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Sustainability in the age of AI
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Sustainability in the age of AI

Despite the shift in priorities, sustainability remains a major challenge for business leaders. CEOs point to environmental sustainability as their main challenge for the next three years. What prevents executives from moving toward their larger goals? Leaders point out factors such as difficulties in manage data manuallylack of clarity around ROI and economic benefits, scarcity

Despite the shift in priorities, sustainability remains a major challenge for business leaders. CEOs point to environmental sustainability as their main challenge for the next three years. What prevents executives from moving toward their larger goals? Leaders point out factors such as difficulties in manage data manuallylack of clarity around ROI and economic benefits, scarcity of useful information derived from data and regulatory barriers as some of the main challenges in achieving sustainability goals.

The truth is that sustainability and profitability they can go hand in hand. Forward-thinking organizations are leveraging sustainability as an opportunity to drive their business and achieve greater transparency around their sustainability commitments.

Creating a balanced roadmap between sustainability and profitability is a critical first step to propel organizations forward in the age of AI. This roadmap can help leaders identify opportunities and gaps in the current IT environment, facilitating more informed decision making. Applying data and AI to support sustainability goals is one way to boost productivity.

It appears that boards of directors are taking note of the relationship between sustainability and profitability, and are holding CEOs accountable for their organizations’ sustainability efforts. In fact, the percentage of CEOs whose compensation is tied to specific sustainability measures has more than tripled since 2022 and exceeds 50% this year.

Modernizing IT environments can help organizations better understand their data and advance their sustainability goals in a variety of ways, including:

  • AI implementations that automate manual data handling and transform it into usable results without compromising its security or reliability.
  • Green IT solutions that can help reduce an organization’s IT carbon footprint and even reduce computing costs by up to 30%.
  • Advanced analytics platforms that provide transparent management of sustainability data across value chains, with a single source of truth for sustainability analysis data and greater transparency.

Source: www.ibm.com

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