AI assessment

Before we begin

About your organisation

This provides useful context for your result. These answers are not included in the maturity score.

Which option best describes your role?

Executive leadership

Manager with people or performance responsibility

HR, learning or organisational development

IT, digital transformation or security

Subject-matter or process owner

Adviser

Other

Approximately how many employees does your organisation have?

1–19

20–49

50–249

250–999

1,000 or more

How broad is your area of responsibility?

My own work

One team

One department or function

Several departments

The whole organisation

Where are you in your use of Microsoft 365 Copilot or similar AI tools?

Not yet considered

Considering or planning

Testing on a small scale

Rolled out to selected groups

Broad use across the organisation

Not sure

Which industry does your organisation operate in?

Area 1 of 5

Direction and leadership

Select the option that best describes current practice – not your ambition.

How clear is the organisation about what it wants to achieve with AI?

We have no shared, clearly stated purpose. Activity is mainly driven by curiosity and individual initiatives.

We have general ambitions for efficiency or higher productivity, but few specific goals.

We have identified some needs or use cases, but goals and priorities vary across the organisation.

We have clear goals linked to priority workflows, business needs and expected outcomes.

AI is part of our strategy and portfolio management, with clear goals that are monitored and adjusted over time.

How are responsibility and ownership for AI adoption assigned?

It is unclear who is responsible, and no one has a clear mandate.

Individuals, enthusiasts or IT follow up the activity informally.

Pilots or individual areas have designated owners, but mandates, roles and leadership sponsorship remain inconsistent.

Leadership has assigned sponsorship, ownership and operational roles for priority initiatives.

Responsibility for adoption, value, risk and improvement is integrated into normal governance and leadership follow-up.

How are areas and initiatives for AI use prioritised?

Initiatives arise mainly because a tool is available or someone has an idea.

Opportunities are selected informally based on interest, visibility or local needs.

We use some criteria, but prioritisation is neither consistent nor organisation-wide.

We assess needs, expected value, feasibility, data and risk before selecting initiatives.

We manage a combined portfolio and use documented learning to prioritise, improve, stop or scale initiatives.

Score – Direction and leadership

Area 2 of 5

Adoption and capability

Select the option that best describes current practice – not your ambition.

How relevant and widespread is access to AI tools?

Most people do not have access to approved AI tools, or it is unclear which tools may be used.

Access is limited and partly relies on self-selected or freely available tools.

We have licences or pilot groups, but access is uneven and not always aligned with roles and needs.

Relevant roles have access to approved tools and the information needed for priority use cases.

Access and functionality are actively managed by role, workflow and value potential, and adjusted based on experience.

How would you describe actual use of AI in day-to-day work?

Use is very limited or unknown.

A few individuals try the tools occasionally.

More people use AI regularly, but mainly on their own initiative and in individual tasks.

Relevant teams have established shared ways of working and exchange experience and good examples.

AI is a natural part of priority workflows, and its use is systematically improved based on outcomes and feedback.

How are capability, confidence and support developed over time?

We have not established training, support or clear learning resources.

Learning mainly happens on individual initiative or through one-off introductions.

Some groups receive training, guidance or resources, but provision is uneven and not well tailored to roles.

We provide role-based training, practical support and opportunities to share learning linked to specific tasks.

Capability development is continuous and connected to workflows, goals, onboarding, leadership follow-up and documented learning.

Score – Adoption and capability

Area 3 of 5

Workflows and organisation

Select the option that best describes current practice – not your ambition.

To what extent has AI changed the workflows themselves?

The workflows are essentially unchanged.

Individual tasks are completed faster, but the process and allocation of responsibilities are otherwise unchanged.

Parts of the workflow have been improved, automated or reorganised.

Entire priority workflows have been reviewed and adapted to new ways of working, roles and information needs.

Workflows are continuously designed and improved with AI, people, responsibilities, controls and information flow considered as a whole.

How is AI used in teams, collaboration and handovers?

Use is individual and largely invisible to colleagues or managers.

Employees share some tips and prompts, but have few common ways of working.

Some teams test shared practices, templates or routines, but use often stops at the team boundary.

Roles, collaboration, handovers and information flows are adapted so AI supports the team’s overall delivery.

Cross-functional workflows have been redesigned and are managed across organisational boundaries with clear standards and responsibilities.

How are changes to work processes owned and led?

No one has clear responsibility for changing the work processes.

Enthusiasts or individual managers drive the changes without a lasting mandate or sufficient resources.

Projects or local managers follow up some changes, but ownership after the pilot phase is unclear.

Process owners, managers and affected employees have clear roles, goals and a plan for implementation and follow-up.

The workflows have permanent owners, feedback loops and resources for continuous improvement, learning and value realisation.

Score – Workflows and organisation

Area 4 of 5

Technology, data and responsible use

Select the option that best describes current practice – not your ambition.

How accessible and suitable is the information the AI tools need to use?

Information is scattered, unstructured or difficult to use safely and reliably.

Users copy and compile a great deal of information manually, while access or quality limits the results.

Selected data sources and document areas have been prepared, but quality, structure and access vary.

Relevant information is accessible, managed and access-controlled for priority workflows and solutions.

Data quality, knowledge management, access and lifecycle are monitored and improved as an integral part of AI solutions.

How clear and practical are the guardrails for safe and responsible use?

It is unclear what is permitted, and employees largely have to assess risk themselves.

We have general advice or guidelines, but they offer limited support in specific work situations.

Policies and training exist, but understanding and compliance vary across roles and areas.

We have role-based rules, approved use cases, training and risk assessment for priority initiatives.

Responsible use is integrated into governance, design, access, monitoring and continuous improvement of solutions and ways of working.

How well are AI tools and agents integrated into the existing work environment?

Use mainly takes place in standalone tools without connections to the organisation’s systems and information.

AI is used as a general assistant, but is only minimally integrated into work processes, data sources or other tools.

Microsoft 365 Copilot, agents or other solutions are connected to selected approved environments and information sources.

Solutions are integrated into priority workflows with relevant data sources, access controls and clear management.

The organisation has a reusable, governed platform for integrations and agents, with monitoring, lifecycle management and continuous improvement.

Score – Technology, data and responsible use

Area 5 of 5

Value, learning and scaling

Select the option that best describes current practice – not your ambition.

How do you measure the impact of AI use?

We do not measure the impact.

We rely mainly on feedback, activity data and individual stories.

Some teams track time, quality, capacity or satisfaction, but measurement is not consistent.

Priority initiatives have a baseline, a value hypothesis, clear ownership and defined measures.

Benefits are monitored systematically over time and actively used to prioritise, improve, stop or scale initiatives.

How do you test, learn from and improve AI solutions?

We have no structured practice for testing and learning.

Individuals and teams experiment, but without clear hypotheses, criteria or shared learning.

We run pilots and gather some experience, but learning is used and shared inconsistently.

We test with clear hypotheses, relevant users, feedback and decision points before further investment.

The organisation has an established learning loop in which results are compared, documented and reused across initiatives.

How do you decide what to stop, develop further or scale?

Adoption spreads mainly through individual initiative, without a shared decision-making process.

Visible successes are copied in some areas, but continuation often depends on local enthusiasts.

Selected pilots are expanded case by case, with varying requirements for ownership, value and management.

We use clear criteria and clarify ownership, resources, risk and expected value before scaling.

We manage a combined portfolio with standards for reuse, scaling, retirement, management and ongoing value tracking.

Score – Value, learning and scaling

Final step

Get your result

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No, I only want the result for now

What would you most like to achieve?

Build foundational capability

Increase actual use and adoption

Improve specific workflows

Prioritise the right AI initiatives

Build Copilot agents

Measure and scale value

Clarify strategy and governance

When is this relevant?

Now

Within three months

Within six months

Later or uncertain

Total maturity score

AI assessment

How ready is your organisation to create value with AI?

About your organisation

Direction and leadership

Adoption and capability

Workflows and organisation

Technology, data and responsible use

Value, learning and scaling

Get your result