Why generative AI has overtaken cybersecurity in the enterprise stack

Generative AI has now overtaken cybersecurity as the top spending priority for global technology leaders, marking a significant shift in how companies are allocating their technology budgets. According to Amazon Web Services’ comprehensive Generative AI Adoption Index, which surveyed over 3,700 senior IT decision makers across nine countries, 45% of organizations now prioritize generative AI investments over traditional security tools. This fundamental reshaping of technology spending patterns signals AI’s transition from experimental technology to essential business infrastructure.

The big picture: Generative AI adoption has reached critical mass, with 90% of organizations now deploying the technology and 44% progressing beyond experimentation into production environments.

• Organizations conducted an average of 45 AI experiments in 2024, though only about 20 of these are expected to reach end users in 2025.
• The move from experimentation to production comes as companies recognize AI’s potential for competitive advantage, though the path to full implementation remains challenging.

Behind the numbers: Companies are restructuring their leadership and talent strategies to accommodate AI’s growing importance in their operations.

• 60% of organizations have appointed dedicated AI executives to oversee strategy and implementation.
• An overwhelming 92% of organizations plan to hire AI talent in 2025, while 56% have already developed formal generative AI training programs.

Key challenges: Despite widespread adoption, organizations face significant hurdles in moving AI initiatives from experimentation to production.

• 55% of respondents cite talent shortages as the primary barrier to production deployment, highlighting the competitive market for AI expertise.
• The gap between experimentation (45 initiatives on average) and successful deployment (around 20 expected to reach users) indicates ongoing implementation difficulties.

By the numbers: Global AI adoption shows notable regional variations, with developing economies often leading in implementation.

• India leads global adoption with 64% of organizations prioritizing AI investment.
• South Korea follows closely at 54%, while the United States aligns with the global average at 44%.

Strategic approaches: Most organizations are taking pragmatic approaches to AI implementation rather than building solutions from scratch.

• Only 25% of organizations plan to develop AI solutions entirely in-house.
• 58% will build custom applications on pre-existing models, leveraging foundation models while adding proprietary elements.
• 65% will rely on third-party vendors for AI implementation, suggesting many organizations prefer to outsource technical complexity.