The talk was delivered by Kaur Kallas from Tartu Centre for Creative Industries, a technology innovator with more than 15 years of experience building advanced lighting systems and control software for the film industry. His work has shaped productions such as Star Wars: Rogue One, Dune, and The Batman, placing him at the intersection of deep tech and high-end creative production.

From distribution to generation at zero cost

Kaur opened by drawing a historical parallel. The internet reduced the cost of media distribution to near zero. AI, he argued, is doing the same for media generation. This shift fundamentally changes what matters in creative work.

When everyone has access to the same tools, the differentiator is no longer production capability, but taste, vision, and the ability to filter ideas effectively. AI does not make decisions for creators — it overwhelms them with possibilities.

AI will amplify either your genius or your stupidity.

This abundance forces a change in mindset. Traditional creative processes often involve protecting and refining a single idea. AI-driven workflows, by contrast, reward experimentation, rapid iteration, and emotional detachment from early concepts.

The creator as a curator

One of the central shifts Kaur described is the changing role of the creator. With AI, creators increasingly resemble producers rather than craftsmen — selecting, discarding, and combining outputs rather than building everything from scratch.

AI systems generate variations quickly, but they lack judgment. Taste remains human. The creator’s job is to set direction, evaluate results, and decide what deserves further development.

Letting go of attachment to individual ideas is difficult, especially for experienced artists. Yet this ability to discard quickly becomes a core creative skill in an AI-augmented environment.

Pre-visualisation as a strategic tool

Beyond ideation, Kaur highlighted AI’s growing role in pre-visualisation. Studios increasingly use AI-generated sequences to test concepts before committing to full-scale production. From a producer’s perspective, this reduces financial risk and allows creative decisions to be validated earlier.

AI enables teams to simulate entire scenes, edits, or even seasons in advance — identifying problems before they become expensive on set. This approach is already used in short-form content, where ideas are tested with audiences before being scaled, and increasingly in large studios experimenting on platforms like YouTube.

However, Kaur cautioned against over-reliance on short-term signals. Audience testing optimises for what works now, not necessarily what will matter in the long term. Tactical wins should not replace strategic vision.

A creative equaliser — with consequences

Because AI tools are widely accessible, they act as a creative equaliser. Production value alone is no longer a moat. What gains importance instead is community — an audience that resonates with a creator’s specific taste and worldview.

Kaur argued that this shift may actually favour independent creators and niche storytelling, as long as they understand their audience deeply. At the same time, it raises uncomfortable questions about the future of personalised content.

AI gives you superpowers — but you have to be careful how you use them.

As content becomes increasingly tailored to individual preferences, creators and platforms must grapple with questions of resilience, diversity of perspective, and creative responsibility.

Where content creation is heading

Looking ahead, Kaur outlined a progression from traditional mass media to algorithmic discovery and, eventually, to fully personalised storytelling. Emerging formats such as micro-dramas — ultra-short episodic content optimised for mobile consumption — illustrate how rapidly formats are evolving.

These models prioritise speed, iteration, and engagement, but often rely heavily on paid distribution and short-term attention. Their long-term sustainability remains uncertain.

At the far end of the spectrum lies fully adaptive content — stories that respond in real time to viewer behaviour and even biometric feedback. While technically feasible, such systems raise ethical and creative questions that the industry has only begun to address.

AI as a mirror

Kaur described AI as a mirror. It reflects the creator’s intent, discipline, and clarity — magnifying both strengths and weaknesses. Used carelessly, it produces noise. Used deliberately, it accelerates craft.

AI doesn’t replace creative judgment.
It forces you to use it more.

The session’s takeaway was clear: the future of content production is not automated creativity, but augmented authorship. Those who learn to guide, filter, and collaborate with AI will expand their creative range — while those who surrender judgment risk losing it altogether.