Online proctoring security: preparing for an AI-accelerated future
The rapid evolution of AI technology is reshaping both opportunities and threats to test security. While bad actors are becoming more sophisticated, the future of testing is also defined by innovation and resilience.
The next generation of AI-enabled solutions promises to not only detect and respond to threats more quickly but also predict and prevent them before they happen. Here’s what testing organizations should be preparing for.
- Dynamic test content and personalized assessments
One of the most exciting frontiers is the use of AI to generate dynamic test items and forms. Rather than relying on static test content, which becomes increasingly vulnerable to theft and sharing over time, dynamic test generation will ensure each test taker’s assessment is unique.
This personalization builds on the concept of Linear on the Fly Testing (LOFT) and takes it further. Future AI systems will adjust test content in real time based on exposure risk and test taker performance, making large-scale cheating and content theft far less effective.
Dynamic content also supports continuous test updates. Instead of refreshing item banks every few years, AI-powered item generation allows for agile updates. This shortens the lifespan of compromised content and helps testing organizations stay ahead of emerging threats, while also keeping pace with evolving legislation, regulations, and professional standards.
Learn how AI is going beyond test preparation to deliver personalized learning tools. - Scenario-based assessments and real-world simulations
AI will also enable more authentic assessments – moving beyond multiple-choice questions (MCQs) to complex, multi-step scenarios. These can evaluate real-world skills like critical thinking, problem-solving, and even soft skills such as empathy.
In sectors like healthcare, finance, and education, this shift will make assessments not only more secure but also more relevant and resistant to theft. Scenario-based items are harder to replicate and distribute compared to traditional item banks.
Moreover, these assessments provide richer data for analysis, helping organizations not only detect fraudulent behavior but also assess the quality and reliability of the testing process itself. - Explainable AI (XAI) for transparency and trust
As AI takes on a greater role in monitoring and decision-making, explainability will become critical. Testing organizations, regulators, and test takers will all demand transparency around why AI systems flag certain behaviors or incidents.
Explainable AI (XAI) will allow security teams to audit decisions, trace back how conclusions were reached, and ensure that no test taker is unfairly penalized by opaque algorithms. Clear, understandable reporting will be vital, especially when addressing test taker queries or regulatory scrutiny.
In addition, XAI can help refine AI models over time. By understanding why certain decisions are made, organizations can identify areas for improvement, ensuring AI remains both effective and fair. - Embedding ethical frameworks into AI security systems
AI is only as good as the data and training behind it. Without careful oversight, AI tools risk bias – potentially flagging certain demographics unfairly or interpreting legitimate behavior as suspicious.
Responsible AI development will require built-in ethical guardrails, fairness testing, and continuous human oversight. Testing organizations will need to partner with experts who understand both the technology and the human impact, ensuring fair security practices that protect test integrity without compromising fairness.
Embedding ethics into AI is a trust issue, as well as a compliance issue. Organizations that demonstrate a commitment to fairness and transparency will strengthen their reputations and build greater confidence with test takers and stakeholders.
Read about how to close the AI trust gap in testing. - AI-supported proctor training and continuous improvement
While AI can flag incidents, human online proctors remain central to the security process. In the future, AI insights will help train and upskill proctors, identifying patterns of missed behaviors or incidents and feeding into more targeted training programs and policy adjustments.
This creates a continuous improvement loop where AI not only helps proctors in the moment but also helps them learn and adapt. This ensures human oversight remains as sharp and effective as the technology itself.
Discover the latest developments in quality assurance for online proctoring.
The future is intelligent – and human
While the future of test security will be AI-powered, human expertise will remain at the heart of decision making. Human oversight will ensure fairness, interpret AI findings, and make nuanced calls that algorithms can’t replicate.
At PSI, we believe the future is built on the combination of innovative technology and experienced testing professionals. Our security systems are continuously evolving – guided by real-world experience and ethical responsibility.