Everyone is talking about artificial intelligence (AI). More specifically, they are buzzing about generative artificial intelligence (GenAI), the chatbots with the perceived potential to usher in a universal utopia or destroy the world (depending on who you talk to).
These extremes are speculative at best, foretelling an uncertain future shaped by GenAI.
In the meantime, GenAI tools, like ChatGPT, Claude, Gemini and the countless other models popping up daily, are good coders.
In fact, they are really good coders.
More specifically, it is a good coding assistant. One study found that GenAI increases coders’ productivity and capabilities, expanding their aptitude for new data science tasks, even without prior experience in coding or statistics.
However, in 2025, we don’t just need more software. We need safer software that is resilient against even the most pernicious cybersecurity threats, putting companies and customers at risk.
For small startups and major corporations, this places increasing importance on DevOps and software development skills, training and certification.
This is where GenAI can really help companies. In addition to producing new code, it can enable companies to teach their tech teams how to protect sensitive data, maintain regulatory compliance and mitigate emerging security risks at scale.
Training and Testing Development is Difficult
DevOps teams need cutting-edge training and testing to prepare them for increasingly sophisticated and constantly emerging cybersecurity threats.
Creating training and testing programs that provide actionable information and don’t just check boxes and waste time is time-consuming, labor-intensive and expensive.
To produce truly effective training programs, in-house or third-party certification programs rely on a rigorous and systematic process involving iterative processes with subject matter experts (SMEs) and other experts who use their experience and expertise to guide content development.
Test creators leverage their insights to generate training material and test items, which are subsequently reviewed by a panel of SMEs, who modify these draft questions for accuracy, appropriateness, difficulty and relevance.
It’s a workflow ripe for new efficiencies that make creating high-quality training and testing materials more agile and responsive while controlling costs and improving consistency.
This is where GenAI can help companies streamline and enhance this complex workflow.
GenAI in DevOps Testing and Certification
GenAI offers compelling DevOps training and certification opportunities but also presents unique challenges.
For example, the technology’s ability to understand and generate natural language allows for the creation of realistic and engaging test scenarios. At the same time, GenAI can enhance and simplify spell-checking and grammar correction, ensuring the accuracy and professionalism of test items while making it more feasible to continuously create and improve training and testing content as the DevOps and cybersecurity field continues to change.
Taken together, GenAI offers a cost-effective solution for test development, potentially reducing the resources required for manual test creation.
To be sure, these are productivity and cost-control improvements, not full-scale automation because the technology still poses unique risks and challenges for certification programs. This includes:
- Accuracy and Reliability: GenAI platforms still make mistakes, hallucinating and confidently presenting wrong information as right.
- Bias: GenAI models can inherit biases from their training data, leading to unfair or discriminatory test content.
- Security and Privacy: Using commercial GenAI products can make it difficult to protect the security and privacy of sensitive test and test-taker data.
- Rapid Evolution: GenAI technology is both novel and rapidly changing, making it difficult for companies to keep up with the rate of change and the implications for their work.
- Legal Uncertainty: There is still uncertainty about the copyright status of AI-generated content.
Perhaps most prominently, because GenAI technology is still so new, its greatest strength and most significant shortcomings are probably still being discovered.
In response, assessment creators must stay adaptable and proactive, modifying their strategies to capitalize on GenAI’s advantages and minimize its drawbacks as the technology evolves.
Best Practices for Implementing GenAI in DevOps Testing and Certification
To harness the full potential of GenAI while mitigating its risks, several best practices can guide organizations in creating effective and responsible AI-powered testing and certification programs.
#1 Treat GenAI as an Assistant
Use AI to augment human expertise, not replace it. Subject matter experts should work alongside GenAI tools to ensure the quality and relevance of test content.
For example, GenAI can create practice tests or question variants that benefit the overall testing experience but don’t undermine expertise or production quality.
#2 Focus on Quality Control
Inaccurate training is the same as no training at all. When using GenAI tools to support training and test creation, robust quality checks ensure the accuracy, fairness and relevance of AI-generated content.
That’s why human review and validation are essential to integrating GenAI into the content creation process.
#3 Prioritize Data Security
Protect the privacy and security of test-taker data and sensitive test content. Use secure platforms and tools that comply with relevant data privacy regulations.
Put differently, don’t just put your test information into ChatGPT. Instead, leverage third-party tools that protect privacy and prevent your data from entering the public domain.
#4 Get Good at Prompt Engineering
Effective prompt engineering, which involves designing and refining input prompts to optimize GenAI model performance, is necessary for creating high-quality exam assets.
#5 Commit to Continuous Improvement
Continuously evaluate and refine the use of GenAI in testing and certification processes. Monitor the effectiveness of AI-powered tools and adapt strategies as needed.
Enhancing Security and Productivity With GenAI
Undoubtedly, GenAI can help organizations develop and validate the skills needed to build and maintain secure and reliable software.
Even so, training and test creators will need to integrate the technology thoughtfully and intentionally, addressing potential challenges and prioritizing data security and quality control.
Organizations can leverage GenAI to enhance their DevOps training and certification programs by embracing these best practices and remaining adaptable.
The result? Meaningful progress toward a more secure and efficient software development lifecycle.