The International Screen Institute provides high-quality training programmes for European and international film, TV and media professionals which are delivered by renowned industry experts who share their real-world expertise and insights.
Applications are still possible for ISI’s winter programmes Future Ready and Hands-on A.I. Producers Lab, which are dealing with new technologies and technological innovation in the audiovisual industry.
Future Ready provides inspiration, orientation and strategic perspectives and it prepares participants to embrace cutting-edge tools like AI, virtual production, and immersive storytelling while staying grounded in legal, business-relevant and ethical considerations.
The Hands-on A. I. Producers Lab, in collaboration with EAVE, is designed as a practical follow-up, in which producers are given the space and time to shape their tools, and to further develop and test ideas that were introduced during Future Ready or the Online EAVE AI Skills Booster.
Future Ready takes place in Vienna from 30 November – 2 December 2026, having the Hands-on A.I. Producers Lab as a practical follow-up from 3 – 4 December 2026, also in Vienna.
The programmes are complementary. Apply for both and benefit of a package deal, as there are still a few places available. Check out the Financial Support Guide of the International Screen Institute to learn about their extensive scholarship-opportunities. Professionals from low-capacity countries are eligible for financial support of up to 50% of the participation fee. In exceptional cases, higher support may be granted.
Joanna Szymańska is one of the mentors at the Hands-on A.I. Producer’s Lab. She is a Polish film producer and co-founder of Shipsboy (https://shipsboy.com/en/), an independent production company focused on international coproductions and new models of development. With nearly two decades of experience across the European audiovisual landscape, she specialises in international coproductions, strategic development, and innovation in storytelling. She has been an early adopter of AI in film, exploring its use in audience research, production workflows, and narrative development. She is also co-founder and co-host of The Sideletters podcast.
FNE: You’ve been working in the film industry for almost 20 years and started integrating AI in filmmaking from an early stage. What initially convinced you that AI could become genuinely useful for producers rather than simply being another technology trend?
Joanna Szymańska: I am genuinely interested in future and in progress, but on a very human scale. I am constantly asking myself: what can help me become a better producer? Somebody who understands more, who can organise things better, who can look at a problem from more than one perspective? And I also have this vice that I do quite a lot of things.
So when I first heard about ChatGPT, really very early on, almost as soon as it became available to a general audience, I immediately thought: this might be a technology that can help me wear all these different hats better.
Producing is complex and strange profession as we constantly move between completely different modes of thinking. We have to think creatively, than we need to analyse something financially or legally. We organise people and processes, we research, we negotiate, we make decisions based on incomplete information. There are all these different challenges, requiring different skills.
So what interested me in AI was its potential to enhance my human capabilities. Not to replace my thinking, but potentially to extend it: to help me process information, move between different perspectives, challenge my assumptions, and sometimes see something I wouldn’t have seen on my own or haven’t heard of yet. I was fascinated by the possibility that it could help me become more capable of doing the things I already do, not to make it do them for me.
And as I started using LLMs, quite quickly it was obvious to me that it wasn’t simply another trend or gimmick. Despite the way AI is sometimes presented, all these „slop of the week” images and videos, generic LinkedIn posts etc., underneath that there is an extremely powerful technology, and years of science and research advancing it. Of course, there is a very big “if” attached to all of this: if we use it critically, and if we remain attentive not only to what it does to our work and our own thinking, but also to the costs we tend not to see immediately: environmental costs, questions around legality of how the models are trained and how dependent we become on a few of big tech non-European companies.
Now I would say I am in my „pragmatic era”. I am much more focused on the practical aspects of technology: does it solve an actual problem, whether the time saved is greater than the time spent setting it up, and what intellectual or financial cost comes with using it.
FNE: You’re already integrating AI into your day-to-day work as a producer. Where have you personally found AI most useful so far and where has it been less useful than you initially expected?
Joanna Szymańska: From my perspective, I use LLMs mostly as an extremely fast junior research assistant or sparring partner. And I should add that this hasn’t replaced junior positions in my company. It has allowed me to do certain things that previously neither I, nor my team, wouldn’t have the time or capacity to do. For example, I am currently exploring the area of film distribution. There is an enormous amount of free data available about audience behaviour, demographics, marketing trends and consumption patterns, but firstly its scattered across different sources and secondly I don’t have the analytical skills to properly digest all of it myself. With AI, and models I have trained for my own use, I can create something like a junior advisor which helps me identify marketing trends that might be relevant to the films I am releasing.
I also find it really useful as a sparring partner. As a producer I have to be involved in negotiations or policy-making discussions. And I come to these with my own prejudices and assumptions, sometimes very focused on my own goal, which I find limiting. So I use AI to challenge myself: be my opponent, be the other person in the room, show me how this situation might look from their perspective. Of course it is a simulation based on incomplete information, not actually entering somebody else mind (yet). But it can expose prejudices and patterns in my own thinking and allows me to see perspectives I haven’t considered.
Where I find it much less useful is creative work. AI can generate enormous amounts of material, but quantity doesn’t produce quality. I almost never use it to generate creative ideas. Once you understand roughly how these models work, it’s quite obvious. And here I think it is important not to anthropomorphise it. This is a technology that is extremely good at identifying patterns, arranging them and analysing them. But genuinely interesting creative work often comes from breaking those patterns, AI cannot do it „by itself”. So part of becoming good at using AI is also learning when not to use it.
FNE: AI tools are developing extraordinarily quickly. How do you decide which new tools are actually worth investing time in as a producer, rather than constantly chasing the newest technology?
Joanna Szymańska: I have stoped chasing tools, the progress is so fast and there is so much of this marketing BS around it, that it simply feels too overwhelming. But it is a challenge to resist this omnipresent narrative “you have to try this, you have to try that, here is the new model that is going to change everything, here is another one that will erase us from the surface of the Earth etc.“
I don’t think following that narrative is a particularly healthy or sustainable way to run a company or yourself as a human being.
What I try is to start with the problem. What is the process I want to address? Could it be automated? Should it be automated? Would it simplify somebody’s work?
I have to admit that this has exposed another challenge for my company. We started thinking about building our own system around an open-source model, fine-tuned to the company’s needs. But we haven’t really moved very far with it yet, because we realised that before you automate processes, you need to understand and describe those processes properly. And we hadn’t. So strangely enough, thinking about AI forced us to look much more closely at how our company actually works without AI.
I am also very aware of the cognitive cost of outsourcing things. I believe that intelligence, creativity and our emotional lives develop through challenging ourselves. So there are things I simply don’t want to outsource. I would never outsource analysing a script to a machine, for example. The time spent with the text, including sometimes struggling with it, is part of how I form my judgement. This also means I take a lot of time to read and give my feedback to the writers – sorry for this (laugh).
I also feel a lot of resistance to this idea that because AI can make us more efficient, that we should squeeze even more productivity into every hour of the day just because we can. I don’t want human-AI collaboration to result in humans simply doing more work, I’d rather see AI make us better human beings rather than simply more productive workers.
Currently I am trying to work out how AI can help me run the company I actually want to run, in the way I want to run it being fully aware there is also no free lunch here. These technologies have material costs: energy, water, environmental impact. There are legal questions and questions of dependency on technology providers. Somebody, somewhere, always pays part of the cost. Also because of that I don’t feel I need to test every new model or application that appears.
FNE: What would you recommend participants do before arriving in Vienna so that they can use the two days as effectively as possible? Should they prepare a very clearly defined challenge, experiment with particular tools, or come prepared to rethink their existing workflow?
Joanna Szymańska: I would definitely recommend starting with some self-reflection. Look consciously at how you are already using AI, but also at the things where you think: „I would like AI to help me with this, but I don’t really know whether it can, or how to approach it”.
You can also bring some of your AI try outs with you. It can be something you tried that worked, but it would be equally interesting to see something that failed. If you spent three days trying to automate a process which was supposed to make your life easier and in the end made everything more complicated, let’s discuss that. There is probably much more for us to learn from that failure than from watching another marketing AI demo.
My goal for these two days is definitely not to introduce twenty new tools or discuss every new agentic approach or RAG setup. I want to look underneath, at the processes themselves, at how we work, what we actually need, and what we consciously want to delegate to technology and what we don’t. So the best preparation is to observe your own work for a while before coming to Vienna and bringing an open mind as well.
FNE: The Hands-on A.I. Producers Lab gives producers dedicated time to engage with A.I. in a focused, small-group environment with close guidance from experienced mentors. Why is it important to give producers this kind of space to experiment with AI and what can they discover that they’re unlikely to learn simply by reading or hearing about AI?
Joanna Szymańska: First of all, I strongly believe in peer-to-peer education. And I think it is particularly important with AI because, despite everything we are hearing, nobody really knows where this is going. There is an enormous amount of narrative heat around AI. We are constantly being pushed between extremes: this will change your life, this will eliminate jobs, this will democratise filmmaking, this will bring the planet to the edge of collapse, this will make you ten times more productive, this will squeeze you out of the job market. And somewhere inside all of that noise, we are actually trying to understand what this technology means for our everyday work.
So I think there is real value in taking some time to detach from that noise and look at what your peers are actually doing. Not what somebody is promising AI will be able to do in two years, but how another producer is using it today. What works? What doesn’t?
A hands-on lab also gives us a kind of sandbox where we can experiment safely. It gives us time to look properly at our companies and our working processes, identify where the real problems are, test and think about what a results we are hoping for. Using AI increasingly means making decisions about how much control we are willing to give to technology, particularly as we move towards more agentic systems. I think producers need to make those decisions consciously rather than simply accepting whatever level of automation the technology happens to be offering.
For me, the best outcome in Vienna would be that people leave the workshop having tried things, having had time to think about them, and most importantly, having developed their own judgement.
Because the tools will change. But the ability to think critically and analytically about them, to self-reflect, and to make your own judgement about where technology belongs in your work, that is something that stays and can be applied again and again.
