On March 15th, Ventech China and BNP Paribas Personal Finance (BNPP PF) jointly hosted a workshop in Shanghai, focusing on the theme of "AI and Corporate Innovation." The event welcomed executives and partners from Geely's financial division, Geely Automotive Finance, senior management from BNPP PF Asia for in-depth discussions.

The workshop served as a platform for exchanging knowledge and fostering collaboration between industry leaders and experts, paving the way for future advancements in AI-driven innovation within the corporate landscape.

During the event, Mr. Cedric Desplats-Reider, the CEO of BNPP PF Asia, gave a wonderful opening speech on the group’s vision on AI. In addition, Mr. Zhiren Mao from Ventech China and Mr. Stan Lu, founding partner of OR10 Venture Builder shared their insights on AI and Corporate Innovation, Mrs. Xia Li, the CEO of Geely Holding  finance sector, expressed her outlook and expectations for AI.

We have compiled selected speeches from the distinguished guests of this event, hoping to inspire you.  

1

Mr. Cedric Desplats-Reider,  the CEO of BNPP PF Asia:

AI is not the future, but the present

According to a ranking released earlier this year, BNP Paribas has emerged as one of the top ten global banks in terms of AI adoption rates. It is also the only bank from Europe to make it to this list, ranking sixth in AI-related talent recruitment. Our group's vision is to position ourselves as a bank with data and AI at its core.

AI has revolutionized the way automotive finance operates, leveraging its ability to process vast amounts of data, deeply understand customer behavior, and provide personalized financing solutions. AI algorithms cananalyse customers' financial histories, social media activities, drive new patterns, enhance credit assessment accuracy, and enabling the provision of more precise financing schemes. AI has also transformed customer service norms, enabling round-the-clock assistance, answering queries, and guiding customers through loan applications, thereby aiding the bank in reducing operational costs.

However, the impact of AI extends beyond these realms. As we embrace AI, we must also confront certain challenges, such as ethical concerns and data privacy. It is imperative that we use AI responsibly, demonstrating transparency and fairness in all AI-driven actions.

2

Mr. Zhiren MAO, Ventech China

Unveiling the Minds of Machines: From Inception to Competitive Edge

Human history has witnessed slow productivity growth until marked by exponential leaps, intersecting with Moore's Law and AI advancements. This era represents a golden age of AI-driven productivity, evident in the internet sector's massive growth. 

AI development has evolved, empowering machines with learning abilities and addressing complex problems. GPT3's transformation to GPT4 promises greater future strength. 

However, AI also fosters the Matthew effect of productivity, amplifying disparities between strong and weak entities. Mastery in AI utilization enables leveraging productivity for significant advantages.

Correct AI usage is crucial for competitive gains, yet many companies fail to boost productivity despite heavy IT investments. Involving all in digitization or AI transformation is vital, with CEOs playing a pivotal role. 

Challenges accompany AI utilization, including the "bitter lesson" of progress relying on increased computing power. Ethical dilemmas arise, demanding a balanced approach to avoid biases and exploitation. Vigilance is crucial, ensuring suitable AI deployment scenarios.

3

Mr. Stan Lu: Founding Partner of OR10 Venture Builder 

How can corporate be prepared for catching the ball of ‘AI’ 

1.        Generative AI will be a new round of cameras replacing painters.

Drawing a parallel with the advent of photography, where traditional portrait painters feared obsolescence but gave rise to new professions like photographers, AI similarly disrupts the job market but also generates novel opportunities.

2.        Generative AI is the reproduction of perceivable features, rather than the application of defined formulas.

The “Tokyo Night” made by Sora video model underscores how generative AI strives to convey perceptual characteristics, emphasizing feature reproduction rather than the strict application of a model. The focus is on conveying information perceptionally, rather than adhering to rigid accuracy. In this sense, generative AI functions akin to the subconscious processes in dreaming, capable of generating language that doesn't necessarily align with reality or accuracy.

3.        The application of Generative AI goes far beyond generating content, and the greater opportunity is to deliver services through agents.

Another exciting future prospect for me is the utilization of AI Agents for service delivery. AI Agents will emerge as innovative applications in the AI era. For instance, in onboard AI systems, we could use voice commands to have AI Agents place orders, showcasing AI's potential in service delivery. In the AI Agent era, smartphones might transition from central to peripheral roles, with Agent services becoming the focal point of construction and design, leveraging both small-scale models and larger ones' capabilities.

4.        Generative AI, like informatization or digitization, brings a revolution but only in "Feasibility".

In enterprise innovation, how does the role of AI relate to previous trends in informatization and digitization? We now see generative AI as akin to past efforts, aiming to enhance feasibility. Firstly, does innovation stem from demand (DESIRABILITY)? Does the design align with needs, and does it offer business benefits (VIABILITY)? Lastly, is the innovation feasible (FEASIBILITY)?

5.        The "Enterprise level" generative AI has already become reality. But how can companies smartly navigate through the swift tech iteration and gain a clear vision of the benefits brought by AI and ROIs before committing resources in developing the AI?

As businesses prepare for the integration of enterprise-level generative AI models, several crucial steps need to be taken. These include assessing the benefits, calculating the return on investment, adapting workflows to accommodate AI integration, addressing organizational challenges, exploring potential collaborations, and undertaking comprehensive preparatory measures before embarking on full-scale development. This meticulous preparation ensures that businesses are equipped to confidently allocate resources towards the development of enterprise-level generative AI models, thereby gaining a strategic advantage in the AI landscape.

4

Ms. Li Xia, the CEO of Geely Holding  finance sector

Attitude and choice are what make humans greater than AI.

I deeply admire those driven by curiosity and exploration, as they expand our understanding and fuel breakthroughs like AI. While some fear AI's emergence, maintaining an open mindset is crucial. 

I strongly agree with the viewpoint that businesses should decide what kind of AI, software, or systems to invest in based on their own operations and business models. Money can measure all this, but more importantly, businesses should understand what they truly need—this is their core competency, not just any ability.

Personal capabilities, including openness and adaptability, are vital. AI shouldn't replace human wisdom; rather, we must leverage it alongside our unique abilities. We possess something AI cannot mimic: true wisdom derived from our thoughts and experiences. Harnessing this, we can shape AI's role and coexist with it, knowing it's a product of our creation. This underscores the power of human ingenuity, surpassing AI's capabilities.

5

A vivid group discussion was held during the event. All the management team discussed their needs, thoughts, and expectations for AI from different business perspectives.