Does AI Have a Sustainability Dilemma? Research Shows Optimism Despite Energy Demands

Nearly 500 sustainability professionals weighed in:

“AI is reshaping our operations — but at what environmental cost?”

While 38% worry about AI’s negative impact on their sustainability efforts, 57% are optimistic they can balance AI’s energy demands with its transformative benefits.

1. The Energy Challenge Ahead

  • Data center consumption could double by 2026, putting corporate carbon-reduction goals at risk.

  • 75% of companies feel unprepared to translate complex AI data into actionable sustainability insights.

  • Spreadsheets and manual processes simply can’t scale with AI’s energy footprint.

Sustainability teams face a dilemma: leverage AI’s power or preserve the planet’s resources. Fortunately, the data shows a path forward.

2. Key Survey Insights

3. Top AI Use Cases for Sustainability

  1. Energy Efficiency Monitoring (50%)
    AI models predict peak consumption and optimize distribution to cut waste.

  2. Carbon Emissions Modeling (48%)
    Machine learning identifies hotspots across product lifecycles for targeted reduction.

  3. Regulatory Compliance (47%)
    Automated checks against ISO standards and emissions regulations accelerate audit readiness.

These use cases show AI isn’t just a performance hit — it can become a sustainability superpower.

4. Bridging the AI–Sustainability Knowledge Gap

  • #1 limitation: Lack of knowledge on how AI can drive sustainability.

  • 79% say educating teams on sustainable practices is a priority; 42% call it a high priority.

  • Top enablers: Improved skills (52%) and formal training programs (45%).

“Education and training narrow the gap between goals and reality — creating a culture of innovation.”
— Suzanne DiBianca, EVP & Chief Impact Officer, Salesforce

5. Turning Insights into Action

  1. Invest in Training: Upskill your teams on AI’s sustainability applications.

  2. Pilot Smart Use Cases: Start with energy monitoring or emissions modeling to demonstrate ROI.

  3. Measure & Report: Leverage AI-driven dashboards for real-time transparency.

  4. Innovate Responsibly: Balance performance gains with green investment (e.g., renewable energy for data centers).

6. Why This Matters for Mid-market Businesses.

  • Strategic Alignment: Combine AI initiatives with corporate sustainability goals.

  • Competitive Advantage: Brands that lead in both AI and ESG will stand out to customers and investors.

  • Risk Mitigation: Proactively address carbon risks tied to AI before they become compliance issues.

Ready to integrate AI and sustainability into a single, winning strategy?
Speak with an Equals 11 expert in a 20‑minute strategy call and discover how to harness AI’s power without sacrificing your green goals.

Source: Salesforce Sustainability Snapshot 2024.




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