Five transformation imperatives. One operating model to deliver them all.
Infrastructure modernization, application re-architecture, developer experience, AI-assisted delivery, and governance at scale — your technology organization faces all five simultaneously. Kyndryl provides the platform, the agents, and the delivery model to execute without trade-offs.
Kyndryl AI Platform Engineering · Executive POV 2025
Near-universal AI adoption with measurable impact and new risk signals.
Returns depend on the underlying system, not just the tools.
24% report high trust while 30% report little or no trust in AI outputs.
Elite performance targets remain the operational bar for speed and stability.
Any team demands assets. Agents generate, personalize, and continuously improve them from production metrics.
Standard domains with clear contracts and service levels.
Compute, network, and data with policy validation.
Build, test, deploy with standards by artifact type.
Dashboards, SLOs, and runbooks as code.
Self-service portal with golden paths, service catalog, and AI-guided onboarding.
Shift-left controls with automated evidence.
Use cases where AI-assisted platforms change economics and risk at scale.
AI-generated landing zones and factory migration waves cut delivery time by up to 40% while reducing misconfiguration risk at scale.
Consolidate fragmented toolchains into a unified, policy-driven engineering platform — faster delivery with guardrails built in from day one.
AI accelerates COBOL-to-cloud translation and iterative refactoring — cutting modernization cycles by 40–60% compared to manual approaches.
Build and operate a Backstage-based IDP with golden paths and AI-guided self-service — reducing cognitive load and accelerating every team on the platform.
AI continuously right-sizes resources, detects cost anomalies before bills land, and automates per-team showback and chargeback reporting.
AIOps reduces alert noise by 85%, accelerates root-cause detection by 50–70%, and automates routine runbooks end-to-end with full audit trail.
Enterprise controls for responsible AI — aligned with EU AI Act, ISO 42001, and leading analyst governance frameworks.
Curated enterprise knowledge base, hybrid RAG with confidence thresholds, and continuous index refresh with stale-data detection.
Policy-as-code in every pipeline stage, automated evaluation suites, ModelOps lifecycle gates, and adversarial red-teaming before every release.
EU AI Act risk classification, SOC 2 Type II, ISO 27001, and GDPR enforced as policy-as-code with continuous compliance monitoring.
Hybrid RAG with confidence scoring and cited evidence — reduces hallucination risk.
Anthropic MCP · 2024Model risk register aligned with EU AI Act tiers, audit trails, and lifecycle controls.
EU AI Act · ISO 42001Retrieval quality gates, automated factuality checks, and human-in-the-loop escalation.
Eval pipelinesKill switches, rate limits, circuit breakers, and immutable audit logs for regulators.
Policy-as-codeEU AI Act, SOC 2 Type II, ISO 27001, and GDPR controls automated as policy-as-code.
EU AI Act · SOC 2 · GDPRRed-teaming, adversarial testing, bias detection, and latency/cost observability.
Red-teaming · EvalKyndryl turns AI adoption into durable operating advantage with platform engineering, governance, and execution.