Creative technology’s advantage beyond access to AI tools

An editorial interpretation of the conversation, distinguishing the guest’s arguments from verified business outcomes.

Where AI is changing the brief

Laurent Thevenet describes creative technology as a bridge between engineering and creative practice. His route from software engineering and a Singapore startup into BBDO, R/GA and Publicis Groupe informs a role that spans campaigns, product design, infrastructure and transformation. Rather than place every specialist in one agency, he connects a core group with a wider network across APAC. AI has made that ability to translate between disciplines especially useful: easy access to a tool does not remove the engineering work of deploying and integrating it.

Why tools alone do not create an advantage

In his account, AI currently makes its clearest contribution at the beginning of the creative process, helping planning, strategy and briefing through faster access to information and proprietary data. Production is also changing as teams move more directly from an idea to visualisation. He argues that experienced filmmakers and art directors who adopt the tools still produce stronger work, while people without traditional creative titles can gain a place in the process. Publicis’s advantage, he says, combines enterprise safeguards, exclusive data and distinctive talent, rather than consumer access to the same models alone.

The distributed creative technology organisation

Thevenet points to India’s Apollo eleven unit and work from Singapore as examples of technology becoming part of a creative team’s normal practice. The Tiger Summer Puffer discussion shows a progression from rough internal prototyping to specialist production across countries. He distinguishes Singapore’s Marcel AI engineering hub, which builds supporting tools, from creativity and creative technology that remain distributed across markets. Bringing the right people into briefs early, sharing work internally and connecting makers across agencies are central to his approach. He also describes AI simulation as a way to help clients consider unfamiliar ideas, while acknowledging limits to his own measurement expertise.

Prototype first; bring the specialists later

Hiring, for him, is about people who can bridge different disciplines; a perfect balance of engineering, ideas and craft is rare. Juniors need freedom and mentorship to develop the other side of their practice. Looking ahead, he sees possibilities in connecting physical and digital experiences through AR and mixed reality, but says the useful form factor remains uncertain and must fit natural behaviour. He also urges attention to quantum computing, framing its timing and effect on advertising as uncertain even as he speculates about major computational gains and an acceleration of AI.