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By Steven Gabris Executive Summary AI agents are starting to perform work that PMOs have traditionally assigned to coordinators, analysts and assurance functions: checking evidence, monitoring portfolio data, escalating exceptions and updating workflow records. That shift creates a delegation question. What is the agent responsible for doing? What is it authorised to decide, communicate or change? What system permissions enable those actions? And who remains accountable when

Steven Gabris Executive summary AI is producing measurable time savings across operational and knowledge work. That is useful evidence of efficiency, but it does not prove that an organisation has realised a financial or operational benefit. A saving spread across selected tasks, roles and different points in a workflow does not automatically create an equivalent amount of removable headcount. Organisations need to establish where usable capacity has actually been released, d

By Steven Gabris Executive Summary Dependencies are unavoidable in complex project and program delivery. A project may rely on another team, vendor, platform, approval or decision before it can complete part of its own work, and the larger the program becomes, the more of these relationships need to be coordinated. Where organisations get into trouble is in assuming that a dependency has been managed because it has been identified and recorded. A dependency can appear in Jira

Executive summary – for delivery leaders and executives Training builds knowledge, but delivery capability is an operating result, not a course outcome. When incentives, standards, tools and leadership behaviour contradict “good practice,” even highly trained people will revert to old habits. Capability is built in real work: through clearer standards, aligned workflows, coaching at the point of need, and leaders who reinforce the expected behaviour under pressure. Measure de

What Australia’s emerging AI delivery model and the World Economic Forum’s financial-services playbook tell us about turning responsible AI into an operating capability Enterprise AI has reached an important point. The discussion is moving beyond access to tools and experimentation with use cases. Governments and financial institutions are now confronting the harder questions: how AI should be selected, delivered, assured, owned and measured once it becomes part of everyday w

What Australia’s emerging AI delivery model and the World Economic Forum’s financial-services playbook tell us about turning responsible AI into an operating capability Enterprise AI has reached an important point. The discussion is moving beyond access to tools and experimentation with use cases. Governments and financial institutions are now confronting the harder questions: how AI should be selected, delivered, assured, owned and measured once it becomes part of everyday w

When we introduced a project-support agent, the aim was straightforward: reduce the manual effort involved in collecting and reviewing project updates so the project manager could spend more time with stakeholders. It did that. But it also did something more useful. The agent showed us where updates lacked detail, where the underlying delivery data was weak and where expectations about a good status update had never really been agreed. It did not eliminate follow-up. It helpe

Build the agent around a clear job description A simple agent-builder template A simple acceptance-test template AI agents are beginning to move beyond simple question-and-answer tools. BNY has described digital employees with defined responsibilities, system credentials, nicknames and human managers, while KPMG has discussed redesigning work across human, hybrid and agent-led roles. These models suggest that organisations are beginning to think about AI as part of their work

Customer due diligence is often reduced to a simple instruction: collect identification from the customer. Under Australia’s reformed AML/CTF regime, that is not enough. Branova: AML/CTF Simplified: Steven Gabris Identification may establish a customer’s name and basic details. Customer due diligence, or CDD, requires a business to understand who is really involved, why the regulated service is being requested and whether the customer presents a higher money laundering or ter

Branova AML/CTF Compliance Australia’s expanded anti-money laundering and counter-terrorism financing obligations commenced for newly regulated businesses on 1 July 2026. For affected businesses, the implementation period has passed an important threshold. The question is no longer what may be required in the future. It is whether the organisation has established the foundations needed to comply now. AUSTRAC expects newly regulated businesses to be enrolled, have an AML/CTF p

During my time at BNY, I saw the firm invest in more than AI tools. It was also building the governance, employee training and internal capability needed for people to experiment with AI responsibly. That foundation mattered. It gave employees room to explore practical uses of AI without treating innovation as an uncontrolled activity. People could develop ideas, test them within defined boundaries and gradually build confidence in how the technology should be used inside a l

Australia’s expanded anti-money laundering and counter-terrorism financing regime is now in force. From 1 July 2026, thousands of real estate businesses, lawyers, conveyancers, accountants, trust and company service providers, and certain dealers in precious metals and stones became subject to AML/CTF obligations for the first time. For affected businesses, this is no longer a future readiness exercise. The immediate question is: Can your business demonstrate that it understa

What APRA’s warning means for PMOs PMOs need to know where AI is entering the portfolio, clarify who owns the outcome and strengthen the evidence used to approve and govern AI-enabled change. This does not make the PMO the owner of AI risk. It makes the PMO responsible for ensuring that delivery, risk, technology, vendors and the business are not operating with different versions of accountability. Steven Gabris — What APRA’s warning means for PMOs At a KPMG roundtable last y

Governance should not be the thing that slows delivery down. At its best, governance gives leaders the confidence to move faster because they can see the risks, understand the decisions, and trust the information being used to manage delivery. That becomes more important as AI starts influencing how teams plan work, summarise information, identify risks, prepare updates and support decision-making. My view is simple: AI does not make governance less important. It makes govern

In the complex landscape of regulated industries, achieving program stabilization is not just a goal; it is a necessity. Organizations operating in sectors such as healthcare, finance, and energy face unique challenges that require a strategic approach to maintain compliance and operational efficiency. This blog post will explore the key components of program stabilization, practical strategies for implementation, and real-world examples that illustrate successful outcomes. U

In the rapidly evolving landscape of financial services, effective governance has emerged as a cornerstone for success. As organizations navigate complex regulations, technological advancements, and shifting consumer expectations, the need for robust governance frameworks becomes increasingly critical. This blog post explores how effective governance can transform financial services, enhancing transparency, accountability, and overall performance. Understanding Governance in

In an era where regulations are constantly evolving, organizations face the daunting task of navigating complex compliance landscapes. Regulatory risk management has become a critical component of business strategy, and the integration of artificial intelligence (AI) into this process is proving to be a game-changer. By leveraging AI-augmented insights, businesses can enhance their ability to identify, assess, and mitigate regulatory risks effectively. This blog post explores