Reducing the environmental impact of operations

Whatever your industry, a clear first step in reducing your environmental impact is by making improvements to your day-to-day operations, but with so many facets and factors to take into account, ensuring you make the right decision for your business and for the planet can be difficult.

Using the deep learning and neural networking capabilities of AI to understand historic and real-time datasets, and the relationships between them, this decision-making becomes far easier. With Quantum AI, not only can you mine your business data from an environmental impact perspective, you can use predictive analytics to forecast how a multitude of scenarios might play out, enabling you to make the right decision that makes the business greener at a company-wide level and enables it to operate more effectively. Our unique algorithms also facilitate the implementation of i-DPA to streamline your operations, and continually optimise processes, intelligently.

Implementing new materials and processes

Aside from the ability to identify areas for environmental improvement, AI has a powerful role to play in ensuring new green technologies are brought to market faster. AI’s computational abilities are already proving invaluable in the identification and testing of new products and materials that displace traditional, harmful materials or negate the need for destructive farming or mining methods for their creation.

Additionally, by enabling advanced prototyping and rapid computational analysis, AI is helping bring these new technologies to market more rapidly than many thought possible.  From greener fuels and smart cities through to carbon capture and emissions monitoring, Quantum is already seeing Artificial Intelligence tools proving their worth in the green economy.

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Monitoring and proving compliance

At a corporate level, businesses are now being held accountable for their approach to climate change: institutional and private investors are placing ever greater importance on executive boards’ abilities to demonstrate a meaningful commitment to climate change, while consumers, too, are showing a greater interest in the corporate citizenship of their favourite brands.

To confidently track, standardise and report on the changing environmental impacts of a global business is a significant challenge, and one that currently takes up significant time among legal, operational and finance teams when it comes to communicating this information to regulatory and financial stakeholders. Too often, the information provided is incomplete due to a lack of true visibility cross the business, and / or a lack of historic data.

Self-learning, self-healing,
self-innovating

As this becomes an increasingly hot corporate topic, the capabilities of AI to truly understand an organisation’s environmental impact at a global level, and across complex supply chains, is matchless.

Better yet, a self-learning AI solution is able to do more than simply report; it can proactively flag and even address shortcomings and inform human colleagues of possible improvements to processes and procedures to quickly make measurable environmental improvements.