Grant funding is yet another area in which Artificial Intelligence (AI) is bringing about transformation. One particular use case is AI-powered bots – we’re not just talking about chatbots, but tools that can automate a wide range of business processes.   

These bots could replace traditional grant management processes, but it’s essential to weigh the pros and cons before replacing your existing processes.  

In this article, we delve into exactly how AI bots are used in grant management, their advantages, and potential issues to be aware of.  

What Are AI Bots?   

The term ’bot’ (short for robot) refers to computer programmes that automate tasks. Before AI, we saw bots in use through Robotic Process Automation (RPA), which is the term for when entire workflows are conducted by bots – workflows such as issuing payments, among other administrative tasks.  

With AI on the scene, bots can now handle more advanced tasks that require human-like reasoning, such as data analysis, making predictions, and classification tasks.   

Another development to look out for is hyperautomation – the integration of diverse technologies that automate complex enterprise processes.   

How Are AI Bots Used in Grant Management?  

Grant management involves many resource-intensive tasks, which highlights the appeal of offloading the job to AI. Below are a few examples.  

Application Assistance 

Through chatbots, AI can provide information and support about available grants, eligibility criteria, application deadlines, and required documentation. They can also answer frequently asked questions and guide applicants through the application process, offering real-time assistance and reducing the need for human intervention. In turn, this can lead to more accurate and comprehensive submissions.  

AI may also verify documents, check that all necessary information is included, and offer suggestions for improving the quality of applications.  

In addition, they may send automated notifications to applicants, informing them about the status of their applications and any updates or changes in the application process, keeping them informed and engaged throughout.  

Document Processing  

According to PwC, using AI to extract information from documents saves 30-40% of the time that would otherwise be allocated to this task.  

Grant admins will therefore save a lot of time that would have been spent extracting data from applicants’ supporting documents, reducing bottlenecks between the application and review stages.  

Automating Finance Processes 

There are many ways to automate finance operations. Automation helps accountants perform complex tasks in a much shorter time, including bookkeeping, expense management and financial planning and analysis. It can handle all the smaller tasks within these operations, such as invoice processing.  

Another use case is automating budget development and monitoring, efficiently preventing overspending. The software may track project expenses against the terms of the grant, automatically sending notifications of any discrepancies so that the appropriate action can be taken in a timely manner.  

Compliance Monitoring 

AI bots can assist in monitoring compliance with regulations. They can track progress, verify the proper use of funds, and alert grant managers to any potential issues. With this happening on a continual basis behind the scenes, grant managers can be assured that any potential issues will be flagged early on and quickly resolved.  

Data Collection and Analysis 

Keeping on top of the huge amount of data generated throughout the grant lifecycle is challenging.  

AI can aggregate and analyse large datasets and extract insights quickly and accurately, which is helpful in many ways. For example, it makes it easier to assess impact and improve resource allocation. In addition, bots can automatically provide data visualisations for easy digestibility.  

The Pros 

Using AI bots to automate grant management processes brings many key benefits:  

• Efficiency and speed: Bots process tasks accurately in a fraction of the time it would take a human. With the extensive processes, verification and data analysis involved in grant management, these accelerated processes are welcome.  
• Reduced human error: Within grant management, examples of human error could be application form errors, monitoring and reporting errors, and errors in allocating grant funds. AI bots, on the other hand, adhere to programmed rules without fail, reducing the likelihood of errors and non-compliance.  
• Cost savings: The reduction in labor costs, improved efficiency, and minimised errors can result in substantial financial benefits.  
• 24/7 availability: Bots can operate around the clock, ensuring that tasks are processed at any time, catering to urgent requests and stakeholders in different time zones.  
• Personalised communication: Chatbots engage in personalised communication with stakeholders based on the data stored about them from previous interactions. This allows organisations to provide a personalised service without paying support personnel. 

The Cons 

Despite the many benefits of using AI to automate business processes, there are a few important issues to be aware of, as outlined below.  

Lack of Human Judgment 

As helpful as it is to avoid human error, human judgement is required in certain scenarios. Grant management often involves complex decisions that require considering unique circumstances and making subjective judgments.  

While AI bots excel at following predefined rules, and while intelligent systems can reason for themselves, there are limits to their capabilities. As such, overreliance on AI may lead to decisions that overlook contextual factors or lack the required discernment.  

Academic Misconduct  

The Australian Research Council (ARC) was recently accused of using ChatGPT to assess and write feedback for research proposals. A few applicants accused reviewers of using the software to write feedback on their proposals and in one instance, even failed to delete the text from the “regenerate response” button from the ChatGPT interface.  

The federal research minister condemned the use of AI for such purposes and said that the ARC must implement measures to prevent their staff from doing it again.    

Research Professional News quoted one of the researchers saying that the response “reads like the assessment was written by someone who doesn’t understand the science and has just paraphrased the application,” and that using AI to generate responses for this purpose is “academic misconduct”.  

Of course, the organisation itself did not condone the use of ChatGPT and it was the fault of several employees. However, this incident highlights the importance of being diligent in how AI is used, and that it should be avoided if it may compromise the integrity of the review process.  

Bias Concerns 

AI systems can inadvertently perpetuate biases present in the data they are trained on, which could result in the unequal distribution of funds or discrimination against certain applicants.  

As mentioned above, it’s important to protect the integrity of the review process. While human judgement is of course necessary when making more involved decisions, some funders use AI to carry out the initial application checks. Careful monitoring and regular audits are essential to address potential bias at this stage.  

Flexigrant comes with a bias detection tool to help ensure the equitable distribution of funds.  

Loss of Personal Touch 

Grant management often involves communication and collaboration with applicants, reviewers, and other stakeholders. Replacing all human interaction with AI would lead to a loss of personal touch and thus, hinder effective relationship-building – something that can be crucial for successful grant programmes.  

Conclusion 

The integration of AI bots into grant management processes offers a range of benefits, including increased efficiency, reduced errors, and cost savings. While RPA automates a range of basic administrative tasks, AI-enabled bots can take on more advanced tasks such as data analysis and compliance monitoring.  

When implementing AI, it’s vital to approach the transition with careful consideration of the potential drawbacks, such as the lack of human judgment and the risk of bias.  

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