The Year Ahead in AI, Enterprise Software, and the Future of Work

2025 has been the year we stopped debating whether generative AI matters and started living with it.

We moved beyond simple autocomplete and clever demos. We began to see AI as a partner, something that thinks, generates, and in some cases acts across workflows, not just responds to prompts. That shift from tool to partner is where the real value begins.

This moment feels familiar. Every major technology shift follows a similar arc. Automation reshapes work, disrupts old models, and creates new opportunities we cannot fully define at the outset. That process has a name: creative destruction. AI is simply the latest, and perhaps most consequential, chapter.

From Experimentation to Real Systems

Over the past year, many teams crossed an important threshold.

We saw a move from curiosity-driven experimentation to the construction of real agentic systems, systems that execute tasks with context, memory, and intent. Developers started running increasingly capable models locally on their laptops, optimizing for privacy, speed, and control.

Perhaps most importantly, we shifted away from chaotic prompt tinkering toward something more durable: spec-driven engineering. Structured workflows. Agentic IDEs. Disciplined iteration. Clear interfaces between humans and machines.

The lesson is simple but powerful.

AI is not replacing work. It is transforming how work happens.

The future belongs to teams and leaders who treat AI as a strategic delivery partner, not just another gadget in the toolbox.

What Excites Me Most About 2026

As I look ahead, three themes stand out.

1. Enterprise Software, Reimagined

We are entering an era where AI is embedded at the workflow level, not bolted on as a feature or an assistant panel.

The next generation of enterprise platforms will use AI as the default interface. They will anticipate needs, enforce context, and automate outcomes end to end. Organizations still layering AI on top of legacy user experiences will struggle to keep up.

2. “Human in the Loop” Becomes a Discipline

Routine work will continue to disappear.

What grows in importance are roles where humans define why something should be done, what success looks like, and how outcomes should be stewarded. The combination of human judgment and AI execution is a genuine superpower, but only if it is designed intentionally.

Human-in-the-loop is not a checkbox. It is a craft.

3. Autonomy With Accountability

Here is a less popular take.

Teams that slow down to build governance, guardrails, and oversight will outperform those chasing speed alone. As AI agents gain autonomy, thoughtful accountability becomes a competitive advantage, not a bottleneck.

In the long run, trust compounds faster than velocity.

A Final Thought for Builders and Leaders

If you are building or leading teams right now, focus on learning systems and tight feedback loops. Measure outcomes, not activity. Resist the temptation to adopt every shiny tool.

The winners in 2026 will not be the teams that used AI the most.

They will be the teams that built with it in disciplined, intentional ways.

What is your team betting on for 2026? I would love to hear what patterns you are seeing.