How to use AI in your job search and what mistakes to avoid

Development job seekers are increasingly turning to artificial intelligence to support their job applications, with more and more tools promising to save time and increase their chances of success. In a recent Devex digital event, Luan Prinsloo, global talent acquisition manager at World Vision, said AI use in job applications has changed dramatically. When used efficiently, there are advantages to using these tools, she explained, but there are caveats. “The industry has gone through such a shake-up since the beginning of this year, and so we are seeing an influx of great talent in the market, which is a good thing for organizations who are hiring,” Prinsloo said. “But it also means that candidates and job seekers have to do a little bit more to make themselves stand out right in the market.” Examples of where AI tools can help them to do so include identifying the key requirements of a role, crafting posts for sites such as LinkedIn to “elevate [their] voice,” or practicing mock interviews. But where AI becomes a “red flag is when we see exaggerated skills or experiences … generic buzz words or keywords … or applications that are not personalized,” Prinsloo said. During the event, she also noted that where candidates rely too much on AI in crafting their CV or cover letter, recruiters can end up receiving several almost identical applications. And, while World Vision, like many organizations, does use an applicant tracking system, its screening process still involves a human element, said Prinsloo, and this is helpful for candidates who take a “hybrid approach” to using AI in their application. During the event, she discussed some of the best ways for job seekers to do this and what mistakes they should avoid. Identifying key skills AI tools, such as Chat GPT, can help job seekers with their initial research into the values and mission of an organization, or by recommending individuals who work there or in similar roles, suggested Prinsloo. Job seekers can then look at the career trajectory of those individuals to inform and inspire their application. Several AI tools can then provide analysis of a job posting — helping a job seeker identify the key skills and requirements. A lot of development organizations’ applicant tracking systems are built on Boolean search algorithms, which are keyword-based, explained Prinsloo, and AI tools can pinpoint the top skills required for a role and help highlight these in a CV. However, she stressed that candidates should still tailor each point with their own personal style and use specific and quantifiable examples of their achievements. “Instead of using the generic phrase ‘results-driven individual’ rather say, ‘I increased profitability on this project by 20%’ or ‘I led this particular change management initiative in record time.’” Where candidates are over-relying on AI, recruiters often see overuse of generic phrases, such as results-driven, dynamic professional, team player, or go-getter, according to Prinsloo. AI tools are trying to optimize for application tracking systems by using a lot of buzzwords, she explained, and, as a result, a CV can read like a checklist of keywords. These tools can also struggle with local jargon or acronyms that are unique to development projects, organizations, or even regions, and they can lag behind evolving terminologies, such as LRF, or locally restricted funding, which is a term that emerged in the last three years, she said. Formulating ideas AI can help candidates overcome writer’s block by providing initial ideas, framing, or samples for cover letters. But candidates should still do the majority of the writing, Prinsloo said. And, while World Vision doesn’t often ask for cover letters, if an employer requests this, then there is a reason — they are likely looking to assess a candidate’s writing style or communication abilities, she suggested. Cover letters that are written entirely by an AI tool also tend not to perform well as they lack insights into an individual’s unique motivations for the role and interests in the organization’s mission, or can end up closely resembling the work of another candidate. Prinsloo also cautioned against relying on AI tools to write technical assessments or case studies, as recruiters are looking to assess a candidate’s creativity or level of experience through these exercises. Interview preparation One of the best uses of AI, Prinsloo suggested, is for interview preparations. She recommended specific tools that can develop interview questions related to a role, help candidates practice mock interviews, and provide feedback on their communication skills. But remember, said Prinsloo, interviews can often go off script, so candidates should still be prepared for additional questions with real-life examples that “quantify” their value and achievements. Examples of this, she suggested, might include how much a candidate grew a donor portfolio or how much fundraising revenue they were able to bring in. The final checks There are several AI detection tools available — recruiters and hiring managers might use these when they find a technical assessment answer that is very similar to another candidate. Prinsloo suggested that job seekers can use these same tools to see where modifications or further human input are needed in their application. AI tools can, of course, also be of great assistance in spell-checking and proofreading text, she said, but candidates should still double-check all parts of their application or even ask a friend to do a final read-through.