Ask any company and they’ll say, “Yes, we’re doing AI.”
But what does that really mean?
In most cases, it means they’ve tested copilots. Maybe launched a few agents. Experimented inside individual teams. And in many cases, they’ve probably secured enough early wins to prove AI value and keep investing.
That’s what 2024 and 2025 were about: testing, piloting, experimenting. But that phase is ending.
So what happens with AI in 2026? Will it finally change how teams work every day?
2026 is the year AI stops being something teams try and starts being something companies have to run. And that changes what work looks like far more than any single new tool or model.
It’s the year of AI orchestration and governance. How you scale from one agent to fifty without breaking your systems, your data, or your decision-making.
We asked a few Trayers how they see AI changing the way they work (and how it will impact others in their role) in 2026. They come from different parts of the business, but their answers overlap more than you might expect.
Here’s how they see AI changing day-to-day work in 2026.
How will AI impact the CEO’s role in 2026?
AI will speed up decisions and expose broken processes
“The power of the data analysis that [AI] can do provides entirely new insights that you can react upon as a CEO… In 2026, it’s moving on from that initial experimentation phase and starting to look at how you can have real meaningful impact across the entire organization.” — Rich Waldron, Co-founder and CEO
When AI enters the executive workflow, the first thing it changes is speed. Time to insight shrinks and context is easier to gather. Decisions move much faster.
And that sounds like a clear win (and it is) but there’s a catch. AI doesn’t just accelerate good processes. It accelerates all processes.
When data is fragmented, AI makes that fragmentation obvious. When teams operate on different assumptions, AI surfaces conflicting answers faster than ever. And when workflows are held together by manual checks, AI exposes how fragile they actually are.
For CEOs in 2026, the top challenge is making sure AI-driven decisions across the business stay aligned. That requires orchestration across systems, teams, and data.
This is where leadership shifts from encouraging innovation to designing how intelligence is applied throughout the company. When AI becomes part of daily decision-making, coherence matters more than speed alone.
How will AI impact the CTO’s role in 2026?
Governance will stop being theoretical once agents touch real systems
“2026 is going to be about governance and oversight and security, ensuring that as we see more AI sprawl… that we have a good view of what’s going on across the business.” — Alistair Russell, Co-founder and CTO
As soon as AI agents move beyond summarizing information and start acting inside systems, governance becomes the main challenge.
By 2026, most enterprises will be running agents that read and write data, trigger workflows, and interact with production systems. That’s when the lack of visibility and control turns into risk.
This should feel familiar to seasoned tech leaders. API sprawl. SaaS bloat. Cloud creep. Each wave started with speed and flexibility, then ran into sprawl and security problems once adoption outpaced oversight. The catchy name usually came after the damage.
Is it too early to name one for AI? How about agent anarchy?
It fits. AI agents raise the stakes because they make decisions and take actions, and that requires oversight. For CTOs, governance in 2026 isn’t about adding policy after the damage has been done. It’s about preventing agent anarchy in the first place.
Orgs must build access control, authentication, observability, and auditability directly into the architecture. Without that foundation, scaling agents safely becomes nearly impossible.
How will AI impact the Ops role in 2026?
AI ops will emerge as a new discipline, moving beyond one-off agents
“2025 was really the testing ground… and 2026 is going to be about taking those learnings and operationalizing AI.” — Stephen Stouffer, Director of Automation Solutions
Most organizations don’t hit friction with their first or second agent. They hit it later when agents start multiplying.
Early success will hide long-term complexity. As agent count grows, teams start to see duplicated logic, inconsistent data access, unclear ownership, and brittle integrations. What worked as a prototype starts to break as a system.
This is why 2026 is also the year AI ops becomes a real discipline.
Running agents at scale requires monitoring, versioning, reuse, incident response, and clear ownership models. Many teams will learn that building the agent is actually the easy part. Teams will have to know how to operate them too.
This is where orchestration becomes practical rather than conceptual, and it’s how orgs move from isolated wins to repeatable execution.
How will AI impact the GTM role in 2026?
Teams will need orchestration under the hood to drive revenue outcomes
“For sales leaders, agents will take on the messy operational work the team still loses hours to… but the only way that actually works is if the data is stitched together behind the scenes.” — Nate Gemberling, Head of Sales
AI doesn’t magically reconcile fragmented systems. If CRM data, product usage, marketing signals, and support history live in silos, agents simply surface inconsistent answers faster.
In 2026, the GTM teams that win won’t be the ones with the most agents. They’ll be the ones with agents that are orchestrated across the stack. When that foundation exists, leaders spend less time cleaning up data and more time coaching, strategizing, and improving predictability.
In GTM, orchestration is the difference between leverage and noise.
How will AI impact the Product Manager’s role in 2026?
Teams will ship faster, but fundamentals still matter
“AI lets us get to a prototype or a first version much faster… but you still need the fundamentals: understanding the customer, the problem, and the data.” — Tom Walne, Director of Product
AI dramatically shortens the distance between idea and prototype. Product teams can test flows, explore concepts, and iterate faster than ever before.
But when experimentation becomes cheap, it’s easy to mistake motion for progress. In 2026, product leaders will feel pressure to ship quickly while still building systems that hold up in production.
This is where governance shows up in product work. Clear data contracts, shared components, and architectural discipline become more important as iteration speeds up.
AI removes friction from early development, but it does not remove the need for judgment.
In 2026, we go from launching agents to running them at scale
AI is already changing work. That much is obvious.
What’s less obvious is that what really changes is responsibility.
Once AI agents are embedded across the business, organizations have to answer harder questions: Who owns them? How do they interact? How do you know they’re behaving correctly? How do you scale without losing trust?
The companies that get this right will have orchestrated, governed systems that let humans and agents work together without friction. That’s how you get from one agent to fifty. And that’s what will actually change work in 2026.
