Privacy Risks Scaling Businesses Need to Get Ahead of in 2026

Published by Annabelle Ilsley on Jan 6, 2026 9:34:40 AM

In 2025, a few privacy themes came up again and again for scaling businesses.

AI moved quickly from isolated use into day-to-day operations. Regulators increased their focus on how personal data is actually being used in practice. Breaches continued to be driven by familiar causes like human error and phishing. And for many scale-ups, growth - new products, new tools, new markets - made privacy harder to manage consistently.

So, what can we expect to see in 2026?

Our privacy experts have broken down the key trends for 2026, and what they mean for scaling businesses.

AI governance for scale-ups: why informal AI use is a privacy risk

For most scale-ups, AI didn’t arrive as a single, well-planned initiative, it crept in. Through productivity tools, customer support platforms, analytics, marketing software, and teams experimenting to move faster. By the end of 2025, many businesses found that AI was already part of day-to-day operations, even if no one had formally signed it off.

The challenge going into 2026 isn’t whether AI is being used, it’s whether businesses actually have visibility and control over how personal data flows through AI tools.

From a privacy perspective, the same questions keep coming up:

What personal data is being used in AI systems, and for what purpose?
Where is that data going, and who has access to it?
What safeguards are in place when AI tools are trained, integrated, or updated?
And crucially, who owns the risk if something goes wrong?

Regulators are paying closer attention to these issues, but they’re not the only ones. Customers and investors are increasingly asking direct questions about AI use as part of security reviews, procurement processes, and due diligence.

Preparing for AI risk in 2026

For most scale-ups, the priority isn’t introducing heavy-handed controls. It’s getting a better grip on how AI is actually being used across the business.

Here’s a few practical steps worth focusing on:

Start with visibility. Get a clear view of where AI is already in use - across teams, products, and vendors. Most risk sits in the unknowns.
Treat AI like other higher-risk processing. Where personal data is involved, AI shouldn’t sit outside existing privacy processes. Assess it in the same way you would other higher-risk activities.
Be clear on ownership. Decide who is responsible for oversight and escalation. AI risk often grows because no one clearly owns it.
Keep governance proportionate.
Simple guardrails, documented decisions, and clear escalation routes are usually enough. The aim is control, not friction.
Have a clear AI policy in place. A simple, practical AI policy helps set expectations around how AI can be used, what’s off-limits, and how risk is managed - and gives teams something concrete to point to when questions come up.

You can download our AI Policy template for free here >>

Data breach responses are not only a privacy issue, but a commercial one too

For most businesses, the causes of data breaches haven’t changed much.

Incidents are still largely driven by human error, phishing, weak access controls, and misconfigurations. What has changed is how quickly those incidents escalate, and how many people are paying attention when they do.

Over the past year, breaches have increasingly triggered more than just internal incident response. Customers are asking detailed follow-up questions, procurement teams are getting involved, investors want reassurance, and in some cases, boards expect clear explanations about what happened and what’s been done to prevent a repeat.

From a privacy perspective, breaches now tend to bring up the same issues:

Was the incident detected quickly?
Were roles and responsibilities clear?
Was the response documented and consistent?
Did staff receive adequate awareness training?
And can the organisation show that reasonable measures were already in place?

How can scale-ups prepare for data breaches in 2026?

Managing breach risk is about getting two things right: reducing the likelihood of a breach, and being ready to respond if one does happen. Even with strong prevention in place, breaches can and do still happen.

A few things to focus on:

Regular training and awareness. Keep training frequent, practical, and easy to engage with, so teams know how to spot common risks and feel confident raising concerns early.
Sensible access controls. Limit access to those who need it, and review permissions as roles and teams change.
Clear ownership and escalation. Be explicit about who leads a breach response, who makes decisions, and who needs to be involved.
A clear, documented response process. Have a data breach response plan that’s easy to find, regularly reviewed, and tailored to how your business actually works - not a generic template that isn’t applicable.
Well-organised evidence. Keep records of controls, training, and decisions easy to access, so they’re available when scrutiny increases.

Children’s data risk applies to more products than most teams realise

For many scale-ups, children’s data still feels like a niche issue. Something that only applies if you’re explicitly building products for kids. In reality, that boundary has become much less clear.

Regulators have continued to focus on how children’s data is handled, particularly where products or services are likely to be accessed by under-18s, even if they aren’t the intended audience. The shift isn’t about new rules so much as how expectations are being applied. There’s less weight placed on stated intent, and more attention on product design, default settings, and whether risks to children have been properly considered.

From a privacy perspective, the same questions tend to come up:

Could children realistically use this product or service?
What personal data would they be sharing if they did?
Are default settings appropriate for younger users?
And is there evidence that children’s data has been actively considered, rather than assumed away?

Age assurance adds another layer of complexity. Verifying age can itself require collecting additional data, sometimes sensitive data, which creates a tension between protecting children and minimising data collection. Getting that balance wrong can introduce new risks rather than reduce them.

Managing children’s data risk

For most scale-ups, the issue isn’t that they’re handling children’s data badly, it’s that they haven’t clearly decided whether children fall into scope at all.

Here’s a few practical steps worth focusing on:

Be realistic about your audience. Look at who could actually use your product, not just who it’s marketed at. If children could reasonably access it, that needs to be reflected in your risk assessments.
Consider children early in product decisions. New features, onboarding flows, and default settings are often where risk creeps in. Thinking about children’s data at design stage is far easier than retrofitting controls later.
Document your reasoning. Whether you conclude that children are in scope or not, being able to show how you reached that decision matters. Silence or assumptions are harder to defend.
Be cautious with age assurance. Where age checks are needed, make sure they’re proportionate and don’t introduce unnecessary data collection or security risk.

Evidence matters more than good intentions

Privacy decisions are made constantly across a business. They happen when tools are approved, data is reused, risks are assessed, or trade-offs are made. In most cases, those decisions are reasonable, but the problem is that they’re not always easy to evidence later.

What’s changing is how those decisions are assessed under scrutiny.

Across regulatory engagement, customer audits, and incident response, organisations are expected to show how decisions were made, what risks were considered, and what actions followed.

Where scale-ups struggle is rarely because the decision itself was unreasonable, it’s because the rationale isn’t clearly documented or easy to pull together later.

What good privacy evidence looks like in practice

Evidencing privacy decisions doesn’t mean documenting everything. It means being clear about what does need to be recorded, and doing it consistently.

A few things to focus on:

Record key decisions when they’re made. Short, factual records are enough. Reconstructing decisions later is much harder.
Use a consistent approach to risk assessment. Putting every tool or use case through the same process leads to more accurate assessments, fewer gaps, and more confidence that risks haven’t been missed.
Show follow-through. Evidence isn’t just the decision, it’s what changed as a result, whether that’s controls, training, or processes.
Keep evidence easy to access. If it takes days to find, it won’t stand up well under scrutiny.

What the Digital Omnibus signals for scaling businesses

In 2025, the EU’s Digital Omnibus proposals signalled a shift in how digital regulation may be applied going forward.

The focus isn’t on introducing entirely new privacy obligations, but on simplifying and clarifying how existing rules work in practice, particularly where GDPR, the AI Act, and other digital laws overlap. This is about reducing ambiguity, not reducing accountability.

What isn’t changing is the expectation that businesses understand their risks, make proportionate decisions, and can explain how privacy is managed day to day. Clearer rules leave less room to rely on broad interpretations or generic compliance statements.

What does this mean for scale-ups heading into 2026?

The Digital Omnibus isn’t a reason to pause privacy work. It’s a prompt to focus on the fundamentals.

Don’t assume simplification means a lighter touch. Even if rules are clarified or streamlined, regulators will still expect you to manage risk properly and make good decisions.
Be ready to show how the rules work in practice for your business. Scrutiny is less about debating legal interpretation, and more about explaining how privacy is actually applied across your tools, products, and processes.

Putting the right privacy foundations in place

The trends we expect to see in 2026 aren’t new, but they’re becoming harder to manage without the right foundations in place.

For scaling businesses, the focus should be on putting the right foundations in place early, so risk can be managed consistently as the business grows.

To help you get there, we’ve put together a free Privacy Essentials Pack with the core policy templates you need to kickstart a practical, proportionate privacy programme - without starting from scratch.