Trust is what makes AI scale. We help you engineer it into every stage of the AI lifecycle.

AI Trust

Colleagues collaborating in an office - AI generated

Scaling AI with trust drives adoption and growth

Australian organisations are moving from isolated AI pilots to AI embedded in core operations, decisions and infrastructure. The question is no longer whether to use AI, but how to scale it across the enterprise while sustaining trust, speed and human-centred value. According to PwC's 29th Global CEO Survey - Australian insights, keeping pace with technological change, including AI, is the number one concern for Australian CEOs, yet only 18% of local companies have built strong AI foundations and 37% of CEOs report a high degree of trust in AI.

Scaling AI also raises the stakes. Agents now plan and act across systems, attack surfaces expand to prompts, connectors and non-human identities, and new categories of risk emerge faster than traditional governance can absorb them. Trust is not a brake on that change. It is what lets organisations scale AI with confidence.

AI Trust brings together PwC specialists across governance, data, cyber security, risk, actuarial and assurance to embed trust into how AI is designed, built, deployed and run. We address model and agent performance and the data, infrastructure, security and regulatory requirements that surround them. We align to international standards such as ISO/IEC 42001 and the NIST AI RMF, localised to Australian expectations including the Australian Government's guidance on safe and responsible AI, APRA CPS 230 and CPS 234, and the Privacy Act.

Defining trust in AI is simple. Operationalising it at scale is complex.


Trust in AI is not a concept you present.
It is a capability you engineer.

Trust is designed in from day one. 

Governance, security and human oversight are built into AI systems from the start, so teams move faster without retrofitting controls later.

Trust keeps humans at the helm.

As AI becomes more autonomous, decision boundaries, traceability and escalation are engineered into the architecture so people retain authority to set direction, monitor behaviour and step in when it matters.

Trust is continuous.

Trust is earned through reliable outcomes over time. Continuous monitoring and assurance replace point-in-time checkpoints, so confidence keeps pace with change.


AI Trust helps you navigate new challenges and unlock lasting value

As AI adoption accelerates, the challenge shifts from proving a use case to scaling safely across complex data, technology and operating environments. Like your companies culture, trust in AI cannot sit outside the transformation as a one-off review. It needs to be built into design and implementation, monitored in operation and independently evidenced where stakeholders require assurance.

Key lever: Build AI trust by design  

Move from one-off, static controls to trust by design: a risk-based operating model, clear accountability, an AI inventory and controls embedded into delivery workflows. This makes governance proportionate to each use case and gives teams practical guardrails they can apply as AI moves from design into production. For example: establish risk tiers for use cases (e.g. low, medium, high) with defined controls and evidence requirements for each tier, so oversight scales with risk.

Key lever: Scale AI with confidence 

Trustworthy AI depends on data that is ready for use. Improve quality, lineage, provenance and access, then embed these requirements into the platforms and workflows where AI is built and run. Ongoing controls help models remain accurate, relevant and reliable as adoption scales.

Key lever: Scale AI with confidence 

Create a continuous line of sight across AI usage, performance, quality, cost and risk. Integrated observability helps teams demonstrate value, detect drift and emerging threats, enforce guardrails and respond before issues become incidents — turning trust into an operational capability rather than a point-in-time assessment.

Key lever: Protect AI in use 

Embed secure architectures, identity and access controls, human oversight and reusable guardrails into AI solutions and agents from the start. Test how they behave in realistic conditions, remediate weaknesses before go-live and integrate controls into the enterprise platforms where AI will operate.

Key lever: Protect AI in use 

Protect the full AI stack — data, models, agents, applications, infrastructure and third parties — and align security with engineering and operational workflows. Continuous monitoring, tested response processes and disciplined access controls help sustain resilience as AI use expands.

Key lever: Assure and evidence trust over time

Build evidence as AI is designed, deployed and operated, then use independent evaluation and assurance where boards, regulators, customers or other stakeholders need confidence. This connects day-to-day controls with credible proof that AI remains governed, secure, explainable and fit for purpose over time.


Our AI Trust Services

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AI Governance

Unlock value at pace

Our people and technology help you establish a scalable, policy-aligned and intentionally balanced AI governance program that drives accountability and strengthens trust. Then, we help you activate the right people, processes, training, controls, testing and monitoring at the level appropriate for each use case. 

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Data Activation for AI

Maintain quality at scale

Our people and technology help you improve data readiness and architect infrastructure that supports AI implementation and is flexible enough to support evolving use cases. Then, we help you operationalize monitoring, remediation, and protection models that produce consistent, reliable inputs for AI workloads and drive quality and security at scale.

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AI Observability

Manage AI at scale and demonstrate value

Our people and technology help you gain clear visibility into usage, cost, quality, and risk signals to manage AI at scale, maintain control, and demonstrate value. Then, we help you establish a living inventory of all AI systems, models, and embedded tools to support strategic AI growth and coordinated adoption across teams.

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AI Security Foundations

Maintain security at scale

Our people and technology help you enable safe interactions and reduce variability by establishing practical safety and security controls that teams can apply as they build, deploy, and scale AI solutions. We also help you validate protections and identify and address potential vulnerabilities of your AI infrastructure or systems.

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AI Stack Protection

Enable lasting impact  

Our people and technology help you enable defense in depth and strengthen trust at scale by reinforcing security across the AI stack. We help you harden and standardize your AI systems, platforms, infrastructure, and configurations, protect AI across environments, safeguard sensitive data, and strengthen defenses, so AI systems remain resilient as they scale.

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Evaluation and Assurance

Gain confidence in AI model integrity

Our people and technology help you bring clarity, confidence, and credibility to AI systems through objective evaluation and independent assurance. We help you validate your AI implementations are operating as intended, are in alignment with industry leading practices and emerging standards, will withstand external scrutiny, and deliver outcomes leaders can stand behind.


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Contact us

Nicola Costello

Nicola Costello

Partner, Digital and AI Trust Leader, PwC Australia

Peter Malan

Peter Malan

Partner, Cybersecurity & Privacy Practice Leader, PwC Australia

Nina Larkin

Nina Larkin

Partner, Risk and Regulation, PwC Australia

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