For the hardware they need and the data traffic they generate, AI and IoT are definitely power hungry. On top of that, some of business cases that are supposed to enforce greener processes deliberately boosted the rebound effect. As a reminder, note that rebound effect stands the reduction in expected gains from new technologies that increase the efficiency of resource use for other reasons. For instance, working from home seems eco-friendly but if you spend the day turning the A/C on, you will end up using more energy than if you merely go to the office. As a consequence, new habits can lead to offset the beneficial effects of the new technology or any other measures taken, if these new habits are not sustainable.‍

AI and IoT can also bring up good news if they are used in a responsible way, to green up existing processes and hardware. Based on an Intel study delivered in 2018, 74% of the top 200 decision makers in businesses agreed that AI would help them enable solutions for a more sustainable world. So, who is right?

Actually, the question is not that easy to settle...

Even if no real study was delivered this way, it is quite easy to understand that AI and IoT, if not developed properly for green purposes is the opposite of sustainability.

It requires specific hardware (that need high performance and up-to-date versions) and the infrastructure they need (network, back-end, servers...) must be changed often. Also, the competitive aspect of such technologies - companies must show and deploy the best projects to ensure they are better than competitors -  require companies to work on new processes and devices all the time. This indirect impact should not be underestimated, some tech companies (and their AI suppliers of course) spend time, energy and money to develop all kinds of new projects.

Nevertheless, seeing things under that only point of view is very restrictive.

It would take days, weeks to draw an exhaustive list of all green AI business cases. So, instead of giving such a list, let's just think out some wide guidelines to deploy AI for a better world:

• Improving energy consumption efficiency
• Using IoT and AI to reduce e-waste
• Using IoT and AI to reduce food waste
• Deploying IoT and AI for agricultural projects based on sustainability or any species protection
• Using IoT and AI for a better environment, cleaner air or water preservation
• Enforcing safer solutions
• Helping to develop new hardware that are more efficient (especially semi-conductors)

All these guidelines up there were deployed for recent business cases. If you wish to know more, just ask us!