2026 will not be defined by technological breakthroughs.

It will be defined by how institutions respond to technologies they have already deployed—often without sufficient clarity about ownership, authority, or consequence.

Artificial intelligence is no longer emerging. It is embedded. It now shapes decisions about capital, labor, access, and risk. What has changed is not capability, but accountability. The distance between automated decisions and real-world consequences is closing.

This is not a technical moment.
It is a leadership one.

The Shift That Matters Now

For years, AI discussions focused on potential: what systems might do, how work could change, whether regulation would arrive. That phase is over.

In 2026, AI is operational inside many organizations. It approves, flags, ranks, allocates, and denies. And because it is now part of ordinary decision-making, it can no longer be governed as an innovation experiment or a siloed ethical concern.

The relevant questions have changed.

Not:

• Is the model advanced?

• Is the system explainable?

• Are we keeping pace with competitors?

But:

• Who owns the outcome of this decision?

• Who has authority to intervene when it fails?

• What incentives shape how this system is used?

• Where does responsibility actually sit?

These are governance questions. They determine whether AI strengthens institutions or exposes their weaknesses.

What This Site Will Focus On

This site will not attempt to track every development in artificial intelligence.

It will focus on the points where AI intersects with power, accountability, and institutional design—because that is where failure, and leadership, become visible.

Specifically, the work here will examine:

• How responsibility diffuses as AI systems gain authority

• Why silence emerges before ethical or operational failure

• How incentives undermine stated values

• Where governance breaks between strategy and execution

• Why regulation follows capital and liability, not technical elegance

These are not abstract concerns. They are patterns already shaping outcomes.

What This Work Is (and Is Not)

This is not advocacy for slowing technology, nor is it enthusiasm for deploying it faster.

It is not interested in hype cycles, tool comparisons, or surface-level ethics. And it is not concerned with AI as spectacle.

The focus is accountability in practice:

• how decisions are actually made,

• who benefits from them,

• and who is expected to answer when they fail.

That requires looking beyond models and into organizational behavior, leadership incentives, governance structures, and decision rights under pressure.

Technology does not remove responsibility.
It concentrates it.

The Leadership Test of 2026

As AI systems become inseparable from everyday operations, leadership will be judged less by intent and more by structure.

Transparency will not substitute for ownership.
Alignment will not substitute for authority.
Automation will not substitute for judgment.

The organizations that hold will be those that make responsibility explicit—before it is imposed from the outside by regulators, courts, or public scrutiny.

This year will test whether leadership is willing to stand in front of its systems rather than behind them.

Closing

2026 will not be remembered for the tools it introduced.

It will be remembered for whether institutions were willing to accept accountability for decisions they had already delegated.

The work here begins from that premise.

— Viktorija Isic