An evolution as well as a revolution, AI could have more of an impact in a shorter time frame than the industrial revolution. The job market, and roles, both technical and non-technical, are undoubtedly going to be affected.
Integrating AI sensitively into the workplace while acknowledging the perceptions, negative and positive, around the impact it may have is going to be an essential skill for the C-suite over the next few years.
If you are contemplating integrating agentic AI into your organisation, what should you bear in mind in terms of sensitivity and awareness?
Machines and Human Skills
Transparency and authenticity are key, along with consistency in message. There is genuine alarm about AI technology taking jobs, which has created a slight element of fear around its integration. There are also those in denial – pretending AI is not happening is not an option. By becoming a (relatively) early-adopter, you are giving your organisation time and space to adapt your business model to become as productive as possible with as little pain as possible.
Demonstrating opportunities, offering training and ultimately being honest about the direction of your business and where AI fits in provides both reassurance and a clear opportunity to grow. One of the best ways to build trust is to develop an ‘ask anything’ culture, using executive forums. In addition, demonstrating that you care more about your people than about your tech is going to be more important than ever.
Emphasise the fact that human skills such as communication, diplomacy, empathy and negotiation are not anything that can be replicated by AI. Nuance in language such as tone, sentiment, context, and implied meaning enable the transfer of deeper human emotions and intention.
These are essential for guiding machines to interpret instructions, respond appropriately, and deliver optimal results aligned with human expectations. There will also be key opportunities for professionals with an understanding of not only the regulatory requirements surrounding AI but its ethical implications in the field.
So what kind of job roles will we see, post agentic AI introduction?
The immediate impact will be the automation of administrative tasks. This will lead to a reduction in entry-level roles and a long-term shift in focus towards more strategic, analytical, and customer-facing positions.
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 emphasizes 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 personalized, while ensuring AI integrates seamlessly across ecosystems. Balancing user control with AI autonomy, these designers prioritize 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 specialized 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.
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.
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.
So as we can see, what a successful AI revolution is going to require more than anything else is undeniably human skills.
Hugo Farinha is the Co-founder and CTO of Virtuoso QA, a groundbreaking low-code platform designed to help organizations automate testing processes, identify issues within digital products, and enhance overall software quality.
Growing up in Lisbon, Portugal, Hugo is a self-taught computer scientist who has been at the forefront of building innovative solutions for both consumers and businesses for over 25 years.
His extensive experience spans the entire software development lifecycle, including the early days of web applications for media content and large-scale industry programs for global technology giants like Alcatel-Lucent.
