How Will Your Role Work with AI? 

Author: Hugo Farinha, co-founder of Virtuoso QA

Integrating AI sensitively into the workplace while acknowledging the perceptions, negative and positive, around the impact AI may have is going to be an essential skill for the C-suite over the next few years. The landscape will shift, putting greater emphasis on certain skills that will be needed to cover the requirements of working alongside AI, and others better suited for areas where human involvement is still essential… 

 The immediate impact of AI will be the automation of administrative tasks, leading to a reduction in entry-level roles. Over the long term, this will shift in focus towards more strategic, analytical, and customer-facing positions as AI takes over routine tasks. The job market is going to evolve alongside AI advancements, requiring ongoing adaptation and skill acquisition to stay relevant. Skills such as empathy, Communication and negotiation will remain essential skills, serving as key differentiators in effectively achieving objectives with both humans and machines. In this new era, where machines are trained to understand human language and its nuances, these skills take on even greater importance.

Nuances in language—such as tone, sentiment, context, and implied meaning—enable the transfer of deeper human emotions and intentions. These subtleties are not just critical for human collaboration but also for guiding machines to interpret instructions, respond appropriately, and deliver optimal results aligned with human expectations. Understanding AI tools and data analysis will be increasingly important, even for non-technical roles and as AI becomes more integrated, the need for professionals who understand the ethical implications and regulatory requirements will grow.

Outside of testing, AI is already poised to take over decision-making tasks across many industries, from financial market trading to human resources, the legal sector and healthcare. 

So, what are the kinds of roles within software and testing that we’ll see being offered over the next few years? 

Agentic AI Workflow Designer 

An Agentic AI Workflow Designer will implement dynamic testing workflows using Agentic AI and enable adaptive testing based on system behaviour and conversational machine-to-machine problem-solving. Rather than rigid, predefined workflows, this role will improve efficiency by optimising test paths in real time and reducing redundancies, ensuring tests are always aligned with the evolving needs of the project. 

AI Interaction and Integration Designer

The AI Interaction and Integration Designer evolves the traditional UI/UX designer role by focusing on creating seamless, collaborative experiences between users and AI agents. This role emphasises designing end-to-end user journeys where AI serves as a proactive partner, sharing cognitive, creative, and logistical tasks. It requires crafting interactions that feel natural, empathetic, and personalised while ensuring AI integrates seamlessly across ecosystems. Balancing user control with AI autonomy, these designers prioritise transparency, ethical considerations, and adaptability, transforming static interfaces into dynamic, human-AI partnerships that enhance productivity and engagement.

AI Model Validation Engineers

AI Model Validation Engineers will validate AI models, ensuring their accuracy, fairness, and reliability. The AI aspect of this role addresses unique issues like model drift and bias, making the process more efficient by identifying problems early in the AI development lifecycle.

AI Ethics Specialist 

Ethics, governance and compliance are going to gain enormous value and importance to organisations. An AI Ethics Specialist will be required to ensure Agentic AI systems meet ethical standards like fairness and transparency.  This role will have to involve someone using specialised tools and frameworks to address ethical concerns efficiently and avoid potential legal or reputational risks.  Human oversight to ensure transparency and responsible ethics is essential to maintain the delicate balance between data-driven decisions, intelligence and intuition.

Autonomous Testing Engineer 

An Autonomous Testing Engineer will design fully autonomous testing systems powered by Agentic AI. Unlike manual or semi-automated testers, this role maximises efficiency by removing the need for human intervention in repetitive or regression testing, allowing teams to focus on more complex, exploratory tasks.

AI-Driven Test Strategist 

That leads us to the AI-Driven Test Strategist who uses AI to develop high-level strategies to identify critical testing areas and prioritise resources effectively. The results achieved by AI-Driven Test Strategists will be more efficient than traditional test managers. Traditional strategists will rely on experience and intuition but the AI Driven Test Strategist uses data-driven insights to optimise efforts and prioritise areas of highest risk or value.

 AI Test Data Specialist 

Traditional testers manually create or extract test data, but an AI Test Data Specialist
will design and manage synthetic test data using AI, ensuring realistic test scenarios while addressing privacy concerns. As a result, this tester can achieve greater efficiency by generating diverse datasets at scale, reducing the time spent on preparation and ensuring compliance with data protection regulations.

Agentic AI Trainer and Configurator

Agentic AI Trainers and Configurators will adapt to domain-specific requirements by creating AI-driven systems that dynamically adjust to new inputs and requirements.

AI Bug Detector 

AI will be used to predict potential bugs before they occur, focusing testing efforts on high-risk areas which reduces rework, shortens development cycles, and lowers costs, making an AI Bug Detector a hugely important role.

Conversational Test Automation Engineer 

Chatbots and voice assistants will be tested by a Conversational Test Automation Engineer using AI-driven tools for dynamic interaction validation. Traditional testers often struggle with the complexity and variability of conversational interfaces, but Agentic AI improves efficiency by automating testing across multiple scenarios and languages.

Continuous AI Monitoring Specialist 

A Continuous AI Monitoring Specialist will detect anomalies and performance issues in real time while monitoring AI systems in production. This position leverages AI for proactive issue detection and rapid incident response and minimises downtime.

AI Lifecycle Manager 

An AI Lifecycle Manager will be required to oversee the integration and lifecycle of AI systems in the SDLC and align development and testing efforts with evolving business needs.

AI Overseer

And finally, an AI Overseer. This role is going to involve monitoring the entire Agentic stack of agents and arbiters, the decision-making elements of AI.   

AI integration is going to be an evolution as well as a revolution.  It has the potential to have more of an impact in a shorter time frame than the industrial revolution of the eighteenth century.  Integrating the human within the AI workforce is going to require, appropriately enough, peculiarly human skills.

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