Sustainability in the Era of Artificial Intelligence

6:35 pm
July 8, 2023

Sustainability and technology modernization are becoming integral to business performance, with organizations incorporating both into their core processes. One aspect of this transformation is the use of generative AI, which is gaining recognition from business leaders worldwide. However, CEOs are faced with the challenge of implementing generative AI responsibly while maintaining trust from stakeholders.

CEO Perspectives on Generative AI

A survey conducted by the IBM Institute for Business Value found that 75% of CEOs believe that having advanced generative AI capabilities will be crucial for gaining a competitive advantage. CEOs prioritize productivity and profitability as their top business goals and acknowledge the importance of technology modernization in achieving these objectives. However, there is a disconnect between CEOs and their executive teams regarding AI readiness, with only 29% of executives believing that they have the expertise to adopt generative AI.

The Impact of AI on Sustainability

While sustainability is a key challenge for business leaders, there are obstacles preventing progress in this area. CEOs cite struggling with manual data management, unclear ROI and economic benefits, lack of insights from data, and regulatory barriers as the top barriers to achieving sustainability objectives. However, forward-thinking organizations recognize that sustainability and profitability can go hand-in-hand. By creating a balanced sustainability and profitability roadmap and leveraging data and AI, leaders can drive productivity while achieving sustainability goals.

Corporate boards are also increasingly emphasizing sustainability efforts, with more than 50% of CEOs having compensation tied to specific sustainability measures. Modernizing IT environments is critical for organizations to make sense of their data and progress towards sustainability goals. This can be achieved through AI implementation, green IT solutions for reducing IT carbon footprints, and advanced analytics platforms for transparent sustainability data management.

Leadership and AI in Sustainability

Sustainability requires leadership across the entire organization. CEOs and decision-makers must recognize sustainability as a business driver and imperative. The role of AI in meeting sustainability goals cannot be understated, and organizations must leverage technology to drive real and sustainable change.

Learn More about Sustainability, CEOs, and AI

For more information on sustainability, the role of CEOs, and the impact of AI, consider:

  • Exploring how CEOs leverage technology to meet business demands
  • Learning more about IBM Consulting Sustainability Services

*Methodology

The data for this article is based on the 28th edition of the IBM C-Suite Study series, which involved interviews with 3,000 CEOs from over 30 countries and 24 industries. The study was conducted by the IBM Institute for Business Value in collaboration with Oxford Economics. Additionally, a survey of 200 CEOs in the United States was conducted to gather insights on their responses to generative AI.

FAQ

Q: What is generative AI?
A: Generative AI refers to the use of artificial intelligence technology that can generate new content, ideas, or solutions based on patterns and data inputs.

Q: How can CEOs leverage generative AI?
A: Generative AI can help CEOs make more informed decisions by providing insights and recommendations based on complex data analysis. It can also automate certain tasks, improve productivity, and drive competitive advantage.

Q: Why is sustainability important for business leaders?
A: Sustainability is increasingly recognized as a critical concern for businesses due to environmental challenges and changing consumer expectations. Embracing sustainability can lead to cost savings, improved reputation, and long-term business resilience.

Q: What are the barriers to achieving sustainability objectives?
A: Business leaders face challenges such as manual data management, unclear ROI and economic benefits, lack of insights from data, and regulatory barriers when trying to achieve sustainability objectives. These obstacles can hinder progress and require innovative approaches to overcome.


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