AI as a New Factor of Production

In today’s evolving business landscape, industry analysts see the emergence of AI as a new factor of production alongside human effort.

Rather than simply adding more people to increase output, organisations can boost productivity by equipping individuals with AI capabilities—effectively adding “digital labour” to each role.

Some experts argue that AI’s ability to reason, code, write, and analyse at scale qualifies it as a form of labour in its own right. These systems act as digital colleagues, contributing meaningfully to the production process.

People + AI: New Factor of Production

This shift redefines productivity by combining human ingenuity with intelligent systems. It marks a move towards an AI-augmented workplace, where machine intelligence enhances human decision-making and output.

Rather than spending time on repetitive or computational work, individuals now delegate these tasks to AI and focus on creative, strategic, and high-impact activities.

The People + AI Paradigm

Some organisations are rapidly adopting this model. For example, pairing an engineer with an AI assistant enables them to tackle a broader range of tasks. The AI can handle code generation, data analysis, documentation, and other routine work, while the engineer focuses on strategic decisions and expert judgement. The result is a significant amplification of individual capability.

From a hiring standpoint, this means increasing headcount isn’t the only way to scale output. Companies will prioritise candidates who know how to effectively leverage AI tools. In technical roles, one AI-savvy employee may deliver the impact of several traditional hires. Hiring leaders should consider this “compute factor” when planning team capacity and evaluating candidates.

Implications for Hiring and Talent Strategy

This transformation has significant implications for recruitment and workforce planning in tech and engineering:

Workflows are evolving: AI tools are becoming embedded in everyday processes, changing how tasks are completed and how teams collaborate.

Skill sets are shifting: Organisations now search for candidates who can work effectively alongside AI—those who understand how to use these tools to amplify their impact.

Productivity expectations are rising: With AI handling routine tasks, employees are expected to deliver more strategic value. This raises the bar for what constitutes high performance.

Talent strategies must adapt: Hiring managers should assess not only technical expertise but also a candidate’s ability to integrate AI into their workflow. Interview processes may include tasks that involve AI tools to evaluate how well candidates can leverage them.

Higher Productivity Through AI Integration

Organisations integrating AI into daily workflows are seeing dramatic productivity gains. These gains can be grouped into three levels of AI adoption:

Level 1: Humans + AI Assistants

At this stage, individuals use AI tools to accelerate their tasks. For instance, developers might use AI to generate code, write boilerplate, or debug errors. Studies show that developers using AI assistants complete tasks up to 55% faster, translating to roughly 1.5× productivity.

Candidates who can partner effectively with AI tools bring immediate efficiency benefits. At this Level 1, organisations can look for individuals who embrace AI tools to enhance personal efficiency.

Level 2: Human-Led AI Agents

Here, AI agents take on entire subtasks under human supervision. In software teams, AI might manage deployments, run tests, triage bugs, or draft code. The human sets objectives and handles exceptions. This partial automation can triple productivity by reducing time spent on routine work.

From a recruitment perspective, candidates with experience managing AI-driven workflows or orchestrating automation will stand out. Interviewers might explore how applicants would use AI to scale their impact or lead digital agents.

Level 3: AI-Led Work

At this advanced stage, AI agents can autonomously run entire projects or processes. Humans intervene mainly for guidance, exception handling, or final approval. For example, an AI system could develop a software module from start to finish, while engineers refine requirements and address edge cases.

In non-technical roles, AI might manage logistics end-to-end, with humans overseeing relationships and exceptions. Productivity gains at this level could reach 5–10× per person, depending on the task.

At this Level 3, organisations should search for and hire candidates with system-level thinking who can oversee autonomous agent teams.

As organisations progress through these levels, the qualities they seek in candidates will evolve.

Hiring assessments may increasingly include tasks involving AI tools to evaluate how well candidates harness these technologies. The future of work will see the co-existence of AI alongside human ingenuity to drive higher productivity.

A New Blueprint for Talent in the Age of AI

We’ve reached a pivotal moment in the evolution of work. For HR and engineering leaders, the blueprint for success in the age of AI begins with talent.

Organisations that understand the implications of AI-driven transformation—and align their hiring and development strategies accordingly—will position themselves as agile, high-performing, and attractive to forward-thinking professionals.

Embracing this future of hiring goes beyond simply filling roles. It means building a workforce that can fully harness the potential of AI while keeping human creativity, judgement, and innovation at the core.

Companies that invest in AI fluency, responsible integration, and continuous learning will lead the way as “Frontier Firms”—setting new standards for productivity and employee experience.