Every January, over 300 CEOs and business elites gather in the Swiss Alps for the annual World Economic Forum (WEF) meeting to discuss and shape industry agendas for the year ahead. In 2024, it was clear artificial intelligence (AI) has captured zeitgeist — becoming THE buzzword of the modern society and dethroning last year’s poster boy, cryptocurrency — as Generative AI took centre stage in many boardroom conversations.  

Here are 10 key takeaways from “AI as Driving Force for the Economy and Society” at WEF 2024 for individuals, businesses, and institutions.

1. ‍AI will fuel the 4^th industrial revolution driven by hyper-productivity.
   AI has the potential to add up to $4 trillion in economic value annually, with its impact felt across all industries — from accelerating new drug discovery to revolutionizing supply chains with digital twins. While a handful industry leaders adeptly integrate AI into their company, many are still playing catch up, building digital transformation foundations and modernizing IT infrastructures to support an imminent AI strategy. The new era will be one of hyper-productivity with AI becoming accessible and people finding innovative ways augment not only routine cognitive work, but also creative, discretionary, strategic jobs in consulting and research.  
2. ‍AI will transform what it means to have a future-ready workforce.
   Despite AI's potential impact on almost 60% of global employment and 40% of job tasks, the risk is not job loss to AI, at least in the short to medium term, but to other individuals who embraces and knows how to use low-cost AI tools like ChatGPT effectively. Quoting Paul Hudson, CEO of Sanofi who said, “AI beats human, but AI plus human beats AI”. This paradigm shift will impact society and business in numerous ways — from education syllabus, workforce training to regulatory frameworks and labor reallocation strategies — to protect those at risk from the widening gap in workforce readiness.  
3. ‍Governments play a key role in getting their countries ready for AI.
   Governments should look towards the UAE as a role model for preparing their nation for AI. Three things they do well, educating senior government officials on AI through the AI Program facilitated by the University of Oxford, sending SMS to every citizen with resources on what AI is and how it will impact their career and lives, and lastly, making AI a compulsory subject for all students above grade 9.
4. ‍AI starting to show clear business value in enterprises.
   Finance and IT will be the first functions to change because of AI. Developers using AI tools like GitHub Copilot or AWS CodeWhisperer report 20 – 40% enhanced productivity, compared to those who don’t. Customer service will be next, as business use AI to redefine service for a new generation of customers by responding to queries faster, using fewer resources for issue resolution and providing more empathetic service while embracing automation.  
5. ‍Every employee will become a manager.
   The evolution of white-collar job will see many roles operating at “a little bit higher of a level of abstraction” as Sam Altman, CEO of Open AI puts it. With more automated capabilities just a few prompts away, we will see an increase in hiring for roles that coordinate and make smart decisions using AI tools and possibly autonomous agents. The next generation of managers will be creatives, idea-generators, and out-of-the-box thinkers fueling greater innovation and doing more meaningful work with AI.
6. ‍AI will increasingly be deployed at the edge and everywhere.
   The recent CES showcase revealed consumer devices — from mobile phones to AI-specific hardware like Rabbit’s R1 pocket and Apple’s Vision Pro — featuring AI-native capabilities. There will be AI in everything we get our hands on, learning who we are and how we interact with the world. And as next generation of GPUs show up more powerful and smaller in size, AI will be pervasive in our daily interactions, warranting explainable AI to ensure trust and safety in its use.
7. ‍LLMs are an early form of AI and capabilities will evolve significantly.
   Concerns over the concentration of closed LLMs, have led to emergence of open source and smaller language models — developed with smaller data sets and lower computational requirements to democratise transparency and avoid inherent pitfalls of larger models. While large enterprises continue to build company named GPTs for proprietary use, the future LLMs will have the ability to learn from smaller, higher-quality data sets more effectively. And as we eventually hit a roadblock of trying to get smarter, human-based data for training, LLMs will need to self-improve by experimenting and interacting with other models. Humanity and our knowledge are an upper limit to the current strategy, and it needs to evolve.  
8. ‍Industry data sharing will be a tricky talk of the town.
   How good an AI performs depends on its training data. Enterprises today guard their data as a form of competitive advantage in a personalisation-driven world. However, as AI evolves to enable critical use cases in healthcare, companies may need to move past data protectionism and establish an industry-wide data-sharing framework to build better LLMs that can serve society better. Imagine healthcare companies combining their collective trove of patient data to build a superior AI model for diagnosing and recommending treatments for life-threatening diseases. The society would be a much better place with one-unified model build on multiple datasets than have multiple models trained with less data. While data privacy and security are valid concerns, they can be addressed through partnerships between industry consortia and regulatory bodies.
9. ‍Governments to exercise care in regulating AI as the technology matures.
   AI-generated disinformation is second only to extreme weather from climate change as a global risk, according to 53% of leaders. With the potential to influence elections, the need for AI regulation is pressing. While the EU has agreed on AI regulations that is soon to be approved by the Parliament, there are still looming questions about the safe and responsible use of AI — should prompts be copyrighted, how can we distinguish human-made vs machine-made, is it ethical to bring back artists like Michael Jackson in AI-generated music videos. As image generating and processing AI gains traction, a balanced regulatory approach is crucial, one that allows for co-evolution of society and technology while providing a framework that allows innovators to do what they do best, responsibly.  
10. ‍AI can solve most, but not all of humanity’s problems.
    The potential of AI to help us solve our biggest challenges is why we have been working so hard to get it to where it is today. The speed at which COVID-19 vaccines were produced is one evidence of AI’s contribution — Moderna went from manually producing around 30 mRNAs each month to producing around 1,000 a month with AI. Discussions at Davos highlighted AI applications in synthetic biology, waste management, and material lifecycle management. However, the journey before companies invest in AI for sustainability is long, given the substantial energy and power needed for training. Echoing the sentiment of Amandeep Singh Gill, the UN Secretary-General's Envoy on Technology, current trends suggest that "AI will not rescue the SDGs."

While Twimbit is not a participant in WEF 2024, we have compiled these insights from interview soundbites and publications by third-party partners. We are a long-standing admirer of WEF’s ability to ignite forward-looking conversations on global issues and priorities. We aspire to one day contribute to these discussions, help build a better world, and deliver exceptional experiences to all stakeholders.