From decision-making to efficiency gains: Leaders at 'Summer Davos' discuss ways to harness AI

AS artificial intelligence (AI) continues to evolve, the narrative is clear: how can we leverage the emerging technology to solve real-world problems in a responsible way?

This was the resounding message from leaders who gathered in Dalian, China, in June for the World Economic Forum's Annual Meeting of the New Champions (AMNC24), as they urged for discussions to focus not on who has the best AI, but who is solving the most pressing problems through AI.

Throughout key sessions around the theme of 'Entrepreneurship in the Age of AI', participants stressed the importance of proactive regulatory frameworks, ethical standards and the crucial balance between innovation and control.

The discussions not only showcased AI's advancements, but emphasized its role in addressing issues from skills gaps to the energy transition. Here are just a few themes that emerged during the Meeting:

1. Decision-making

In the future, advanced AI agents will be able to help organizations with decision-making, said Darko Matovski, Co-founder and CEO of causaLens, which is empowering AI systems to reason about cause and effect.

"There's this tremendous opportunity to use AI agents and more advanced forms of AI, as we develop them, to transform completely how we make decisions in our society, which will lead to more equitable, more efficient, better societies," he told the What can AI Assistants Do? session.

But, even the most advanced organizations have a minimal number of real-world use cases of AI when it comes to decision-making, he said, so there's a long way to go.

Matovski explained the difference between causal AI and large language models (LLMs): "We want an AI that can understand the cause and effect relationships in the real world like we do, like humans...

"To the user, it will look like they're using an LLM. But in reality, it will be grounded to a causal understanding of the world. And we believe that this is really the breakthrough technology that will unlock most of the use cases in enterprise and in policy decision-making."

2. Talent gaps

AI has already been proven to speed up recruitment, said Nancy Xu, Founder and CEO of Moonhub in the same session. The company combines proprietary AI and human talent to help organizations find talent fast, with less bias.

"I think about it as a sort of combination of silicon talent or AI agents and biological talent, which is what humans can do. And creating that synergy between the two."

Xu said AI tools could lead to a world of "talent abundance":

"In a world where talent is traditionally the bottleneck for growth, I think the really exciting opportunity for AI agents is actually to compress the time scale that it takes to build ideas or companies to impact and make it possible to do that in a much more compressed time frame."

Early AI adopters also have a competitive advantage, she added: "What we've observed is that the companies that can actually deploy AI early on to solve this problem have a significant advantage, because they're now able to scale faster, they're more competitive."

3. More efficient industries

The Forum's network of Lighthouse manufacturers are already proving that the 'ABC' of AI – Algorithms, Big Data and Computing – can improve efficiency in smart factories

In the session, AI Breaking New Ground: What's Next for Industry?, Jay Lee, the Director of the Industrial AI Intelligence Center at the University of Maryland, said that in the manufacturing industries, in the past few years, AI was leading to "about a 30% benefit in predictive maintenance, 15/20% in quality improvements and another 20% in operation optimization, such as scheduling and efficiency".

Energy efficiency in offshore wind turbines, for example, was also being improved, decreasing downtime from around 5% 10 years ago to 2% today: "That's a lot of energy you can generate".

There are some "really attractive opportunities" for AI to improve efficiency in both commercial buildings and shipping and logistics, said Samuele Ramadori, CEO of BrainBox AI.

But he stressed there was "a lot of work to be done" in many industries to make them AI-ready, with the main challenge being to enable AI to access data.

"There has to be that combination of access to the data and then making novel AI outcomes quite powerful."

4. Upskilling through personalization

The efficiency of AI means it can enable powerful "hyper-personalization of learning" which "allows for better student engagement, better learning outcomes," said Vu Van, CEO of ELSA, an AI English language speech assistant.

"In education, that's basically the holy grail, because every single individual has very different needs of learning, but traditionally it has been extremely hard to offer a hyper-personalized learning path at scale for all of the learners, from school to corporations."

In organizations, Van said it was hard for companies to even identify the areas of skills gaps for employees and then often they offered a generic blanket training solution for the entire team, which could be costly and inefficient.

But "with AI, especially generative AI, we [have the ability to] automatically generate content on the fly".

5. Unlocking growth

Adopting digital technologies through the Digital Economy Framework Agreement (DEFA) could unlock $2 trillion in inclusive growth for the 10 countries in ASEAN, according to research.

In the AMNC session, Unlocking ASEAN's Digital Prosperity, Ivan John E Uy, Secretary of the Department of Information and Communications Technology in the Philippines, said the main challenge for ASEAN was that digitalization had been siloed.

But now AI was enabling collaboration and interoperability that would enable growth.

"The challenge is ... being able to collaborate, being able to connect and to share information across the different platforms and across the different countries. And we can do this today because the technology allows it: the cloud platforms, the artificial intelligence understands the uniqueness of each system, but at the same time identifying the commonality of the applications," he said.

"We can utilize common technological platforms now to adopt to a more interoperable system."

But, there's also an obligation to ensure we don't leave people behind, as Erika Kraemer Mbula, Professor of Economics at the University of Johannesburg, stressed in the How Ready Are Countries for AI? session.

"Widespread access to the internet and electricity are still insufficient. And unless we address the digital divide, we are very likely to leave many behind in this AI movement.”

Towards responsible AI

While AI can significantly enhance operational efficiencies and creative capacities, a thoughtful and ethical approach is essential to realizing its full potential, leaders said.

And while there's a lot of hype around generative AI, most applications in industries are still in their infancy.

The Forum's AI Governance Alliance is committed to fostering inclusive, ethical and sustainable AI, with initiatives that focus on practical impacts that empower communities and industries, streamline governance and accelerate technological and societal advancements.

In June, the Alliance published the Responsible AI Playbook for Investors, highlighting the need for strong governance frameworks and clear responsible AI (RAI) standards designed to ensure AI applications are honest, helpful and harmless.

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