Siemens and IBM showcase an AI-based, CO2 friendly advisor

Making the case for AI, or any nascent technology for that matter, can be a struggle for companies today. While large enterprises know they need to be fast, agile and innovation-obsessed to survive disruption, their age-old policies, antiquated systems, disconnected data and entrenched corporate habits can be serious blockers to adoption.

With a century plus-long tradition of engineering excellence, we at Siemens knew we had a challenge to transform ourselves in order to continue to lead in the AI era. Adopting a mindset of risk-taking and innovation from the inside-out had to be a key part of that transformation journey.

Thanks to our recent efforts with the IBM Data Science and AI Elite team, together with the IBM Garage at the Watson IoT Center in Munich, we recently made a critical breakthrough on our journey to AI. Working with partners such as IBM and others, we developed a proof of concept to showcase how we could harness AI and blockchain to drastically reduce our employees carbon output—not through mandates, but through incentivizing more eco-friendly behavior.

When it comes to reducing CO2, the main culprit of climate change, Siemens maintains that companies have a clear role to play. Prior to the adoption of the Paris Agreement, Siemens made a commitment to achieve a net zero-carbon footprint by 2030 with one clear goal: cutting CO2 in our production facilities in half by 2020.

With Siemens’ employee travel producing upwards to 300,000 tons of CO2 annually, we knew we would need to re-think the future of work. When our CTO’s office created an innovation arm to pilot blockchain and AI projects to spin out into the rest of the department, we were inspired to apply these technologies toward this goal.    

Once we shared some early concepts with IBM, they quickly got us into an IBM Garage workshop where we came together as one team strengthened by the diversity of ideas.Once we refined the idea for a CO2-friendly travel advisor, we were against a short and swift 6-week sprint to completion of a minimum viable product (MVP).