Using Generative AI tools, it's now possible to create realistic videos of nearly any subject imaginable. This technology is moving fast and likely to make this article out of date quite soon, but the implications of this new technology are profound.
Moving past the risks that this technology poses for disinformation and deepfakes, one of the most compelling use cases is in foresight and scenario planning.
The power of scenarios lies in their ability to realistically portray different possible futures, each rich with detail describing how things may unfold in different ways over time. This richness is how we can use scenarios to look at multiple factors at the same time and better understand how they interact and is why scenario planning is superior to one dimensional or extrapolative forecasts.
Up until now, we had to rely on scenarios described as words, images, or even so-called "artifacts from the future". While being able to step into a room that has been created to portray a certain future is an amazingly immersive experience, it is not something that is affordable for many organisations.
Generative-AI image and video tools have brought the cost of production to near-zero and offer the ability to generate compelling videos of scenarios, which increase engagement, improve comprehension and foster more innovative thinking.
This article is about how a set of scenarios were brought to life with generative AI image and video tools.
Case study overview
These videos were prepared as part of a strategic foresight project for Minda, a disability care provider. You can read more about the background of the project in the case study.
The project created 4 scenarios based on the 2x2 Scenario Matrix approach:
Video showcase
The following videos are from each quadrant of the scenario matrix:
The journey through creating these videos.
Creating these videos used several tools as part of the overall workflow. They are:
- Leonardo.AI - Image generation
- Runway ML - Image and Video generation
- Topaz Labs Video AI - Video post-production, interpolation and up sampling
- Adobe Premiere Pro - Video editing / compositing
Challenges
With generative AI there is always a level randomness and getting not-quite-what-you-asked-for, so for many scenes there were several generations to get the right look.
Generative AI also struggles with creating consistent characters between shots so there is a lot of work done with the prompts to attempt to get some consistency. Several shots also required compositing or photo-editing to get the right look or feature.
These challenges are things that are being addressed by the latest versions of video and image generation AI models, so there is confidence that these challenges will eventually disappear.
Implications of Generative AI for foresight and strategy
One of the major barriers to organisations taking up foresight as a regular practice has been the cost. Up until recently, foresight activities required specialist practitioners and expensive research, or were limited to top decision makers only.
Generative-AI delivers the ability to democratise access to foresight, and to vastly increase the scale of foresight efforts. This in turn improves the overall future preparedness of an organisation, which increases innovation and improves overall resilience.
Organisations that harness Gen-AI to assist with their foresight activities are the ones that will emerge as most successful in the next decade.
What next?
This technology is still emerging and is likely to take a few more years before it is something similar to a ChatGPT experience where a user can simply prompt for a complete video, including music and voice over. Although this technology is moving fast so it may arrive before then.
Organisations that are interested in using Gen-AI for scenario planning can book a free consultation to have a deeper conversation to see if this technology is right for you.
