Putting It Into Practice
Executive Technology Radar
This table converts the topic catalog and the emerging-technology radar into a single decision instrument. Current Importance and 2-3 Year Potential are independent judgments: some items are already important but plateauing, others are unimportant today but worth positioning for. Recommended Action is the operative column, and it is deliberately not "Adopt" by default:
- Adopt: fund and deploy now; the evidence and the risk profile both support it.
- Build Capability: not a single deployment decision, but an organizational muscle to build deliberately over the next 1-2 years (platform, governance, or skills).
- Experiment: worth a bounded pilot with a defined kill date, not yet worth enterprise-wide commitment.
- Understand: you need working knowledge and a point of view, but no near-term investment decision is required.
- Monitor: track quarterly; re-evaluate if the evidence changes, but do not staff or fund against it yet.
- Ignore for Now: genuinely not relevant to this organization's current business at this time; revisit only if your business model changes.
| Topic | Current Importance | 2-3 Year Potential | Recommended Action |
|---|---|---|---|
| Enterprise AI operating model (hub-and-spoke design) | High | High | Build Capability |
| AI portfolio management & build/buy/configure discipline | High | High | Build Capability |
| Multi-model strategy & vendor lock-in mitigation | Medium | High | Build Capability |
| Core agentic AI architecture (loops, orchestration, tool use) | High | High | Adopt |
| Agent autonomy levels & human approval gates | High | High | Build Capability |
| Model Context Protocol (MCP) | High | High | Adopt |
| Agent2Agent (A2A) protocol | Low | Medium | Monitor |
| Coding agents / agent-directed engineering | High | High | Adopt |
| Autonomous software factories (fleets, minimal human review) | Low | Medium | Experiment |
| AI-generated code security risk & secure development controls | High | High | Build Capability |
| Engineering skill-mix shift & junior pipeline redesign | Medium | High | Understand |
| Enterprise AI assistants & enterprise search | High | High | Adopt |
| Agentic workflow automation vs. RPA/BPM | Medium | High | Experiment |
| RAG & enterprise knowledge retrieval | High | High | Adopt |
| Permissions-aware retrieval & data governance | High | High | Build Capability |
| Frontier & reasoning models (as a consumer, not a builder) | High | High | Understand |
| Open-weight models | Medium | Medium | Experiment |
| Context engineering as a system-design discipline | High | High | Build Capability |
| AI gateway / model gateway architecture | Medium | High | Build Capability |
| AI evaluation & golden datasets | Medium | High | Build Capability |
| Hallucination & groundedness controls | High | High | Build Capability |
| OWASP LLM Top 10 & prompt-injection defense | High | High | Adopt |
| Agent non-human identity & least privilege | Medium | High | Build Capability |
| NIST AI RMF / ISO 42001 alignment | Medium | High | Build Capability |
| EU AI Act compliance readiness | Low-Medium | High | Understand |
| AI IP & copyright risk management | Medium | Medium | Understand |
| Token economics & cost governance | Medium | High | Build Capability |
| AgentOps / observability & incident response | Medium | High | Build Capability |
| AI-native product UX (progressive autonomy, citations) | Medium | High | Experiment |
| AI champions & adoption change management | High | High | Adopt |
| Outcome-based AI value measurement | High | High | Build Capability |
| Autonomous software development (issue-to-PR-to-deploy, no human in loop) | Low | Medium | Experiment |
| Self-healing software | Low | Medium | Monitor |
| Agent marketplaces, discovery, reputation & identity standards | Low | Medium | Monitor |
| Agent payments / agentic commerce (incl. agent-to-agent) | Low | Medium | Monitor |
| Persistent digital workers & autonomous departments | Low | Medium | Understand |
| Synthetic organizations | Low | Low/Uncertain | Ignore for Now |
| AI-native ERP & CRM | Low-Medium | Medium | Monitor |
| Generative UI & software generated on demand | Low | Medium | Monitor |
| Natural-language programming ("vibe coding" for non-developers) | Low-Medium | Medium | Experiment |
| Edge AI & local/on-device models | Low | Medium | Monitor |
| Embodied AI & robotics | Low | Low (for this business) | Ignore for Now |
| World models & AI-enhanced digital twins | Low | Uncertain | Ignore for Now |
| Synthetic data for training/eval | Low | Medium | Monitor |
| AI for scientific discovery | Low | Low (for this business) | Ignore for Now |
| Real-time multimodal agents (voice + vision + action) | Low | Medium | Monitor |
| Autonomous cybersecurity (AI-driven defense/response) | Medium | High | Experiment |
| Machine customers (Gartner's term) | Low | Medium/Uncertain | Monitor |
A pattern worth naming explicitly: nothing on this list scores "Adopt" purely because it's new. Every Adopt row already has production-grade tooling, a body of evidence, and organizations your size running it successfully. Several genuinely important developments (autonomous departments, agent-to-agent commerce, embodied AI) sit at Monitor or Ignore for Now not because they're unimportant in the abstract, but because the evidence for enterprise deployment at your scale doesn't exist yet. Funding them now would be funding a bet, not a capability.