TIAPS ALB_Module 2E. Data Analytics for Internal Auditing

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• Don’t have the right leadership. • Don’t have proper support. • Don’t have the right knowledge on the team. • Inertia and complacency. 66 What can internal audit do about these obstacles? A lack of the right people and sufficient budget can be significant inhibitors which is why it is necessary to persuade senior management and the governing body. Internal audit managers should develop a robust strategic plan aligned with organizational priorities and based on a clear vision of an advanced, agile, and responsive function in which utilization of technology plays a central role. The mission of helping management and the board make timely interventions to support organizational success is the justification needed for investing in internal audit digital transformation. To attract the best talent and to deliver the maximum value requires audit functions to be leaders of innovation. It can be easy to be complacent about the current state and essential to break that mindset in favor of continuous positive momentum, even if taken incrementally. Audit leaders can start small and build on success. Senior management and the governing body may not be pressing the audit function to change but it should be part of every auditor’s DNA to strive for continual improvement. Sometimes an external quality review can help provide added weight to the case for investment in technology. As the advocate for continuous improvement, audit managers need to implement processes for identifying and evaluating opportunities for improving the delivery of service excellence. In addition to the use the internal audit function may make of artificial intelligence and other technological innovations, they also represent potential opportunities and threats for other parts of an organization. Internal auditors need to be well informed to be able to offer meaningful assurance, insight, and advice. The IIA has produced a three part series to help internal auditors. 67 The guidance references four different kinds of AI: Type I. Reactive machines: This is AI at its simplest. Reactive machines respond to the same situation in exactly the same way, every time. An example of this is a machine that can beat world-class chess players because it has been programmed to recognize the chess pieces, know how each moves, and can predict the next move of both players. Type II. Limited memory: Limited memory AI machines can look to the past, but the memories are not saved. Limited memory machines cannot build memories or “learn” from past experiences. An example is a self-driving vehicle that can decide to change lanes because a moment ago it noted an obstacle in its path. Type III. Theory of mind: Theory of mind refers to the idea that a machine could recognize that others it interacts with have thoughts, feelings, and expectations. A machine embedded with Type III AI would be able to understand others’ thoughts, feelings, and expectations, and be able to adjust its own behavior accordingly. Type IV. Self-awareness: A machine embedded with Type IV AI would be selfaware. An extension of “theory of mind,” a conscious or self-aware machine would be 66 Garyn, Hal, “Why Is Internal Audit Often A Tech Laggard?” Internal Audit 360, 2022. 67 Global Perspectives & Insights, The IIA, various. 75
aware of itself, know about its internal states, and be able to predict the feelings of others. 68 The guidance also highlights potential opportunities and threats. Opportunities • The ability to compress the data processing cycle. • The ability to reduce errors by replacing human actions with perfectly repeatable machine actions. • The ability to replace time-intensive activities with time-efficient activities (process automation), reducing labor time and costs. • The ability to have robots or drones replace humans in potentially dangerous situations. • The ability to make better predictions, for everything from predicting sales of certain goods in particular markets to predicting epidemics and natural catastrophes. • The ability to drive revenue and grow market share through AI initiatives. Threats • Unidentified human biases are imbedded in the AI technology. • Human logic errors are imbedded in the AI technology. • Inadequate testing and oversight of AI results in ethically questionable results. • AI products and services cause harm, resulting in financial and/or reputational damage. • Customers or other stakeholders do not accept or adopt the organization’s AI initiatives. • The organization is left behind by competitors if it does not invest in AI. • Investment in AI (infrastructure, research and development, and talent acquisition) does not yield an acceptable ROI. 69 Which of these apply to your situation? 2E.3: Reflection Don’t have the budget. Don’t have the time. Don’t have the right people. Don’t have the right leadership. Don’t have proper support. Don’t have the right knowledge on the team. Inertia and complacency (we don’t need to do more – clients and stakeholders are happy). 68 Artificial Intelligence, Internal Audit’s Role, and Introducing a New Framework Part 1, The IIA, 2017. 69 Artificial Intelligence, Internal Audit’s Role, and Introducing a New Framework Part 1, The IIA, 2017. 76
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