A key aim of developing high-quality AI tools and effective KM approaches is to increase evidence uptake. Technological advances can contribute to this by generating more accessible and timely insights, and by freeing up resources that can be channelled into dissemination activities. While the potential of AI in this area is significant, participants emphasised the continued importance of advocating for evidence use and building close relationships with decision makers.
“We’re doing all of this because we want evidence to be used”
Freeing up resources. The appropriate use of tailoredAI tools combined with effective KM has the potential to allow for significant efficiency gains throughout the research cycle. Participants highlighted that the time and money saved by employing AI technology effectively can be diverted to encouraging evidence use, with researcher capacity freed up to focus on disseminating findings more widely and building relationships with decision makers.
Supporting synthesis impact. Technological advances offer opportunities for researchers to synthesise evidence more efficiently. However, these technologies can also be harnessed to allow policymakers to understand and interact with the product of these efforts. Participants flagged the potential for AI tools to close the loop between evidence production and evidence uptake by increasing policymakers’ access to digestible information on what works.
Producing timely insight. Policy decisions often need to be made quickly, responding to rapidly changing situations in complex environments. There is usually limited time to access and consider all the available evidence. The ability to produce timely insights offers the opportunity for researchers and evidence brokers to help decision makers take an evidence-informed position, and robust KM offers the opportunity to base responsive insights on a more comprehensive and inclusive evidence base. AI tools were also seen as allowing researchers to anticipate the questions that evidence users might ask in advance, enabling the production of relevant insights ahead of time.
Shaping the demand side. The advantages of co-generating evidence alongside governments and policymakers were highlighted, with participants demonstrating that programme impact can be increased by several orders of magnitude when decision makers are involved in evidence production from the start. Participants positioned AI as enabling the development of processes and frameworks to help those on the demand side establish and communicate their requirements to evidence producers, and allowing researchers to provide robust insights that are tailored to those needs. AI and KM were also seen as having the potential to lead to behaviour change among both researchers and evidence users, enabling researchers to adopt a relationship-centric approach and focus on building trust and credibility and allowing policymakers to act as champions for evidence use.
Understanding evidence users. Despite technological advances in evidence synthesis, the challenge of ensuring that evidence is used effectively by policymakers remains significant. Participants agreed that practical steps should be taken to understand the needs of the end-user of synthesis products and AI tools, and how incentives can be formulated to ensure policymakers engage constructively with evidence.