11 tips for changing habits and getting AI ready_

Updated March 2026

Key takeaways_

Building AI readiness is primarily a people challenge, not a technology one — habits, confidence and clear guidance drive adoption.
Small, structured changes (working groups, clear policies, intentional licensing, documented use cases) accelerate sustainable AI usage across teams.
Businesses that support experimentation, strengthen prompting skills and measure impact see faster performance gains and higher long‑term ROI from AI.

AI is moving faster than most organisations can keep up with. While leaders are under pressure to unlock productivity gains, reduce costs and stay competitive, the biggest blocker isn’t the technology itself – it’s people. Staff don’t always know where to start and habits are hard to change.

Getting AI-ready isn’t about rolling out a tool and hoping for the best. It’s about shifting behaviours, creating safe spaces to experiment, and giving teams the confidence to use AI in their day‑to‑day roles. The good news: with the right structure, this can be done gradually, sustainably and without overwhelming anyone.

In this guide, we share 11 practical, field-tested tips to help your organisation build lasting AI habits, accelerate adoption and prepare your teams for the opportunities ahead.

What are the barriers to AI adoption?

Even with the growing pressure to adopt AI, many organisations still struggle to get it embedded into day‑to‑day work. And this is largely due to people. And leaders are often in the dark, with more than half (59%) believing their employees collaborate with AI every day, yet only 42% of employees report actually doing so.

Key reasons for an aversion to AI include:

Not knowing how to use the technology
Not having relevant use cases to try
Fears around job displacements
Fears around ethics and security
Lack of time to experiment

And even when people do use AI, there’s no guarantees they’re using it correctly. According to research:

81% of employees use unapproved AI tools and 45% will find workarounds to use even blocked tools
44% of workers admit using AI improperly at work and 46% say they’ve uploaded sensitive company information to public platforms

When staff use AI tools that aren’t safe, or in irresponsible ways, your organisation becomes exposed to data breaches, non-compliance and reputational damage.

If you want to utilise AI in a way that solves challenges, boosts performance and avoids risk, working with your teams to change behaviours and improve adoption safely is crucial.

Preparing for AI_

Before you start encouraging staff to use AI, your organisation needs the right foundations in place. Good preparation reduces risk, avoids confusion, and ensures AI is introduced in a way that’s secure, ethical and aligned to your long‑term goals. Here are the three steps every business should take before rolling out AI.

1. Assess your AI readiness_

Bringing AI into your organisation represents a meaningful shift, so it’s vital to understand how prepared you are. Start by getting clear on the impact you expect AI to have: the problems it will solve, the gains you want to unlock and how it will support your wider strategy.

Next, look at your current processes and data. If your organisation is heavily manual, AI adoption may require more change than if you already use automated workflows. By mapping how much disruption and uplift is expected, you can introduce AI at a pace that feels manageable rather than overwhelming.

You should also consider the ethical implications of AI: how it affects employees, customers and stakeholders, what data you’re comfortable sharing with AI tools and how you’ll maintain compliance. Preparing your data (including appropriate labelling and access controls) ensures AI can be used safely from day one.

Our AI Readiness Assessment gives you a clear picture of how prepared your organisation is and helps you structure your data and processes into a practical, achievable roadmap.

2. Find the right tools_

Choosing your AI tools is both a technical and strategic decision. Consider cost, capability, accuracy, ease of use and alignment with the outcomes you’re aiming for.

Data privacy is crucial at this stage. Some tools are open models that learn from your data and may share it across their wider ecosystem. Others, like Microsoft Copilot, keep your data secured within your organisation, helping maintain compliance and preventing accidental data exposure.

Selecting the right tools early on creates confidence and reduces barriers for staff, supporting smoother adoption across your teams.

3. Outline your AI policy_

A clear AI policy is essential to ensure staff use AI safely, ethically and consistently. This policy sets expectations, eliminates ambiguity and gives people the confidence to experiment without overstepping boundaries.

Your policy should answer core questions such as:

How should people use AI — and what should they avoid?
What data can be shared with AI tools, and what must remain protected?
Which roles are permitted (or expected) to use AI?
Are only approved tools allowed, or is broader exploration acceptable?
How will AI‑generated output be reviewed and quality‑checked?

Once defined, communicate your policy clearly across the organisation so everyone understands how to use AI responsibly and effectively.

What’s involved with a culture that boots AI adoption_

Getting everyone on board with AI doesn’t happen overnight. While the journey will be unique to every organisation, there are some common threads that boost success: specifically the right culture, leadership and guidance. We’ve put together some stats, based on leading research from Microsoft, to guide your AI adoption approach.

Engaged employees are 2.6x more likely to support AI being integrated in their workplace. So, it’s wise to use your most engaged employees as your AI advocates to encourage usage across teams.
Up to 43% of how AI-ready an individual is can be explained by their previous experience with change. Having strong change management processes and good communication can drive AI readiness success.
83% of employees at high-performing organisations say they have opportunities to integrate AI into their work, while only 56% of employees at typical organisations say the same. Giving your staff more chances to utilise AI in their daily work can therefore drive performance.
High-performing organisations provide far more access to AI tools than typical organisations. So, allowing your staff to use AI tools rather than discouraging them, can provide greater rewards.

These stats show the correlation between how AI change is managed and the positive benefits businesses experience, making your approach critical. Creating a safe environment where people have access to AI tools, support and practical integration opportunities are critical. Next, let’s dive into some top tips for bringing that to life.

Our top tips for changing AI habits_

1. Lead from the top_

Successful AI adoption starts with visible, committed leadership. When senior teams actively use AI, talk about it openly and reinforce its value, it sends a clear signal that AI is a strategic priority. Consistent communication from leaders helps remove uncertainty, builds confidence and shows staff that experimenting with AI is encouraged.

Alongside leadership involvement, identify a group of AI champions across different departments. These are the early adopters who regularly use AI, share best practices and showcase real examples of how AI has improved their work. Their experiences create momentum, inspire others and help drive adoption organically across the wider organisatio

2. Assign your seats intentionally_

We typically recommend starting with a small number of licences for AI tools while you experiment and identify use cases. When you do this, we recommend you assign seats intentionally.

Ensure members from every team have access to AI, as this will enable you to identify use cases across your core functions for a comprehensive view of the AI impact.

This will also make it easier to encourage adoption in every team, so everyone is bought into the transition.

3. Create a working group_

An AI working group is one of the fastest ways to build confidence and momentum across your organisation. By bringing people together regularly to share what’s working, where they’re getting stuck and how they’re using AI day‑to‑day, you create a space where learning happens naturally and adoption increases organically.

These sessions encourage people to actively use AI so they have something to contribute, while also allowing early successes to inspire others. Over time, the group becomes more skilled, more consistent and more confident – and you gain a steady stream of real, validated use cases that can be rolled out to the wider business.

We created our own AI working group and saw significant benefits – including 4.2 hours saved per member, per week. We’ve also seen it improve adoption across the business.

4. Encourage experimentation_

No one fully knows the limits of AI yet — and the only way to understand how it can add value to your business is through hands‑on experimentation. Giving people permission to explore AI without fear of “getting it wrong” is one of the most effective ways to build confidence and uncover high‑impact use cases.

Create a safe environment where staff can try out different tools, test prompts and see how AI fits into their daily workflow. This could mean allocating dedicated time to experiment, normalising AI as part of everyday conversations, or allowing teams to trial new tools in a controlled way.

When people feel empowered to experiment, they naturally discover smarter, faster ways of working. Those discoveries quickly spread across teams — driving productivity, creativity and better adoption without forcing change from the top down.

5. Document successful use cases_

As people become more confident with AI, they’ll naturally uncover ways to work faster, produce better output and remove day‑to‑day friction. Capture these wins. Documenting successful use cases turns individual improvements into collective progress.

Create a simple, accessible space where anyone can share what worked, how they used AI and the impact it had. Over time, this becomes a growing library of proven examples that teams can learn from, replicate and build on.

Circulating these use cases across the business accelerates adoption, helping everyone benefit from ideas that have already shown real value.

6. Share external inspiration_

There are plenty of resources out there to help people use AI better. People have dedicated hours to researching AI (so you don’t have to!) and turning their successes in videos, blogs, social media posts and so on.

Spend time looking at what’s available and pinpoint the use cases that are most relevant to your business. You can then pass these onto relevant teams, helping to inspire their AI usage.

We’ve even put together 45 use cases to get you started.

7. Manage expectations_

AI is powerful, but it isn’t a silver bullet — and setting the right expectations early prevents frustration later. AI excels at tasks like generating content, summarising information and analysing data, but it struggles with work that requires strategic judgement, deep technical expertise or uniquely human qualities such as empathy, nuance and lived experience.

Even when AI can perform a task well, it still needs human oversight. Teams will need to provide clear prompts, review outputs and refine the results to ensure accuracy and quality. Without this, standards can quickly slip.

Making it clear that AI is there to augment people’s work (not replace it) helps staff understand where it fits, when to rely on it and when human input remains essential. This balanced framing builds trust, reduces resistance and encourages more responsible, confident usage across the business.

8. Increase usage gradually_

Adopting AI represents a meaningful change in how people work, so moving too fast can create confusion, resistance or inconsistent usage. A gradual rollout gives teams space to learn, adjust and build confidence without feeling overwhelmed.

Start small. Give a handful of people early access so they can explore AI, test it against real tasks and develop comfortable, repeatable habits. Once those foundations are in place, scale access across more teams. This phased approach allows adoption to grow naturally, with early users helping others, sharing best practices and demonstrating the value AI can bring.

Introducing AI at a sensible pace encourages genuine buy‑in, reduces disruption and ensures each stage of adoption delivers real benefit rather than becoming a box‑ticking exercise.

9. Master prompting_

Being able to prompt AI efficiently is key to getting high-quality outputs. With better outcomes, you’re more likely to improve business performance and gain competitive advantages.

However, prompting is an art. You need to give detailed prompts that clearly set out what you need, give enough context and put AI in the best position to respond.

Encourage your staff to spend time testing different prompt styles, with the aim of uncovering which generate the best answers. They should also share their wins with others, so everyone gets better at prompting.

Our Copilot promptbook contains top tips to master prompting, with example prompts to test out across your business areas.

10. Measure impact_

AI adoption accelerates when people can see the real, measurable value it delivers. Tracking impact is one of the most powerful levers you have to build momentum and trust.

Make a deliberate effort to measure the outcomes of AI usage as adoption grows. This could include hours saved, reductions in manual effort, improved accuracy, faster turnaround times, better project outcomes or even qualitative wins like reduced frustration or improved collaboration.

Then share these results widely. When teams see clear evidence that AI is making work easier, faster or better, they’re far more likely to embrace it themselves — turning isolated wins into organisation‑wide adoption.

11. Tailor_

Many AI tools out there are one-size-fits-all. But every business will implement AI in different ways, depending on their processes, staff, challenges and objectives.

Tailoring AI can fit it better to your specific business needs, delivering bespoke advantages that have a bigger impact on performance.

There are many ways to tailor AI, including:

Find industry or role-specific tools that have been built for businesses like yours
Connect AI to your data, allowing it to deliver contextual responses
Create bespoke AI solutions, using platforms like Copilot Studio

With AI that’s better connected to your business, you can enable users to get good responses without having to spend time prompting it, reducing the barriers to usage.

Getting your business AI-ready_

AI can significantly evolve your business for the better. However, it can only drive results if your organisation is ready for it, with staff who feel encouraged to use it efficiently and creatively.

We know getting the ball rolling with AI can be tricky, especially if your team don’t know much about it. It’s something we’ve had to tackle ourselves. That’s why we created our Copilot Adoption Hub, designed to help you build momentum, strengthen adoption and give your teams the confidence to use AI effectively.

It’s packed with expert insights, practical guidance and resources for every stage of adoption — from early experimentation through to organisation‑wide rollouts. Whether you’re looking for best‑practice prompts, change management advice or real examples of AI in action, you’ll find the support you need to make AI a natural part of everyday work.

Key takeaways_

What are the barriers to AI adoption?