Eighty-seven percent of respondents say C-suite leaders involve themselves regularly in tech decisions.
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Google’s $32 billion acquisition of cloud security firm Wiz made headlines for its scale, but it also reflects a deeper shift that’s underway in enterprises around the globe: Security is no longer just an IT priority. It’s a C-level concern embedded in transformation, compliance and AI strategy.
To understand how enterprise tech buying is evolving, the Forbes Research 2025 Enterprise Technology Purchasing Survey polled over 1,000 global business and technology leaders in October 2024.
Key findings:
- Cybersecurity ranks as the No. 1 external factor shaping enterprise tech strategies over the next five years, cited by 83% of leaders — more than AI regulations (82%), innovation cycles (81%) and economic uncertainty (75%).
- While IT leads 59% of tech purchases today, that’s changing. By 2028, 53% of enterprise tech investments will be led by lines of business, indicating a major shift in purchasing dynamics.
- 87% of respondents say C-suite leaders involve themselves regularly in tech decisions that impact business strategy, 83% of C-Suite executives also say they participate in a purchasing committee and 42% report meeting directly with vendors.
- 84% cite data privacy and security as top purchasing criteria.
- Only 25% are very satisfied with the security of their AI systems.
- 54% say internal coordination around purchases is becoming more difficult, suggesting a need for unified governance as tech decisions decentralize.
The data reveals a pattern: As enterprises scale investments in AI and cloud, the C-suite is focusing more heavily on security and cross-functional alignment.
Executive leaders are also bullish on artificial intelligence with 42% planning major investments in AI and machine learning this year.
But there’s a growing disconnect between where enterprises are spending and where they are ready. As noted above, security satisfaction levels are low, and 85% cite a lack of internal expertise as a major challenge in AI implementation.
Prioritizing speed over protection may cause data to become vulnerable, a risk that enterprises can mitigate by putting security and investing in AI know-how first.