Generative AI is having a transformative effect on academic work, but it is also reshaping the professional services and research management sectors that support it. Here Anna Aston discusses where AI can be useful for research management and the tools research managers can use in different areas of their work.

Research managers are navigating a rapidly changing landscape. There is growing pressure to improve efficiency, manage data sets, and boost productivity. While AI is often touted as the solution to these challenges, many research professionals don’t know where to begin. Here is your cheat sheet to thinking through where and how AI can help with research management workflows.

Why AI Matters in Research Management

Today, many employees already have access to AI tools like Microsoft Copilot or may even bring their own to work (a trend known as BYOAI). While ChatGPT might be widely used, many other tools cater to individual preferences and needs.

Broadly speaking, AI is particularly good a streamlining repetitive tasks and processes and thereby creating space for you to focus on more complex work. In this respect, AI offers opportunities for research managers in three key areas:

• Improved communication
• Data analysis and error detection
• Predictive modelling

First steps to AI integration

Curious about AI but not sure where to start? Consider the following:
Assess your needs: Identify which tasks are taking too much time or effort and can be handled by AI. AI is most effective when applied to routine, time-consuming tasks.

Start small: Pick one or two AI tools to experiment with. Tools like ChatGPT for writing assistance or Notion AI for task management can be great starting points.

Train your team: Help your team get comfortable with AI tools through basic training. The key is to make everyone aware of AI’s potential and how to use it effectively.

Evaluate and adapt: Regularly assess how AI is impacting your workflow. What is working? What isn’t? Adapt based on feedback and explore other AI applications as you grow more comfortable.

Identifying pain points AI can solve

Research managers and administrators juggle many responsibilities, many of which AI can help with.

Summarising and reformatting data: With the right prompts AI can significantly reduce the time you spend analysing documents. Instead of poring over a fifty page report, you could let AI give you a concise one-page overview. I have found tools like ChatGPT, ChatPDF, SciSpace, and Quillbot are well suited for this purpose.

Answering emails: Finding the right words for an email can often be a significant block to getting a project moving. AI can generate responses summarising contracts, milestone reports into a couple of easy-to-read sentences. Tools like ChatGPT, Grammarly, and Compose AI excel in automating and improving email responses.

Academic search: AI can assist in finding relevant research publications and browsing the web for useful information (hallucinations are real so remember to verify sources!). Tools like Perplexity AI, ResearchRabbit, Elicit, and Scite.ai are current leaders in AI for research discovery.
Marketing content creation: Whether it’s social media posts or event invitations, AI can generate audience-targeted messaging that resonates with different demographics. Jasper AI and Copy.ai are great for generating industry standard marketing content.

Creative content: Need a quick video or engaging presentation? AI can generate visuals, audio, and even entire presentations in a fraction of the time, without sacrificing quality. Tools like MidJourney, Gamma, and Suno AI make this possible.

Data analysis: Whether checking data accuracy, identifying entry errors, or predicting funding trends, tools like ChatGPT or Julius AI can help advance data analysis and reporting.

The human-AI partnership

AI isn’t here to take your job, but it can make it easier. While AI can automate many tasks, humans remain critical to ensure the quality and integrity of the work. The human role is to oversee and guide AI outputs, using them as tools for augmentation rather than replacement.

You can think of AI as a colleague, a smart one, who occasionally makes mistakes, but can help you handle mundane tasks while you focus on strategic decisions. Platforms like Zapier or Make can be used to help integrate AI tools (like ChatGPT) into your workflow, connecting them with other apps to create an efficient automated system. Still, you hold the final say and the responsibility for outcomes.

Addressing Common Concerns

Many research institutions haven’t fully embraced AI yet due to the lack of clear guidelines and policies. Concerns over GDPR compliance, bias detection, and data privacy make AI a tricky subject. But there is a positive trend: funding bodies like UKRI have developed a policy on ‘Use of GenAI in Application preparation and assessment’; the European Commission has published guidance on the responsible use of GenAI in research, and the Information Commissioner’s Office provides guidance on AI and data protection, offering a clearer path for institutions to follow.

Ongoing training will be essential as AI tools become as common as spreadsheets. Understanding how to use AI ethically and effectively will ensure that you are not only saving time but also safeguarding the integrity of your research and data.

AI can be a powerful ally for research management professionals, offering solutions to everyday pain points while opening new doors for productivity and innovation. Starting small, staying informed, and embracing AI tools will enable you to stay ahead in a rapidly evolving landscape.

AI isn’t the future, it is the present. So, what is your next move?

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Image Credit: Google DeepMind via Unsplash.