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AI’s Dual Impact on Workplace Equality: Challenges and Opportunities

The rapid rise of Artificial Intelligence (AI) is presenting leaders with the challenging task of prioritizing human resource needs while pursuing profitability.

Key Insights from Industry Leaders

  • Corporate responsibility is heightened as AI may increase unemployment and exacerbate inequalities, according to Pedro Uria-Rescio, CIMB Group’s Chief Data Scientist, speaking at the GITEX Asia 2025 conference.
  • Uria-Rescio emphasized that companies should not only equip employees with AI-related skills but also create new job opportunities in light of ongoing technological shifts.
  • The UN’s trade agency has cautioned that AI could affect 40% of jobs globally, deepening the disparity among nations.

Navigating the AI Revolution

The AI revolution is reminiscent of past technological upheavals, such as the internet boom. While AI is often touted for boosting efficiency, its broader implications need careful management. Uria-Rescio argues that businesses should adopt an ‘AI-first’ mindset without sidelining human involvement.

Balancing People and Profits

The Microsoft Trend Index 2025 reveals that 82% of business leaders are confident about leveraging digital labor to extend workforce capabilities, with 78% exploring AI specialist hiring. Meanwhile, 47% prioritize upskilling current employees.

Human Element in Focus

Despite the concerns, experts remain optimistic about AI’s societal role. Tomasz Kurcik from Prudential Singapore believes AI can democratize opportunities, potentially revitalizing traditional crafts and generating new job prospects. Successful adaptation relies on collaborative efforts among educational institutions, governments, and corporations to mitigate emerging inequalities.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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