At work and in the world, change is in the air.
The Great Resignation? That’s behind us. The debate over hybrid and remote work? It’s less relevant. The struggle to retain top talent in a competitive job market? It’s an ongoing challenge.
Now the conversation has coalesced around the potential impact of generative AI (genAI) and its impact on the present and future of work.
According to Gallup, 72 percent of Chief Human Resources Officers (CHROs) say AI will replace jobs in their organization in the next three years, while 65 percent say the technology can be used to improve employee performance throughout their companies. Consequently, as Gallup notes, “the demand for new skills is higher than ever. The time to act on upskilling the workforce is now.”
Employees know it and are ready to act.
Less than half of employees strongly agree they have the skills they need to excel at their jobs, and they are eager to upskill their skill sets. That’s why many professionals are pursuing skills-based training and certifications, creating testing challenges for employers, regulatory bodies, and other stakeholders.
Training and Testing Challenges When Upskilling Employees
Upskilling is a powerful lever for workforce development. However, many training initiatives don’t formally upgrade skills because they don’t validate and certify knowledge acquisition. That’s because testing and certification protocols are inherently complex and resource-intensive.
When developing certification examinations, in-house and third-party certification programs typically follow a rigorous and systematic process. They convene subject matter experts (SMEs) to conduct a job task analysis, defining the expected knowledge, skills, and abilities of their profession or specialty. These SMEs outline the content domain for assessment, drawing on their extensive expertise. They also gather input from others in the field before test creators apply these insights to test item creation.
Experts draft initial test items that cover specific content areas of the exam blueprint while a separate cohort of SMEs review and modify these draft assessments for accuracy, difficulty, and relevance.
SMEs are valued and valuable, and they are in limited supply. Their efforts often are hindered by workflows and limitations, creating a need for new efficiencies that make creating training and testing material more adaptable, dynamic, and cost-effective.
GenAI in Testing and Training
GenAI, the same technology driving so many professionals to seek upskilling opportunities and prompting employers to provide it, can provide powerful tools to augment the capabilities of subject matter experts.
There are many reasons for this. Perhaps most importantly, genAI understands and generates natural language, allowing SMEs to quickly use the technology to create realistic and engaging testing scenarios. It also can amplify quality control by correcting spelling and grammar errors, ensuring content is appropriate for the audience’s background knowledge and industry standards, and producing differentiated materials such as practice tests, study guides, and simulations.
Of course, genAI isn’t without its drawbacks and potential risks, including unpredictability of outputs, its propensity to hallucinate without warning, and uncertain copyright status.
To capitalize on the benefits of genAI while mitigating risks, it matters how this technology is leveraged not just that it is used.
Best Practices for Using GenAI in Test Item Creation
Here are some best practices for using GenAI to enhance the test item creation process.
1. Treat GenAI like your assistant, not your replacement.
More professionals are worried about genAI’s impact on their career trajectory than they are hopeful that it will improve their work experience.
Those fears often feel validated when genAI’s unprecedented power is brought to bear on their specific work tasks.
In reality, genAI is a better assistant than a human replacement.
Therefore, SMEs shouldn’t shun the technology out of fear that it will eliminate their job. They should leverage the technology to create better work more efficiently.
2. Focus on quality control.
Training, testing, and certifying new skills is a high-stakes endeavor. After all, we want to know that our cybersecurity specialists, medical professionals, or legal counsels are vetted by accurate, rigorous, and relevant content.
When using genAI as part of the testing and certification development process, also introduce a process to review and correct inaccurate, biased, or irrelevant information.
3. Protect test-taker data and sensitive test content.
Indiscriminately feeding personal or proprietary information into a genAI solution is a data privacy and integrity nightmare.
Put bluntly, don’t just input sensitive information into consumer-grade genAI solutions. Instead, use secure platforms and tools that comply with relevant data privacy regulations and protect critical information.
4. Get good at prompt engineering.
Prompt engineering—the art and science of crafting effective instructions for generative AI models to elicit desired outputs—is increasingly in demand among companies looking to maximize genAI’s impact on their organizations.
Unsurprisingly, job postings and salaries for these professionals with these skills are surging.
Companies looking to enhance their testing, training, and certification processes with genAI should invest in prompt engineering, as the quality of a genAI model’s output is highly dependent on the input prompt.
Experiment with prompting and learn how to write effective prompts to get the best results from genAI solutions.
5. Commit to continuous improvement.
GenAI is still in its infancy with new capabilities and concerns arriving in real time. Its application to training, testing, and certification is even more nascent.
Content creators need to stay up to date on the latest developments in this field and to continuously evaluate and refine the use of genAI in testing and training programs.
In other words, genAI isn’t a “set it and forget it” solution. It’s a still-developing tool that requires constant monitoring and adaptation.
Preparing a Next-Gen Workforce with GenAI
As the workplace changes and modernizes, upskilling workers will be an important part of the transition. Companies need people equipped to thrive in the future of work and employees want to remain relevant and competitive in their careers.
Training, testing, and certifying these skills will be an important component of organizational success and individual growth.
It’s an iterative process propelled by experts and technology. It’s also one that can be enhanced by genAI making it more accessible, efficient, and adaptable to companies and their employees.
