Trainings Headling
The report's data reveals a fundamental tension. AI is everywhere. Daily AI usage has become standard, with 88% of respondents reporting regular use, for code generation (75%) and documentation (71%). While 73% of respondents say AI plays a large role in organizational goals, and 90% expect it to transform their future. Yet many are still stuck turning individual AI experiments into real business value as usage remains tactical, driven by individual experimentation rather than strategic value.
Platform engineers are uniquely positioned to bridge these gaps. This report will highlight this opportunity, and the challenges that come with it, addressing the following:
How is the intersection of AI and platform engineering driving the AI revolution? By using AI to empower Internal Developer Platforms (IDPs) through smarter automation, natural-language interfaces, log analysis, and workflow optimization. Alongside the building of Platforms for AI, where purpose-built foundations enable the efficient deployment and scaling of AI/ML workloads, complete with specialized hardware, secure data infrastructure, and high-performance services.
Is “prompt fatigue” the new cognitive overload? Uncoordinated tool proliferation, overly restrictive policies, AI hallucinations bottlenecks: despite the technology's promise, 59% of teams face the skill gaps necessary to adopt and implement fast.
The disconnect between AI potential and realized value: The gap between individual productivity gains and measurable organizational ROI reveals a fundamental disconnect. Emphasized by the “Implementation plateau” where despite widespread usage, organizations struggle to move beyond basic applications.
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