How to Turn Process Mapping into an Effective Evaluation Tool

 

One of the fundamental activities carried out by internal control specialists and internal auditors is the mapping of operational processes that will be evaluated.

First of all, it is important to understand that an operational process is a set of tasks logically organized with the aim of delivering products or services that add value. It allows management to better allocate resources, actions, and decisions to achieve strategic goals and objectives. Thus, it becomes clear that a process only makes sense if it is connected to the company's strategy.

Another important point is that each process must have a responsible manager who handles the management functions — that are planning, organizing, directing, executing, and monitoring. This manager is also responsible for risk management and the internal control system of the process.

Process mapping is an essential practice both when modeling new processes and when assessing existing ones, to verify if they are efficient, effective, and economical. Additionally, mapping is indispensable for analyzing whether the internal control system is sufficient to keep risks at acceptable levels, aligned with the organization's risk appetite.

In a performance or operational audit, mapping is part of the planning phase.

Nowadays, it is very common to use the BPM methodology to design processes, but it does not clearly distinguish between a task and an internal control. As a result, the outcome often looks more like a block diagram than a flowchart that is useful for a more precise evaluation.

This article aims to propose a reflection: how can we improve this mapping, making it simpler and, at the same time, more effective for evaluating both the process and the internal control system?

The first point concerns the way the process is mapped. It works better when conducted through planned interviews with those who perform the tasks on a daily basis. In these interviews, the specialist or auditor needs to have the skills to clearly identify what a task is and what is a control.

Put simply:

• An internal control is an action aimed at reducing the probability of a risk materializing. For example: reviewing, checking, recalculating, approving, authorizing, among others.
• A control is a decision point: if everything is correct, the process continues; if not, it returns for correction. In the flowchart, the control should be represented by a diamond shape (also known as a gateway).

On the other hand:

• A task is an execution action, such as recording, demonstrating, archiving, or relating information. In the flowchart, it is represented by a rectangle.

With this, notice how we can simplify: it is enough to use three symbols to create the flowchart:

• A circle to mark the beginning and end of the process,
• A rectangle for the tasks,
• And a diamond for the controls.

This model makes the flowchart clearer, more objective, and easier to use in the evaluation.

I personally like to use the "swimlane" format in the flowchart, where horizontal bands indicate the roles or functions involved in the process. This helps to better visualize whether there is a good segregation of responsibilities, which is essential to avoid failures.

Keep in mind: the flowchart must always represent the process as it is currently carried out, not as we would like it to be. Therefore, after mapping, it is essential to validate it through a "walkthrough", that is, walking through the process together with the person responsible, to confirm that what is described is accurate.

In the end, we will have a clear view of:

• All the tasks of the process,
  
• All the existing internal controls.

These elements are the basis for assessing:

• Whether the process is efficient and effective,
• Whether the internal control system is sufficient and effective.

All internal controls identified must be recorded in the internal control matrix, where they will be organized to facilitate analysis.

I am often asked: “Is it necessary to identify risks in the flowchart?” My answer: it is not mandatory, but there is also no problem in doing so. If you wish, you can include this information, linking it to the process risk matrix.

I hope this article has helped you reflect on the topic and, perhaps, improve your process of mapping operational processes.

I wish you great success and, Be Happy!

Managing the Internal Audit Function: What You Need to Know About Domain IV of the New Global Internal Audit Standards

 

Since January 9, 2025, the Global Internal Audit Standards (GIAS) have officially replaced the 2017 IPPF. 

This transition marks an important evolution in the way internal audit is practiced worldwide,  not a revolution, but an elevation of the profession.

These standards provide an essential technical and ethical framework for internal auditors, ensuring consistency, quality, and credibility in their work. Among the most critical updates is Domain IV: Managing the Internal Audit Function.

While some elements of Domain IV were present in previous frameworks, it now brings a sharper focus on strategic management, resource optimization, effective communication, and continuous quality improvement.

Domain IV clarifies the role of the Chief Audit Executive (CAE) in ensuring that the internal audit function is:

•      Aligned with the organization's strategy
•         Efficient in resource management
•         Transparent and effective in communicating with stakeholders
•          Committed to continuous improvement

Perhaps the most significant new element is Principle 9, emphasizing that internal audit must have a strategic plan as its primary driver.

Internal audit is no longer just about executing an annual or multi-year audit plan. The CAE must approach audit planning strategically, ensuring that internal audits support the organization's long-term success.

This requires:

•        A deep understanding of the audit mandate
•         Full awareness of the Organization's operational and financial dynamics
•         Knowledge of governance, risk management, and internal controls

In other words, the CAE must understand how the organization operates, makes decisions, and sets its long- and medium-term strategic goals.

How can audit leaders implement this effectively? Here's a simple roadmap:

1. Start with the Organization’s Strategy
   Your internal audit strategy must support the organization’s strategic objectives.
2. Engage Key Stakeholders
3. Align your strategy with the expectations of the Board, senior management, and other key stakeholders.
4. Define the Vision
   While your mission is set by Domain I of the GIAS, your vision articulates the desired future state of internal audit. For example:

“To be a catalyst for change and innovation, driving operational and financial efficiency.”

4. Set Strategic Objectives
   Define specific goals linked to your vision. For instance:
• Ensure auditors have the necessary competencies to address emerging risks
• Secure resources for predictive analytics and innovation-related audits
5. Conduct a SWOT Analysis
   Identify your function’s strengths, weaknesses, opportunities, and threats to develop a practical roadmap for achieving your objectives.
6. Monitor and Adjust
   Continuously monitor action plans and progress toward strategic objectives, adjusting as needed to remain relevant and effective.

Why does this matter more than ever?

• Strategic planning is no longer optional; it’s essential for internal audit to:
• Allocate resources efficiently
• Ensure audit work adds tangible value
•  Anticipate and respond to organizational changes
• Strengthen governance and risk management processes

It transforms internal audit from a compliance-focused activity into a strategic partner within the organization.

Final thoughts for audit leaders:

In my point of view Domain IV is a cornerstone of the new standards, reinforcing the need for internal audit to operate strategically and systematically.

As internal auditors and leaders, embracing this approach will elevate your function’s relevance, impact, and value within the organization.

Let’s make internal audit a true driver of strategic success!

What steps are you taking to align your internal audit function with these new standards? Share your thoughts and experiences in the comments!

I’d like to close with this reflection:

“Always strive for simplicity — it is a competitive advantage. But remember being simple does not mean being superficial.

Be Happy!

This article was written with the help of human intelligence

 

The Critical Role of Artificial Intelligence Governance in a World Undergoing Profound Transformation

 

I have been participating in several working groups where we discuss the impact of artificial intelligence (AI) on organizations and society. And I must confess: the deeper I dive into this subject, the more I realize we are living through a moment of transformation far deeper than it seems at first glance.

In recent years, technology has evolved at an unprecedented speed. Innovations that once seemed distant are now knocking on our doors, radically changing how companies operate and compete. If we once spoke of isolated disruptions, we now live in a state of continuous disruption, spanning all areas and directly challenging corporate strategies.

And who is at the center of this revolution? Artificial intelligence, of course. But not AI alone. Technologies like autonomous agents, quantum computing, and neuromorphic computing are reshaping the fabric of organizations and, consequently, of society itself.

What strikes me most is that, despite all this, many professionals and companies have yet to grasp the depth and speed of these changes. And that’s concerning. It could compromise the sustainability of organizations and even the relevance of many professionals.

This new scenario demands more than enthusiasm for innovation. It demands responsibility, structure, and governance. And this is where AI governance comes in—as a viable, necessary, and urgent path to ensure that all this transformation is sustainable, ethical, and strategic.

We are entering an ecosystem of emerging technologies that, when combined, have the potential to completely reshape the fabric of society. More than just new tools, they represent new paradigms.

Much has been said about generative artificial intelligence, which is undoubtedly a milestone. But it’s only the doorway. We are witnessing the convergence of several emerging technologies that together have the power to radically change how we live, work, and relate to one another.

I want to share some of this reflection with you, starting with understanding what is truly happening around us.

Autonomous Virtual Agents

Autonomous virtual agents are not just smarter chatbots. They are systems capable of understanding objectives, making decisions, and executing tasks without continuous human supervision.

These agents are already being tested in financial negotiations, medical diagnostics, and even customer service learning, interacting, and adapting in real time.

Soon we will have our own virtual agent capable of performing simple tasks like receiving our emails, reading, assessing, prioritizing, deciding, and responding as if it were us even carrying out complex operations, such as defining products based on actuarial calculations.

Their ability to operate in complex and dynamic environments raises crucial questions about control, responsibility, and social impact.

Autonomous Robotic Systems

Industrial automation has adopted a new meaning with autonomous robotic systems, where robots not only follow instructions, but they also learn from their environments, correct their paths, collaborate with each other, and make decisions based on data.

Tesla’s Optimus is an example of this, expected to hit the market by 2026, at the price of a vehicle. In sectors such as logistics, healthcare, agriculture, defense, and space, these systems are replacing human labor in critical tasks raising significant questions about employment, ethics, and safety.

Quantum Computing

The promise of quantum computing is simple yet monumental: solving problems that would take a traditional supercomputer millions of years—in just minutes or seconds.

This could transform areas like climate modeling, molecular simulations for new drugs, logistical optimization, and especially cybersecurity.

IBM has already launched the Q System, a commercial quantum computer. Google has achieved “quantum supremacy” by performing a calculation on a quantum computer that would be impossible for classical supercomputers in a reasonable time. Microsoft is advancing in qubit technology, having developed a new quantum chip capable of solving large-scale complex problems.

With this power come significant risks, such as the potential to break encryption systems that underpin the modern internet, exposing sensitive data from governments, companies, and citizens.

Neuromorphic Computing

Although not new—Misha Mahowald and Carver Mead developed the first silicon retina and cochlea, as well as the first silicon neurons and synapses in the 80s neuromorphic computing gain renewed relevance with generative AI.

Inspired by the functioning of the human brain, neuromorphic computing seeks to create systems with learning and adaptation capabilities that closely mirror biological cognition.

This represents a major leap toward the creation of truly autonomous AI, capable of reasoning with context, memory, and emotion.

But it also represents a turning point: how do we regulate machines that think similarly to us?

Observe that what makes this moment unique is not the emergence of one disruptive technology, but the convergence of several.

When autonomous agents operate using neuromorphic neural networks, supported by decisions optimized through quantum algorithms, within robotic ecosystems, we are undoubtedly facing a new form of systemic intelligence—one that, if not properly governed, could surpass our control, with unpredictable consequences.

In 2024, at an AI event, a presenter stated that soon we would have three types of agents operating in companies: human agents, hybrid agents, and android agents.

At the time, I thought, “This speaker is watching too many sci-fi movies.” But today I see how mistaken my view of technological evolution was. Not as an excuse but understand that I’m almost a "time traveler” when I began working half a century ago, the most advanced technology was a manual typewriter, or a communication device called the Telex.

But let’s set aside the nostalgia and continue our reflection. 

Thus, it's clear that beyond the fascination with new technological possibilities, there’s a reality that organizations cannot avoid: the way they operate, protect themselves, and provide accountability is being profoundly reconfigured—so rapidly that it’s difficult to process, adapt to, and integrate innovations into daily operations.

And since companies are made up of people, all this deeply and continuously affects individuals’ lives, requiring them to break paradigms constantly. This contributes significantly to professional burnout and rising depression levels.

Corporate structures are being redefined, and this doesn’t only affect IT it impacts the entire operational ecosystem. Every department is being affected, without exception.

Compliance, risk management, and internal audit—traditionally pillars of corporate governance are directly impacted by this new disruptive ecosystem. Let’s examine:

Compliance

With the rise of autonomous agents and real-time decision-making systems, ensuring legal and ethical compliance is no longer a matter of simply “checking processes.” It now demands continuous monitoring, a deep understanding of the technologies involved, and the ability to respond to unforeseen events.

What happens, for instance, when an autonomous AI makes a biased or unethical decision? How can we ensure systems comply with regulations that are still being formulated?

Risk Management

In today’s landscape of exponential innovation, corporate risk management faces one of its greatest challenges: anticipating the unpredictable.

Technologies like autonomous agents, quantum computing, and neuromorphic systems introduce variables that didn’t exist a few years ago—and often aren’t even recognized as risks until they’ve already materialized.

The traditional risk management model—based on static cycles of identification, analysis, response, and monitoring—was already showing signs of exhaustion and now must be completely reimagined. It lacks the agility and adaptability to handle emerging risks that evolve in a matter of weeks, days, or even hours.

Risk is no longer a possibility—it’s a certainty at some point in the journey. The real differentiator now is the speed and intelligence of the response. This demands new organizational capabilities.

Internal Audit

Internal audit, long the guardian of compliance and efficiency, must now also serve as an interpreter of technological complexity.

With increasingly automated processes and decisions made by autonomous systems, auditing the "who did what" requires understanding algorithms, data flows, and machine learning logic.

More than identifying failures, auditing now requires anticipating risks, evaluating efficiency considering new innovations, assessing ethical impacts, and verifying whether digital governance principles are being upheld.

So, the central question is: How will we, and our organizations deal with all this?

In my view, there is no single answer. But one thing is certain: the first step involves a structured approach to effectively manage this technological disruption in a sustainable way, which we can call artificial intelligence governance.

AI governance is not just a control strategy, it is a foundational approach to ensure digital transformation occurs in alignment with corporate, societal, and ethical interests.

In times of rapid and unpredictable innovation, it serves as the backbone for managing disruption sustainably creating a framework that guides organizations not just to innovate, but to innovate with responsibility and long-term vision.

For our reflection, I believe AI governance must address the following key areas:

Defining Responsibilities

AI governance sets clear responsibilities within the organization. Who is accountable for the ethical and safe use of technology? How do we ensure automated or AI-assisted decisions follow company guidelines and legal standards?

Creating an AI governance committee, for instance with executives from IT, compliance, legal, and ethics, ensure decisions are made in a coordinated and informed way, without overwhelming any single department.

Additionally, governance determines how responsibilities align with strategic objectives. Every new AI project should be evaluated not only for its innovative potential, but also for its strategic, ethical, and regulatory impact.

Committing to AI governance means that, while the organization explores new technological frontiers, it also maintains control over the consequences of innovation.

Defining Security Standards

As technologies advance, security becomes a critical issue—not just in terms of data protection, but also regarding the integrity of automated decisions and system reliability.

AI governance establishes the necessary security standards to protect both sensitive data and autonomous systems. This involves implementing advanced cybersecurity mechanisms and protocols to ensure AI makes decisions that are secure and aligned with the organization’s values.

Preventing bias, ensuring algorithm transparency, and auditing automated decisions are all essential governance practices to ensure technologies are not only effective but also safe and fair.

Operational Formats and Monitoring

Governance also defines the operational structure of AI within the organization—creating frameworks for the development, integration, and management of intelligent systems.

AI implementation must be transparent, continuously monitored, and adjusted as technology evolves.

AI monitoring systems are essential to ensure that even when systems make autonomous decisions they remain within established boundaries.

In addition, AI governance demands ongoing monitoring to detect failures, errors, or unwanted behavioral changes, ensuring that unexpected risks don’t arise.

This monitoring must be integrated into strategic corporate management, aligning technological innovation with organizational goals and culture, so that AI contributes effectively to sustainable and ethical growth.

Note that this topic is much broader and far from exhausted here. Organizations through their Boards of Directors and/or Executive Management must address it quickly, seriously, and assertively.

They must take a leading role in structuring robust governance that permeates the entire organization and this is now urgent and non-negotiable.

I leave you with a thought provoking question for reflection:

How are you and your company addressing this issue?

The journey is just beginning. And despite all the challenges, what truly matters in the end is that we continue to find meaning, build together, and be happy
with ethics, awareness, and purpose.

Comments are welcome! Be happy.

This article was written with the help of human intelligence!

Domain III: Governing the Internal Audit Function, Evolution from the IPPF 2017

Domain III of the Global Internal Audit Standards defines the necessary attributes to ensure that the chief audit executive, together with the board and senior management, maintains the independence of the internal audit function, ensuring its effectiveness.

In the IPPF 2017, the attribute standards already emphasized the need for a solid relationship between internal audit and the board to ensure independence. The new standards expand and strengthen this concept, consolidating essential principles.

This domain is structured into three principles and nine standards, providing the foundation for meeting normative requirements. Below, we highlight the key advancements compared to the previous model.

1. Formalization of Internal Audit Function Authorization

Principle 6 reinforces the need for the board’s formal authorization of the internal audit function, supported by the following standards:

• Standard 6.1 - Audit Mandate
• Standard 6.2 - Audit Charter
• Standard 6.3 - Board and Senior Management Support

The mandate defines the authority, role, and responsibilities of internal audit, which, through a systematic and disciplined approach, aims to enhance governance, risk management, and internal controls.

The Internal Audit Charter becomes an essential document, formalizing the purpose, scope of activities, organizational positioning, responsibilities, and authority of internal audit.

Senior management and the board play a fundamental role in supporting internal audit by ensuring unrestricted access to data, information, and assets, enabling the effective execution of its work.

2. Strengthening Organizational Independence

Principle 7 addresses the independent positioning of internal audit, supported by two standards:

• Standard 7.1 - Organizational Independence
• Standard 7.2 - Chief Audit Executive Qualifications

Independence is ensured through the direct reporting line of the chief audit executive to the board, without interference from senior management. This communication channel must allow open discussions, including without the presence of management.

A new addition is Standard 7.2, which details the desired competencies for the chief audit executive, previously addressed in a general manner under the ethical principle of competence in the IPPF 2017. Now, five essential competencies are explicitly defined:

• Deep understanding of the Global Internal Audit Standards and best practices;
• Experience in establishing and managing an effective internal audit function;
• Certified Internal Auditor® (CIA) designation or equivalent credentials;
• Leadership experience;
• Industry-specific expertise.

This clearer definition strengthens the relevance of internal audit and its ability to add value to corporate governance.

3. Board Oversight of Internal Audit

Principle 8 establishes the board’s responsibility for overseeing internal audit, ensuring its effectiveness. The related standards are:

• Standard 8.1 - Interaction with the Board
• Standard 8.2 - Resources
• Standard 8.3 - Quality
• Standard 8.4 - External Quality Assessment

The board must ensure that internal audit has adequate resources, enabling it to fulfill its mandate efficiently. The chief audit executive must transparently communicate any resource limitations and their impact on the audit plan’s execution.

Quality management is also reinforced, requiring an internal and external quality assessment program, with periodic review by the board.

4. Challenges for Organizations Without a Formal Governance Structure

In organizations lacking a formal board, the concept of independence may be compromised. The definition of a board, according to the global standards glossary, includes any high-level governing body responsible for oversight, such as audit committees or advisory boards.

To ensure compliance in these cases, a more robust external assessment program with documented evidence is recommended, including:

• Board meeting minutes discussing audit-related topics;
• Approved audit charter;
• Validated audit plan and budget;
• Audit manual;
• Continuing education plan for the chief audit executive;
• Records of participation in professional events.

Conclusion

Domain III of the Global Internal Audit Standards enhances concepts already present in the IPPF 2017, emphasizing internal audit independence, qualifications, and board oversight. The board’s role is strengthened in ensuring resources and quality supervision, guaranteeing that internal audit has a strategic impact within the organization.

My recommendation is to conduct a compliance assessment against the standards in this domain and, for any identified gaps, define the necessary actions to ensure adherence.

Be happy!

Produced with the help of human intelligence