The New Future of Work: How Enterprises Adapt to the Rise of GenAI Now


Rich Wilson
June 10, 2024

I read a fascinating report from McKinsey last week, A New Future of Work: The Race to Deploy AI and Raise Skills in Europe and Beyond. The report discusses the impact of AI and automation on labour markets in Europe and the US, projecting that by 2030, up to 30% of current work hours could be automated, primarily driven by generative AI. This shift will demand significant occupational transitions, particularly in STEM and healthcare fields, while reducing demand in roles like office support and production work. To adapt, businesses need to focus on upskilling and retraining workers. Successful technology adoption and worker redeployment are essential for enhancing productivity and achieving economic growth.

However, most leaders I speak to are under pressure to adapt now. Open talent models are being accepted by more leaders and here is why:

Reskilling Takes Time

Reskilling employees to meet new technological demands, such as AI and automation, is a significant challenge. According to the McKinsey report, the shift in labour demand driven by AI and automation necessitates major upskilling efforts. Traditional reskilling programs are time-consuming and resource-intensive, often taking months or even years to yield results. During this transition period, businesses can experience skills gaps that hinder productivity and innovation​​​​.

Reducing Fixed Costs

Simultaneously, there is mounting pressure to reduce fixed costs. The economic uncertainty and competitive pressures demand that companies become more agile and financially efficient. Fixed costs associated with full-time employees, such as salaries, benefits, and training, can be substantial. By tapping into the open talent pool, businesses can convert these fixed costs into variable costs, paying only for the skills and labour they need when they need it. Research from Gigged.AI shows that companies can significantly save on recruitment costs by leveraging open talent platforms​​​​.

Immediate Access to Skills

Open talent models provide immediate access to a global pool of freelancers, contractors, and gig workers with specialised skills. This model allows companies to quickly fill skill gaps and respond to market changes without the delays associated with hiring and training permanent staff. For example, in industries where technology and market demands are evolving rapidly, such as tech, marketing, and creative sectors, having access to a flexible workforce ensures that companies remain competitive and innovative​​​​.

Scalability and Flexibility

One of the key advantages of open talent is its scalability. Businesses can scale their workforce up or down based on project needs and market conditions. This flexibility is crucial in responding to sudden shifts in demand or managing temporary projects. It also enables companies to experiment with new ideas and technologies without committing to long-term employment contracts​​​​.

Innovation and Diversity

Engaging with diverse talent from around the world brings fresh perspectives and innovative solutions to business challenges. Open talent pools often consist of individuals with varied backgrounds and experiences, fostering a culture of innovation. This diversity is particularly beneficial in creative and strategic roles where new ideas and approaches can drive business growth​​​​.

Access to New Skills

Gartner produced an interesting report recently on the main skills that wool be needed now and in the next 3 years as GenAI continues to impact large enterprises:

  • Data Engineer: Designs and maintains scalable data pipelines.
  • AI Architect: Designs AI systems and frameworks.
  • Head of AI: Oversees AI strategy and implementation.
  • UX Designer: Creates intuitive interfaces for AI systems.
  • Data Scientist: Applies statistical methods and machine learning to extract insights from data.
  • Model Manager: Oversees the lifecycle of AI models.
  • Model Validator: Tests and validates AI models.
  • ML Engineer: Develops scalable machine learning solutions.
  • Prompt Engineer: Designs prompts for NLP models.
  • Knowledge Engineer: Manages knowledge bases for AI applications.
  • Analytics Engineer: Builds data solutions for advanced analytics.
  • AI Product Manager: Drives the development of AI products.
  • AI Risk and Governance Specialist: Manages ethical and regulatory aspects of AI.
  • AI Ethicist: Ensures responsible and ethical use of AI.
  • D&A and AI Translator: Bridges the gap between technical teams and business stakeholders.
  • Decision Engineer: Integrates AI into decision-making processes.
  • AI Developer: Creates AI applications and solutions.


In conclusion, the integration of open talent into business strategies is not just a trend but a strategic imperative. As reskilling takes time and the need to reduce fixed costs becomes more pressing, businesses must leverage open talent to remain agile, competitive, and innovative. By embracing this model, companies can access the skills they need when they need them, drive down costs, and position themselves for long-term success in a rapidly changing market.

For more insights on the future of work and the role of open talent, you can read the full McKinsey report here.

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