NetApp: How Leaders Navigate AI's Sustainability Challenges

The rapid progress in AI technologies, highlighted by developments in LLM's and ML applications, has thrust companies into a maze of investment decisions, data handling and infrastructural demands.

With the global economic climate and stringent regulation of AI tech posing added pressures, businesses stand at a crossroads.

Over the past year, AI has leapt forward, with GenAI finding widespread use and novel applications transforming various sectors.

This leap has underscored the urgent need for robust data frameworks and management tactics.A deep dive by NetApp into how global corporate entities and regions are facing these hurdles reveals vital benchmarks for leaders crafting AI strategies for 2025 and beyond.

Its study, the 2024 Data Complexity Report, shows companies wrestling with the realisation that success in AI hinges not only on sophisticated algorithms but also on foundational data management, secure practices and sustainability measures.

Data sustainability: AI's environmental impact under scrutiny

As AI adoption accelerates, 34% of global tech executives foresee significant changes in corporate sustainability processes, while 33% anticipate new government energy policies and investments, according to NetApp.
The energy-intensive nature of AI-driven data growth and infrastructure poses a challenge to sustainability goals, with this impact being more pronounced in AI-leading countries.

Carbon footprint reduction remains a top priority, especially in regions with high AI adoption. However, its focus has declined year-over-year, from 84% of companies in 2023 to 72% in 2024.

The key challenge ahead lies in balancing AI's environmental costs with its innovative potential.

“2025 is shaping up to be a defining year for AI, as organizations transition from experimentation to scaling their AI capabilities,” Gabie Boko, Chief Marketing Officer at NetApp concludes.

“This year’s Data Complexity Report shows that businesses are making significant investments to drive innovation and efficiency, but these efforts will succeed only if global tech executives can address the mounting challenges of data complexity, security and sustainability. Intelligent data infrastructure, with unified data storage at its core, will be key to unlocking AI’s potential.”

Is AI an expensive necessity?

NetApp's findings point out that two-thirds of organisations globally have their data fully or mostly primed for AI uses. Yet, a significant 40% of tech leaders worldwide foresee a daunting surge in investment towards AI and data management come 2025.

The shift from experimental AI projects to full-scale implementation underscores this forecasted spike in funding.

While strides have been made in data optimisation, the push towards groundbreaking AI achievements is expected to demand deeper investment.

This does not come without its challenges, however.

With the escalation of AI usage, a notable 41% of tech chiefs predict a noticeable upsurge in security threats by 2025, marking data privacy and security as persistent global challenges.

This concern is magnified in nations leading in AI, with countries like India, Japan and the USA reporting nearly double the rise in security issues relative to countries lagging behind such as Germany, France and Spain.

The increase in AI adoption expands the attack surfaces for many firms, leading to new hurdles like securing AI models, shielding exposed datasets, and ensuring their availability for AI functions.

However, there's a silver lining as the emphasis on cybersecurity as a primary concern has diminished by 17% since last year, hinting at the effectiveness of strategic security measures already in place.

“The organisations leading in advanced analytics and AI are those that have unified and well-cataloged data, robust security and compliance for sensitive information and a clear understanding of how data evolves”, Krish Vitaldevara, Senior Vice President and General Manager at NetApp summarises.

“By tackling these challenges, they can drive innovation while ensuring resilience, responsibility, and timely insights in the new AI era.”

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