Augmented and Sustainable Entertainment: how Sustainability in Entertainment identifies new frontiers for augmented and Sustainable Performance

Who today has not used at least once the many functions of Artificial Intelligence? This is almost a rhetorical question, yet it opens up profound scenarios regarding the new era we are moving towards, or perhaps the one in which we are already immersed: the age of Industry 5.0.

AI is transforming the way we conceive productivity, creativity and even the very experience of cultural consumption. Few sectors reveal this transformation as clearly as entertainment. And this is not merely a matter of artificially generated content or creative support tools: what we are witnessing is a structural redefinition of the production, distribution and narrative chains of contemporary entertainment.

Cinema, television, gaming, music, live events and streaming platforms are integrating Artificial Intelligence systems across almost the entire production cycle: from writing to post-production, from content management to the personalisation of the user experience.

In other words, AI is no longer simply a technological support tool, but a genuine invisible infrastructure that now runs through much of the contemporary entertainment ecosystem.

AI in Entertainment: where we wre today

The current state of the art shows that AI is already fully integrated into the major entertainment industries, probably among the first sectors to make such extensive and cross-cutting use of it. In cinema and television, for example, virtual production has revolutionised the very concept of the set. Thanks to real-time graphic engines, digital twins and virtual environments, many productions can now recreate complex scenarios without necessarily having to move crews, sets and equipment to remote locations. Productions can collaborate remotely, share data in the cloud, render from a distance and reduce part of the traditional physical logistics.

At the same time, streaming platforms use increasingly sophisticated predictive systems to shape the user experience through recommendation and profiling algorithms. Gaming and immersive XR technologies are also evolving rapidly thanks to AI, through dynamic environments, adaptive simulations and increasingly interactive experiences. Even the music industry is redefining the relationship between creativity and automation: automatic mastering, voice synthesis, timbre cloning and assisted composition are opening up possibilities that would have been unthinkable only a few years ago.

The sustainable promise of AI

In this scenario, AI also carries an important promise from the perspective of environmental sustainability.

Let us consider a concrete example: in the past, location scouting, site inspections, crew travel, the construction of physical sets and filming in remote places involved a high burden in terms of transport, materials, operational management and, often, repeated production work. Today, thanks to the virtualisation of environments and AI-assisted previsualisation, part of these impacts can be concretely reduced. A location can be simulated, tested, adapted and reused digitally; a scene can be optimised before it is shot; a crew can work in a more distributed way, and certain journeys can be reduced or avoided.

A similar argument certainly applies to the experiential side: augmented content, immersive environments, hybrid forms of access and distributed productions can broaden cultural access without replicating, in every situation, the traditional model based on physical movement. On an organisational level too, in complex sectors such as entertainment, AI can support flow forecasting, energy management of spaces, predictive maintenance of facilities, intelligent localisation of workloads and better use of technical resources.

All this represents important progress from both a technological and environmental point of view, and it would be wrong not to recognise it. However, it would be naive to stop at this narrative alone. The question we must ask ourselves is not whether AI is "sustainable" in the abstract, but rather: under what conditions, compared to which scenario and within which analytical boundaries does AI enable a net reduction in environmental impacts compared with the traditional alternative it replaces? This is a fundamental question if we are to bring its so-called "hidden costs" to light.

The hidden costs of AI

Certain cognitive biases lead us to perceive the digital world as something immaterial, almost devoid of physical weight, simply because we cannot "touch it with our hands". As a result, it becomes more difficult to imagine that its impacts can be quantified. And yet AI is a profoundly material product. Behind every generated content item, every virtual rendering or every immersive experience lies a structured network of data centres, servers, cooling systems, data transmission networks and high-performance hardware that occupy a place and a space, often more than one.

According to the International Energy Agency, global data centres have already reached energy consumption levels comparable to those of entire nations and, although the growth of AI is one of the main drivers of future expansion, the issue of consumption is concrete. We are not only talking about electricity, but also about the water required to cool data centres, critical materials for semiconductors and GPUs, mineral resources, cloud infrastructures and hardware devices with rapid turnover.

One of the most underestimated aspects is precisely embodied carbon, meaning the emissions incorporated into the production of the hardware itself.

In this context, the applied study of Life Cycle Assessment, or LCA, becomes fundamentally important. Indeed, many LCA studies show that, for advanced electronic devices, the production phase weighs more heavily than operational use. This means that the true impact of augmented entertainment cannot be assessed by looking only at the "moment of use"; it must also include the production of devices, the supply chain, material transport, hardware lifespan, obsolescence and final disposal.

Moreover, there is an important systemic risk: the so-called rebound effect. If AI makes it easier and faster to produce content, the risk is that the overall volume of content will increase enormously, cancelling out part of the efficiency benefits achieved.

One thing is clear: efficiency alone does not automatically guarantee sustainability. So, what should be done?

LCA and LCS: the need to truly measure

For this reason, tools such as Life Cycle Assessment, or LCA, become indispensable. LCA makes it possible to analyse environmental impacts throughout the entire life cycle of a product or service: from the extraction of raw materials to end of life. In the case of AI applied to entertainment, this approach becomes fundamental precisely because it allows us to observe what normally remains invisible: the complexity of the technological supply chains that support today's digital infrastructure.

However, in the age of AI, even this approach risks no longer being sufficient. The rise of Artificial Intelligence requires an even broader perspective, closer to Life Cycle Sustainability Assessment, or LCSA, capable of integrating environmental, economic and social dimensions.

AI does not only affect the climate: it affects global supply chains, creative work, access to digital infrastructures, the distribution of resources and the management of environmental costs along the supply chain. Truly measuring therefore means overcoming the illusion that the digital is automatically sustainable simply because it is less visible. It means understanding that every innovation brings with it new responsibilities and new questions. And this is precisely where the strategic role of certifications emerges.

Certifications and Standards: tools for identifying real gaps

When discussing sustainability in the entertainment sector, the topic of certifications often generates two opposing reactions: on the one hand, enthusiasm for the so-called "green label"; on the other, the fear that it is merely bureaucracy. Both reactions, when considered individually, are probably limiting. Certifications, standards and verification schemes do not serve to declare that a technology is sustainable in an absolute sense. Their most authentic value lies in their ability to build processes that reveal the real gaps within production chains.

In a complex sector such as augmented entertainment, this aspect becomes decisive. When used properly, standards and certifications help to understand where the real critical points are located: in design, in the choice of rendering engines, in cloud management, in hardware lifespan, in data governance, in the procurement of electronic devices and in the management of technological waste.

Standards such as ISO 14040 and ISO 14044 for LCA, ISO 14067 for carbon footprint, ISO 20121 for sustainable events and ISO 14001 for environmental management systems can become valuable tools for making visible impacts that often remain hidden. Their most important function is not to declare that a technology is "sustainable", but to make the boundaries of the observed system transparent: what is included, what is excluded, what energy powers data centres, how long a hardware infrastructure actually lasts, who measures cloud consumption and where the most significant impacts are concentrated.

In an age in which the risk of greenwashing and AI-washing is increasingly real, methodological transparency becomes, in itself, a form of responsibility.

Conclusion

Sustainability does not lie in simple solutions, but in the ability to ask the "right" questions. Questions that do not seek an immediate answer, but open up spaces for awareness. Awareness that sustainability is not an endpoint, but a way of looking at reality: a sensitive, critical and conscious gaze upon the world, translated into choices that are not always definitive, but constantly questioned.