If 2024 was the year organisations experimented with AI, 2025 was the year AI entered everyday work.

2025: the year of the Copilot

In 2025, AI stopped being something only innovation teams talked about and became something millions of people used daily. The defining pattern was the rise of the copilot.

Copilots brought AI directly into familiar tools and workflows. Developers used them to accelerate coding and testing. Analysts used them to interrogate data. Operations teams used them to summarise, draft, analyse and support decision-making without leaving the systems they already relied on.

This mattered because it lowered the barrier to adoption. AI didn’t require wholesale system replacement or major organisational change. It worked alongside people, improving productivity at an individual and team level.

But 2025 also revealed the limits of this model. Copilots delivered quick wins, but the value plateaued where data was fragmented, integration was weak, or outputs couldn’t be trusted at scale. Many organisations discovered that access to AI wasn’t the hard part. Making AI useful, reliable and repeatable was.

That learning sets the tone for 2026.

Our predictions for 2026

1. Data and integration become the real battleground

In 2026, attention shifts decisively from models to foundations.

Organisations will focus on standardisation, metadata management and ontology alignment. Not because it’s fashionable, but because AI only performs well when it understands what data means, where it comes from and how it relates across systems.

Disconnected data estates, inconsistent definitions and brittle integrations will increasingly be seen as blockers to progress. The organisations that move fastest will be those that invest in integration as a strategic capability, not a one-off technical exercise.

This is where platforms focused on data integration, context and operational intelligence, including players like N8N and UIPath, and a growing set of competitors, will continue to gain traction. Their value lies in helping organisations connect complex environments and reason across them, rather than simply visualising data.

2. Enterprise AI access scales, quietly and broadly

2026 will be the year AI access becomes enterprise-wide, not just concentrated in technical teams.

We expect to see widespread adoption of AI in areas such as documentation, triage, analysis and support functions, including the continued rise of AI scribes and similar tools that reduce administrative burden and improve information quality.

Crucially, this expansion won’t be driven by flashy features. It will be driven by governance, trust and usability. Organisations will prioritise AI that works within existing controls, respects data boundaries and integrates cleanly with core platforms.

AI becomes less visible, but more embedded.

3. Automation moves from ambition to execution

In 2025, many organisations talked about automation. In 2026, more will deliver it.

The difference will be lightweight, flexible integration. Instead of large-scale system replacement, organisations will orchestrate automation across existing applications, stitching together workflows using AI where it adds clarity, speed or consistency.

This approach reduces risk, shortens time to value and fits the reality of complex estates. Automation becomes incremental, composable and easier to adapt as needs change.

The result is progress that compounds, rather than transformation programmes that stall.

The rise of small language models

Alongside all of this, 2026 will mark a shift toward small language models.

Rather than defaulting to the largest possible model, organisations will increasingly deploy smaller, task-specific models that are cheaper to run, easier to control and better suited to defined use cases.

This matters for several reasons. Small models can be trained or tuned on narrower domains. They are easier to explain and govern. They reduce dependency on external platforms and lower operational cost.

Most importantly, they support a more deliberate approach to AI, where capability is matched to need rather than driven by novelty.

How this aligns with AI maturity

When we look across organisations adopting AI, the patterns we see in 2026 map closely to a clear maturity journey.

Early-stage organisations continue to focus on Assist use cases. Copilots, summarisation, drafting and decision support remain valuable, particularly where guardrails and safe experimentation are well established. These capabilities improve day-to-day productivity and help teams build confidence in working alongside AI.

As maturity increases, organisations move into Augment. This is where 2026 really accelerates. AI becomes grounded in trusted internal data and integrated into core systems. Standardisation, metadata management and ontology alignment play a critical role here, enabling AI to operate with context and accuracy rather than inference alone.

With strong data foundations in place, organisations are able to Automate. End-to-end workflows are redesigned so AI supports triage, prioritisation, reporting and operational coordination across existing applications. Lightweight integration becomes the enabler, allowing automation to scale without destabilising established environments.

At the most advanced stage, Agentify, AI operates alongside teams with defined autonomy and accountability. Smaller, task-specific language models and rule-bound agents handle discrete responsibilities while remaining transparent and auditable. Human oversight remains central, with AI acting as an operational multiplier rather than a replacement.

This progression is not about rushing to the final stage. Each step builds on the last, and value comes from moving deliberately up the maturity curve in line with organisational readiness and risk appetite.

What this means overall

2026 won’t be about chasing the next breakthrough model. It will be about making AI dependable.

The organisations that succeed will be those that invest in data clarity, integration, governance and practical automation. They will treat AI as part of their operating model, not a bolt-on.

The shift from experimentation to execution is well underway. 2026 is the year it becomes unmistakable.

If your organisation is exploring early productivity gains, looking to ground AI in your data, automate critical workflows or introduce agent-based systems safely, Answer Digital can help you move forward with confidence.

We work with organisations at every stage of AI maturity, combining strategy, engineering and operational experience to turn ambition into execution.

If 2026 is the year you want AI to become part of how your organisation actually runs, we’d love to start that conversation.