What were your expectations from the trip to Paris?

Kaavya:
Over the last two years, we have studied coding languages such as R, Python and PSQL. I was hoping that the trip to Paris would allow me to see, directly, how Large Language Models are built and used by companies and how they compare to those we have studied on the programme.

Jiaqi:
I was also brimming with questions for industry experts. With all of the conversations around AI, the labour market and skill requirements from graduates, I was hoping to both gain reassurance on the future awaiting graduates and an idea of how I want to move forward in my professional development.

What did you learn about how companies use data, AI or analytics in their work?

Kaavya:
We visited all sorts of companies, from the International Finance Corporation (IFC) of the World Bank to Schneider Electric and L’Oreal. I was surprised to see the extent to which each one has embedded GenAI and AgentAI into their day-to-day operations across all divisions, from HR and Marketing to Research and Engineering.

Jiaqi:
What struck me most was how differently each organisation applies analytical and technological tools. From relying on clear, data-based modelling to estimate consumer demand to driving efficiency and inspiring creativity to improving their product offerings, each company used AI in tailored and innovative ways to improve their overall performance.

Can you tell us about a company visit that resonated with you?

Kaavya:
During our visit to AXA, we were tasked with finding insights and solutions to the flash flooding that occurred in Valencia in 2024 using genuine client data. This exercise showed us how data science can be incorporated into the insurance industry to manage claims, especially during mass crisis events. It also meant that we could apply the skills we’ve learnt from the degree into a real-world scenario.

Jiaqi:
For me, the visit to Alstom – a global leader in rail transport – was especially eye-opening. Coming in with limited exposure to the infrastructure industry, I was fascinated by the creative ways technology is being integrated into their operations. Whilst exploring the uses for AI in Alstom’s system operations and maintenance, they shared how their models help optimise energy efficiency in Singapore’s Mass Rapid Transit (MRT) system. This connected with me on a personal level being from Singapore myself and having an increasing interest in sustainable development.

Outside of the company visits, how did you explore Parisian culture?

Kaavya:
The river cruise on the Seine was one of my favourite moments – it was lovely to see the landmarks and socialise with my friends, and there was no rain!

Jiaqi:
My favourite moment was a guided tour of Montmartre, a neighbourhood perched on the hills of Paris with breathtaking views and a fascinating, if often tragic, history – it was a welcome contrast to the city’s bustling centre.

As a third-year student, why were these company visits so valuable for your future career?

Jiaqi:
These company visits helped me bridge the gap between theory and practice. I’ve become more conscious of the need for me to develop good prompt engineering skills and awareness when interacting with AI so that my creative and critical thinking is enhanced rather than replaced.

Kaavya:
Gaining real-world insights was especially helpful – it helped to identify how the skills I’m learning may be relevant in the private sector and confirmed that continuous learning in areas such as Python and coding, even after graduating, is an advantage.

Jiaqi:
The visits also broadened my awareness about possible career paths, from roles that focus on organisational value, creation and adaptability, to opportunities that require deeper technical expertise or further study. I am also even more inspired to eventually join a global organisation such as the World Bank to contribute to poverty alleviation and sustainable growth.