How GenAI shapes talent strategies for the future

AI is transforming the workplace at an exponential pace - leveraging it for talent development is key to building a confident future.

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Organizations are navigating complex changes, with artificial intelligence (AI) playing a key role in accelerating growth and transforming workplaces. Leveraging it for talent development is essential to shaping the future with confidence.

In this episode of the EY Nordic Fit for Future Podcast, we explore insights from the EY 2024 Work Reimagined Survey, which reveals a notable increase in employee turnover rates, indicating a need to adapt to a more dynamic job market.

To gain a "talent advantage," companies must focus on comprehensive rewards, advanced work technology (including generative AI) and opportunities for learning and career growth.

The episode discusses how employees are eager to apply their digital skills across various sectors, underscoring a shift in the traditional office role to a hub for socializing and professional collaboration.

In conclusion, the episode stresses on the urgency for adaptability. It advocates for lifelong learning and fostering enriching cultures to attract and retain top talent, thereby creating an innovative work environment.

Exponential growth in employee turnover highlights the need for talent advantage through comprehensive rewards and learning opportunities. Learn how:

  • GenAI is transforming workflows and processes.
  • New metrics, like employee recommendations, are crucial for assessing organizational culture and talent health.
  • Flexibility fosters innovation and trust.
  • Strategies can improve talent retention and health.
  • Success hinges on breaking down silos, fostering a culture of growth, and integrating AI and holistic incentives to drive innovation and retain talent.
  • Continuous learning and personalized upskilling can help.

Presenter :

  • Marcus Jarl, Associate Partner, EY Markets & Business Development, EY Sweden

Podcast

Season 2, Episode 1

Duration

39m 51s