy. This will amplify the innovation that the team is able to deliver, without requiring any more effort or capacity.
Research is not just about gathering data; it's about translating data into actionable insights and recommendations, which can be used to drive innovation and growth.
AI will help researchers identify new opportunities and distribute these to the key decision makers across their organisation, at lightning speed - enabling teams to move towards product and business objectives with increased accuracy and pace, while elevating the research team in the process. Your new strategic superpower 💪
Security is paramount when it comes to handling sensitive research data. It’s why any AI Assistant needs to operate solely within your organisation's workspace. This ensures that the answers to your research questions are provided using only your data, and that no public AI models are trained using your organisation’s research.
So be sure to take a read of the terms and conditions of any AI-assisted tool that you’re considering to use to improve the knowledge management capabilities of your research team.
If you’re interested in how tools in the space are approaching the techy stuff while keeping security front of mind, you can read a copy of our Artificial Intelligence terms for Dualo here.
Using AI to enable your team to query an entire knowledge base shouldn’t be just a feature; it should act as a collaborative partner in your research journey.
Most generative AI tools allow users to provide real-time feedback for outputs provided, with a simple ‘thumbs up’ or ‘thumbs down’. This helps these tools to continue to fine-tune and enhance the conversational experience, alongside keeping your data private and secure.
This user-driven approach ensures the insight management tools of tomorrow will evolve to meet the ever-changing needs of researchers and their stakeholders, helping to make a tool like this an indispensable asset in your research arsenal.
So what types of questions might you ask to an AI-powered knowledge base?
Imagine you and your stakeholders, receiving answers to the following questions in seconds…
Show me all the insights we’ve discovered about <insert topic here>?
Do we have any research reports that cover <insert area of interest here>?
Which of our priority segments for 2024 have we acquired the most insight for?
What insights have been gathered by our <insert team here> in the last 6 months?
Which research methods have we utilised to capture insights as a team this year?
Are there any trends in our knowledge base that show how the needs of our users in <insert geography here> have evolved throughout 2023?
Can you help me to identify if there are any seasonal or cyclical patterns in the insights acquired by our research team?
What are the common usability issues reported by users for our <insert user journey here>?
Can you identify any demographic or geographic trends in user behaviour insight that may have been missed from what we’ve captured already in our knowledge base?
What are the key takeaways for our product strategy for <insert product here> when considering both UX research and market research findings together?
These questions are examples of what can be asked to a generative AI solution to help glean additional insights into your existing knowledge base, and support decision making across your organisation.
We expect to see AI assistants helping to answer questions like these becoming the norm for all insight management platforms as these tools evolve throughout 2024.
Dualo is a dedicated insights repository for researchers who want to maximise the visibility, accessibility, and impact of their research across the organisation. It's a knowledge base designed for research teams to centralise their key documents and combine qualitative and quantitative insights held across tools and projects.
The ability to query your knowledge base using natural language is set to become a transformative force for researchers looking to streamline the research and decision making process at their organisation, a real game changer, offering a groundbreaking solution to the challenges of information accessibility and stakeholder engagement. And it’s not as far away as you might think…
By seamlessly integrating AI into the existing Dualo platform, Dualo will empower researchers and stakeholders to retrieve valuable, synthesised insights in seconds - simply through asking a question.
The key benefits of this new AI-powered capability: rapid search and decision making capabilities, transparency in the origins of answers, and a holistic view of how research is requested and utilised across the organisation.
With security and user-driven evolution at its foundations, Dualo Q&A is not just a feature; it's a strategic ally in the ever-evolving journey of research, designed to help you maximise the impact of your research and elevate your insights and the team within your organisation.
We’re building a new way to engage with user research. No longer will researchers feel pressured to stay in their corner, instead they’ll take their place as strategic advisors to the entire organisation - providing access to invaluable insight that helps drive teams and businesses forward through innovation and growth.
We’re currently oversubscribed, but if this feels like a mission you can get behind, you can sign up for the Dualo Q&A beta waitlist and be amongst the first teams pioneering the future of knowledge management for user research 🚀
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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