Every business has been on a shared journey over the last 12 months. It began with adapting to new ways of working while fighting for survival as the global pandemic tightened its grip. More recently, many have progressed to recovery so they can hit the ground running as the world opens back up.
However, forward-thinking leaders are already looking beyond COVID-19 and rethinking how they can thrive and survive in a very different world to meet their customers evolving needs. Big data, AI, automation, and sustainability are big topics in boardrooms. But they seldom stop to think about how these different areas affect one another.
Rethinking business strategy with AI
No business needs another lengthy IT project on its hands. Solving business problems should always come before adopting any new tech solution. When appropriately used, the winning combination of AI and machine learning can help any organization to reduce operating costs, improve efficiency and deliver better user experiences that their customers are demanding.
As consumers increasingly favour experiences over products, AI can bring personalized product recommendations to life.
Data-driven decision-making and demand forecasting have become the norm.
Elsewhere many are leveraging the value of customer service automation, sentiment analysis, and customer segmentation. From a security perspective, innovation in AI analytics and toolkits make it easier to prevent fraudulent transactions.
AI enables businesses to expand their horizons and unlock a revitalizing effect that allows an entire organization to think bigger. Advanced systems can process and draw results from a smorgasbord of data points that have not been possible until now. But what impact is progress having on our environment?
The carbon footprint of artificial intelligence
Data centres account for more than 1% of all electricity consumption worldwide. As modern AI models develop an insatiable appetite for data, the energy requirements for computational resources will dramatically increase the world's energy usage.
Could data-hungry business strategies conflict with company-wide sustainability plans?
If industry trends continue as predicted, we can expect AI and cloud technologies' carbon footprint to become much more severe and undo any positive effects of well-intended sustainability initiatives. It's a catch-22 situation where AI models can transform entire industries and play a pivotal role in boosting individual climate change strategies, but it can also increase carbon emissions.
Data-intensive computing is raising more questions on the actual energy costs of our infrastructure and the GHC footprints they leave behind. But could Green AI be the answer?
Green AI technology
Green AI is a popular topic of conversation in the tech community. The belief is that AI can also help reduce the effects of the climate crisis by building a greener and more inclusive future. Despite AI using vast amounts of energy, many believe that the unlikely partnership of AI and sustainability could be the perfect match.
Big tech is currently racing to be carbon negative by 2030, and AI will play a key role in ensuring these targets are met. For example, Google's DeepMind division developed AI to improve energy efficiencies when cooling its data centres.
AI helped Google reduce its data centre cooling by 40%.
In agriculture, AI is also promising to transform production by monitoring, learning, and managing environmental conditions. AI's deep predictive capabilities combined with intelligent grid systems can also manage the supply of renewable energy. Green AI is also drastically improving the sustainability and efficiency of supply chains.
Critics would argue that AI cannot help build a sustainable future if it's not sustainable by design. The AI revolution is proving costly for our environment with worrying increases in CO2 emissions. Whether the pros genuinely outweigh the cons will depend on how businesses approach their goals, future strategy, and technology.
Although we have witnessed giant leaps forward with advances in AI, the efficient use of energy in its infrastructure is still very primitive. A quick look in the history books reveals similarities in how the arrival of steam engines and later electricity transformed our world. We also need to learn from our past and how progress can impact our planet.
Here in 2021, it's AI, the IoT, big data, and cloud computing that has the power to help businesses become more sustainable, low-emission, renewable, and efficient. But the push for energy-efficient Green AI will require very different strategies and a commitment to continuous improvement.
Businesses need to see Green AI as having two sides. One for sustainability and the other for the sustainability of green AI itself.
On paper, AI and sustainability might appear to be the odd couple of tech. But when emerging technologies and new ways of thinking replace legacy hardware and mindsets, we will see a convergence that delivers a greener AI which helps build new systems that enable both the economy and nature to thrive.