Proposal WritingThe (AI) elephant in the (Grant Writing) room

It’s time to talk about Generative AI and Grant Writing.

In the evolving landscape of grant writing, the advent of generative AI presents both significant opportunities and points of contention. As institutions like the European Commission and other funding bodies receive an increasing number of proposals, the role of AI in assisting grant writers has become a topic of considerable interest and debate.

This article explores the potential benefits and concerns associated with the use of generative AI in the preparation of grant proposals. My conclusion is that while AI can enhance the efficiency and quality of proposal writing, the core determinants of success remain beyond the reach of any artificial assistant. So, AI in grant writing is a tremendous opportunity for all, but it is not game-changing.

Let’s have a look…

 

Opportunities for Grant Writers

At the most basic level, AI can handle time-consuming tasks such as formatting, grammar checking, and ensuring compliance with specific guidelines of funding bodies like Horizon Europe. These functionalities alone can save significant time and effort, allowing writers to focus on the more substantive aspects of proposal development.

Furthermore, AI can assist in the brainstorming phase by generating ideas and suggesting potential angles for a proposal based on vast datasets of previous successful applications. This can help grant writers identify innovative approaches and ensure their proposals stand out in a crowded field. AI-driven tools can also aid in conducting literature reviews, synthesizing research findings, and identifying relevant statistics, thereby enriching the content of proposals with data-driven insights.

These are only a few of the applications where we registered significant improvements when using AI in supporting the preparation of successful proposals.

 

Concerns of Donor Institutions

Despite these benefits, donor institutions express valid concerns about the use of generative AI in grant writing. One primary concern is the potential for homogenization of proposals. If many writers rely on similar AI tools, the distinctiveness and originality of individual proposals might diminish, making it harder for reviewers to distinguish truly innovative ideas from well-formulated but fundamentally similar applications.

Other understandable concerns include the accuracy, validity, and appropriateness of the content and any citations generated by the AI tool, as well as the risk of unintentional plagiarism, where the AI tool may have reproduced substantial text from other sources.

Finally, a significant concern is the ethical and integrity issues surrounding AI-generated content. There is a risk that the use of AI might lead to superficial compliance with guidelines, where proposals appear polished but lack genuine depth and feasibility. This could undermine the trust between grant applicants and funding bodies, potentially leading to stricter scrutiny and verification processes.

 

Balancing AI and Human Expertise

The key to leveraging AI in grant writing lies in finding a balance between technological assistance and human expertise. While AI can enhance the efficiency and preliminary quality of proposals, it cannot replace the nuanced understanding and strategic thinking required for successful grant applications. The ultimate success of a proposal depends on several critical factors that AI cannot influence:

  1. Quality and composition of the consortium: The selection of partners and their collaborative synergy play a crucial role in the success of a project. The strength and diversity of the consortium’s expertise cannot be determined by AI but requires human judgment and strategic alignment.
  2. Capacity of partner organizations: The ability of consortium members to implement the proposed research and their track record are essential. Evaluating these capacities requires insights into organizational culture, historical performance, and future potential.
  3. Soundness of the research methodology: Developing a robust and feasible research methodology relies heavily on human creativity, critical thinking, and domain-specific knowledge.
  4. Availability of background knowledge and IPRs: Understanding and using existing intellectual property and knowledge assets necessitate thorough human analysis and strategic planning.
  5. Strategic use of future results: Crafting a strategy to utilize project results to achieve desired outcomes and impacts requires foresight, strategic thinking, and alignment with broader societal and scientific goals.
  6. Distribution of resources: Allocating resources effectively within the consortium involves nuanced negotiations and understanding of each partner’s strengths and needs.
  7. Consistency and Logic of the Work Plan: Developing a coherent and logical work plan that aligns with the project’s objectives and deliverables is a complex task that requires human oversight and expertise.

Furthermore, when it comes to the EU-funded actions’ “Expected Impact,” AI is blind.

The expected impact depends completely on strategic decisions and approaches that the Beneficiaries will take to enable the achievement of the desired (expected) outcomes. Outcomes will depend on how each partner organization plans to use the project’s results and on the very specific “exploitation strategy” designed and implemented. This is something that AI cannot meaningfully provide for you.

AI cannot have (at least yet) the Beneficiary’s “Vision,” cannot define a “Strategy” tailored for a specific organization, and cannot replace human decisions. The impact, as an effect in the long run triggered by the achievement of outcomes, is influenced accordingly. Yes, we can read dozens of artificially generated pages on the project’s future impacts, but they will unavoidably be an appealing body without a soul.

All in all, generative AI undoubtedly represents a powerful tool that can assist grant writers in improving their efficiency and the preliminary quality of proposals. However, the success of an application is ultimately determined by factors that lie beyond the capabilities of AI.

The quality and composition of the consortium, the research and innovation capacity of partner organizations, the soundness of the proposed research methodology, the availability of background knowledge and IPRs, the strategic use of future results, the distribution of resources, and the consistency and logic of the work plan are all critical drivers of success that remain firmly in the hands of the human proposal writing team. Therefore, while AI can augment the grant writing process, it cannot substitute the depth of expertise, strategic vision, and collaborative synergy that human teams bring to the table.

PS: (… the preparation of this article was supported by AI, but you have already spotted where and how it contributed… 😊)

 

Marco Liviantoni

EU grants senior expert – Proposal Writing & Financial Management specialist

 

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