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      AI adoption in the workplace is rising fast – are you realising its full advantage?

      AI is now part of everyday work, but many organisations are still not seeing consistent returns. Nearly four years after generative AI entered widespread use, the results are mixed: some are seeing real gains, while others are finding the anticipated ROI is harder to realise.

      The question for leaders is no longer whether your workforce is using AI. In Australia, 65% of employees already are. The challenge is adoption quality: whether AI is being used reliably, responsibly and in ways genuinely embedded into how work gets done.

      The gap is rarely the tools. It is the how of adoption: how AI is integrated into decision-making, workflows and accountability, with the right checks and confidence built into everyday work.

      How organisations can improve AI adoption and realise ROI

      This report explains how leading organisations are moving from using AI to using it well by deliberately shaping how AI is adopted across workflows, decision-making and accountability.

      It sets out what separates organisations that are seeing real returns from those that are not. That includes getting clear on what actually drives value from AI, clarifying decision rights and quality checks, and building the confidence and capability of leaders and teams to use AI consistently and responsibly in the flow of work.

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      Turning AI adoption into AI advantage

      Explore the full insights, data and practical actions to help your organisation scale AI with confidence.

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      Report highlights: six things leaders should know about AI adoption

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      Leadership matters

      Adoption quality improves when leaders build confidence, set expectations and role-model trustworthy AI use.

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      AI adoption is now mainstream, but enterprise value is not

      Widespread AI use does not automatically translate to repeatable business outcomes.

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      The adoption quality gap is real and costly

      Inconsistent and non-compliant use, and over-reliance on unverified outputs can create errors, rework and avoidable risk.

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      There is a gap between AI activity and measurable value

      Many organisations are investing and experimenting but not consistently translating gains into outcomes that stick.

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      Scaling AI is harder than proving it works

      Moving beyond pilots requires clearer ownership, better controls and the organisational conditions to embed AI into day-to-day work.

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      This is a continuous journey, not a one-off project

      Organisations that iterate, learn quickly and scale what works are more likely to build durable advantage as AI accelerates.

      Strategies for successful AI adoption

      The report outlines evidence-based evolutions organisations can act on now, from leader role-modelling and AI enablement teams, to learning that drives behaviour change and policy that sticks in everyday practice.

      • Support leaders to role-model trustworthy AI use

        Leaders set the tone. When they are transparent about how they use and check AI, they build trust and confidence across teams.

      • Provide practical support to redesign work

        Focus on how work actually happens. Establish support (such as AI enablement teams) to redesign workflows, roles and decision points.

      • Build training that drives behaviour change

        Go beyond tool training. Build capability in judgement, critical thinking and how to apply AI effectively in real work contexts.

      • Turn enterprise AI policy into everyday practice

        Embed simple habits such as verifying outputs and disclosing AI use so guidance becomes part of day-to-day work.

      • Start fast, learn forward and scale what works

        Progress comes from testing small, learning quickly and scaling proven approaches, not waiting for perfect certainty.

      Build executive capability for responsible, value-led AI adoption

      KPMG’s AI learning for leaders program is designed to uplift executives’ capability and help organisations move beyond experimentation to adoption that delivers measurable value.

      Delivered through a blend of workshops, hybrid learning, self-paced e-learning, on-demand video and specialist coaching, it builds practical, board-ready leadership confidence across value, trust and responsible adoption, and supports leaders with governance capability and scaling playbooks to embed AI into everyday work.

      AI learning for leaders

      How KPMG can help you use AI well

      KPMG Australia helps organisations lift adoption quality, so AI delivers repeatable outcomes. We can help establish AI enablement teams to pinpoint value leakage, redesign work and build confidence, accountability and scale. We help you:

      • build leader capability to guide trustworthy AI use
      • redesign workflows and decision points to embed AI where it adds value
      • stand up enablement models to support teams and scale what works
      • turn AI policy into everyday habits to reduce risk
      • keep momentum with an iterative, test-and-learn approach.

      Wherever you are on the journey, we help you move early, learn safely and translate AI investment into dependable performance.

      Ready to move from AI adoption to real impact?

      Download

      Turning AI adoption into AI advantage

      Explore the full insights, data and practical actions to help your organisation scale AI with confidence.

      Download

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      Frequently asked questions

      AI adoption quality refers to how effectively and responsibly AI is used in everyday work, including clear expectations, verification and accountability.

      AI initiatives often stall when value isn’t clearly defined, workflows aren’t redesigned, or organisations aren’t ready to support change at scale.

      Common challenges include inconsistent use, lack of governance in practice, and over-reliance on unverified AI outputs.

      Organisations can improve ROI by embedding AI into workflows, building leadership capability, and scaling only what delivers consistent value.

      It focuses on adoption quality, leadership behaviour, workflow redesign, practical training, and continuous learning to scale impact over time.