The operational AI era has begun

In 2026, leaders must shift focus from “what can AI do?” to “how do we run it responsibly?”

Article link: https://open.substack.com/pub/johanosteyn/p/the-operational-ai-era-has-begun?r=73gqa&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

Audio summary: https://youtu.be/vbfL3HGInEI

There’s a quiet shift happening in how serious organisations talk about AI. The excitement is still there, but it’s being replaced by a more sober question: can we actually run this stuff in the real world, reliably, at scale, without breaking trust? A recent Council on Foreign Relations (CFR) article frames 2026 as a decisive phase for AI, shaped less by speculative breakthroughs and more by the hard realities of governance, adoption, and strategic competition. That framing resonates because it reflects what many leaders are already experiencing: AI is moving from “innovation theatre” to operational dependency, and that changes everything.

CONTEXT AND BACKGROUND

The last two years have been dominated by experimentation. Teams ran pilots, bought licences, tried a chatbot, tested document summarisation, and sprinkled “AI” across slide decks. Some of that produced real value. A lot of it produced demos, not outcomes. The difference now is that AI is increasingly embedded into routine workflows: customer support, marketing, software development, analytics, HR processes, and internal knowledge management.

When a tool is experimental, mistakes are annoying. When it becomes infrastructure, mistakes are expensive. They create compliance exposure, security incidents, public embarrassment, and operational failure. And because AI can produce convincing outputs at speed, errors don’t just occur; they scale.

The CFR piece highlights this transition clearly: policymakers are under pressure to turn principles into enforceable rules, while organisations face uneven adoption and significant security and economic consequences as AI spreads. In other words, we are entering the phase where society stops asking “what can AI do?” and starts asking “under what conditions should AI be allowed to do it?”

INSIGHT AND ANALYSIS

Operational AI is not mainly a technology problem. It is a management problem. The hardest questions are boring, but decisive: Who owns the system? What data is it allowed to touch? What are the guardrails? How do we monitor it? What happens when it fails? How do we prove what it did, and why?

This is where many organisations are exposed. They have adopted AI as a feature, not as a system. They have not built basic visibility into where AI is used, what prompts and data flows exist, and what outcomes are being influenced. That makes governance performative. You cannot govern what you cannot see.

A second tension is speed versus control. AI systems evolve rapidly. Models change, vendors update, new capabilities appear, and staff adopt tools informally because they make work easier. The operational question becomes: how do you allow useful innovation without turning your organisation into a patchwork of untracked AI risks?

And then there is the external reality. The CFR article points to governance and strategic competition as key forces shaping AI’s future. In practice, that means regulatory requirements, procurement expectations, and security concerns will increasingly dictate what gets deployed, not just what is technically possible. The winners will be those who can navigate those constraints with discipline, not those who chase every new capability.

IMPLICATIONS

For business leaders, 2026 requires a mindset shift: treat AI like critical infrastructure. Start with an AI inventory, assign accountable owners, define permissible use, and build monitoring. If your organisation cannot answer “where is AI used and for what purpose?” you are not in control.

For risk and compliance teams, move beyond policy documents into operating mechanisms. Create simple controls that work: approval pathways for high-impact use cases, red-team testing for sensitive workflows, incident reporting, and audit logs for key systems. The goal is not bureaucracy; it is resilience.

For employees, the new skill is not only prompting. It is judgement. Knowing when to use AI, how to verify outputs, and when to escalate to a human becomes part of professional competence. As AI becomes normal, disciplined use becomes the differentiator.

CLOSING TAKEAWAY

The operational AI era is not coming. It is already here. The decisive question for 2026 is whether institutions can keep pace with adoption by building real governance, real accountability, and real safety into everyday use. The CFR framing is right: this phase will be defined less by shiny breakthroughs and more by how well we learn to live with powerful systems. In the long run, the organisations that thrive will not be the ones that “use AI”. They will be the ones who can run it responsibly, consistently, and in a way that earns trust.

Author Bio: Johan Steyn is a prominent AI thought leader, speaker, and author with a deep understanding of artificial intelligence’s impact on business and society. He is passionate about ethical AI development and its role in shaping a better future. Find out more about Johan’s work at https://www.aiforbusiness.net