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From Vision to Reality: 4 Critical AI Themes Discussed by Leaders at Davos, 2025
From Vision to Reality: 4 Critical AI Themes Discussed by Leaders at Davos, 2025

January 23, 2025

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Several Indian political & Tech Leaders headed by Ashwini Vaishnaw are attending World Economic Forum at Davos, Switzerland. In most of the discussion, AI is an important buzzword, and several themes are emerging out of it.  

  • AI Adoption, Revenue Growth and ROI:

One of the important questions that people are concerned about today is the question of how companies can transition from simply adding AI as a "top layer" to integrating it as a fundamental part of their operations. Cathy Li, Head AI at Data & Metaverse, World Economic Forum in one of the interviews said that Companies are seeing real financial gains from AI adoption, with some experiencing a 15% increase in revenue. It is estimated that AI could contribute between 7.6 and 17.9 trillion to the global economy by 2038. However, a significant number of companies are struggling to move beyond pilot projects, with only 16% feeling fully prepared for full scale AI implementation. Neeraj Aggarwal, BCG in another interview said," 75% of CEOs want to lean in on AI, but equally 75% of CEOs are not seeing the ROI on AI ". It is noted that the companies that are leaning in on fewer use cases are getting better return on investment. There is a clear need to move beyond treating AI as simply a top layer and to think about the technology in imaginative ways.

  • Human-Centric AI and Skill Augmentation:

Second important matter of debate that is going forward at Devos is what will scalable adoption of AI have an implementation on people. The focus should be on augmenting human skills rather than replacing them. "AI cannot be replacing human it needs to be augmenting human". As Cathy Li stated, "humans will not be replaced by AI but it might be replaced by humans who actually use AI". This requires a strategic approach to change management, with companies looking at existing value supply chains and identifying gaps where AI can be implemented. Companies that are focusing on the people aspect of AI implementation are seeing better returns. A key idea is that "the ability to direct computers to do exactly what you want will be one of the most important skills". Andrew Ng reiterated that "I don't think AI will replace people but people that know how to use AI will replace people that don't".

  • Challenges in Scaling AI Implementation:

Many companies are finding it difficult to scale AI projects beyond the pilot phase. A common mistake is viewing AI as simply an add-on to existing operations instead of as a catalyst for a broader change management strategy that integrates AI into the organisation. Cathy said, "AI is not just a job of CTO anymore it's really on the CEO agenda".

Key barriers include:

  1. Data Preparedness: Many organizations lack the clean, structured data necessary for effective AI implementation.
  2. Talent Shortage: Over 40% of employers cite the lack of skilled AI professionals as a major barrier to adoption.
  3. Siloed Implementations: Companies that succeed with AI adoption typically avoid treating AI as a point solution, instead building a company-wide AI architecture.

 

  • Agentic AI and its Potential:

Agentic AI, capable of reasoning and planning, is gaining significant attention as a way to simplify complex tasks and break down organizational silos. This emerging technology is expected to proliferate in the coming years, moving beyond language models to quantitative models that can advance fields like chemistry, biology, and medicine.

Leaders at Davos highlighted that "AI agents will be the big theme," predicting widespread discussions about their implementation next year. One notable example is an airline that reduced approval times from 6 days to just 2minutes by transitioning to AI agent-based processes.

These trends suggest that while AI offers huge potential for economic growth and efficiency, it is important to implement it carefully. This involves focusing on human skill augmentation, managing change, and promoting global collaboration and data diversity for responsible AI governance.


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Madhumay
Deputy Manager - Research

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