The Brain's CEO & Future of AI Collaboration: Executive Functions

Why Executive Functions Matter -- Especially for Leaders in Finance

Executive functions (EFs) are a set of high-level cognitive processes that control and regulate other cognitive functions. Much like an executive guiding a company, these brain processes allow us to plan, organize, focus, and adapt so we can achieve higher levels of success and lead ourselves and others toward goals. They are aptly named, as they mirror the responsibilities of an executive in an organization: gathering information, making decisions, regulating actions, and changing course when needed. In the real of business and finance, these skills underpin effective leadership and strategy. A finance executive with strong EFs can analyze complexity, remain agile amid change & uncertainty, effectively leverage AI & technology, while fostering a culture that blends discipline and creativity.

In previous articles on Tech Tuesdays, I explained some of my research on Attention (selecting and sustaining focus - and the key to modern AI) and Working Memory (holding and manipulating information) - both of which are core executive functions crucial for goal-directed behaviors. Now, building on that foundation, we look at the broader suite of EFs, which include abilities such as planning, decision-making, problem-solving, cognitive-flexiblity, and more.

As always, you'll find practical solutions for executives to implement and details about AI below.

Executive functions are critical in virtually every walk of life, because they enable goal-directed behaviors: they help us plan for the future, adjust to new information, mentally play with ideas, consider what to do next, and stay focused on what matters (Neuro-Empowerment of Executive Functions in the Workplace: The Reason Why). Studies have shown that strong EFs correlate with better job performance. In professional settings, especially in high-stakes fields like finance, well-developed executive functions can be a decisive advantage. Successful professionals and leaders tend to display strong cognitive and self-regulation skills, allowing them to navigate complex responsibilities more effectively.

The brain’s prefrontal cortex acts like a “chief executive,” overseeing complex cognitive processes. It integrates information (like a CEO gathering data) and uses it to plan, decide, and control actions.

memory.ucsf.edu BrainFacts.org

Core Components of Executive Function

Grouping executive functions into a few key components helps us create a mental model we can use for research or to incorporate insights for our teams. A common framework identifies three core EFs: working memory, inhibitory control, and cognitive flexibility (Cleveland Clinic Article). These foundational skills work together and enable higher-order abilities like reasoning, planning, and problem-solving.

More than a decade ago, I borrowed from The Data Science Venn Diagram from Drew Conway to create my own model for assessing people and team members that is still useful today. Instead of Math & Stats, the abstraction "Core Skills" applies to any role, but should be used far beyond a job description. Replacing Hacking Skills with "Automation" allows me to consider the ability to scale one's time through technology or delegation. And I've expanded Substantive Expertise into "Value Creation" where I encompass both the deep understanding of a subject and that desirable ability to deliver solutions that fit the market at your highest and best use.

These elements of a success are guided by the executive functions for the individual, the team, and the organization. In the brain, the major executive function skills operate in concert. Here are a few details about the EFs we previously explored and their current AI equivalents:

• Working Memory: The ability to hold and mentally manipulate information in short term. It's the mental "scratchpad" for problem-solving and planning. This is very important while "finger-tracing" across disparate documents to determine if everything is correct in finance.
• Inhibitory Control (Impulse Control): The capacity to restrain impulses and distractions, allowing you to stop automatic or inappropriate responses in order to achieve goals. Discipline to avoid executing that trade, lose focus in a meeting, or response inhibitions, like thinking before speaking or making poor decisions under pressure are great examples.
• Sustained Attention: The ability to maintain focus on a task or goal over an extended period, especially when it's tedious or distractions are present. This is critical when reconciling financial documents, reports, SSIs, loan documents and beyond to monitoring market trends.

Artificial Intelligence (mid-2025) Abilities in Attention, Working Memory, & Inhibitory Control: (see previous article links above) AI and humans handle attention very differently. AI doesn't get distracted, it'll tirelessly process whatever data it's given. If you have many data streams, AI has an advantage where it can monitor thousands of signals at once without fatigue. As for working memory, AI systems with access to data through a Knowledge Graph can "remember" far more information than we can, and retrieve it without errors. The latest AI (especially in language with LLMs) has a handful of guardrails and rules that are being continuously updated to help with inhibitory and impulse controls, but are still fundamentally inference based and can impulsively provide information from other sources or even generate other incorrect information. Current AIs do not have emotions, which means they don't need "emotional control" in the human sense. This is great to avoid stress or panic in a crisis when you need consistent behavior. Algorithmic trading systems won't give in to fear in a market crash. The lack of emotion is also a weakness if not carefully implemented for ethical decision-making or even interactions with your team members. For example, overly positive AI that is mimicking human emotion can lead to short-sighted acceptance of AI generated code.

The biggest catch? AI lacks the rich, contextual integration that humans have. We don't just store and retrieve data, we interpret it. Without external systems, AI models have memory limits (like context windows in LLMs). Additionally, AI doesn't know what information to forget.

Context is the hidden thread that ties executive functions together, providing clarity, relevance, and direction to decision-making.

The remaining major EFs are more familiar to leaders in their day-to-day work:

• Cognitive Flexibility (Flexible Thinking): The ability to shift mindsets, utilize multiple thought frameworks (Design Thinking, Vertical & Horizontal/Lateral Thinking, First Principles Thinking, Systems Thinking, Disruptive Innovation, etc.), and adapt to new rules or situations when needed. This means you can adjust your thinking when your plans may not work out, or consider alternative perspectives on a problem. Cognitive flexibility is the basis for skills like multitasking (shifting or automating attention amongst tasks) and creativity in problem-solving.
• Planning and Prioritization (and Prediction): The ability to visualize and frame a goal, the path to get there, and decide the importance and timing of tasks. This involves forming strategies, organizing steps in sequences, and anticipating needs, costs, blockers, risks, and rewards. We also predict probable actions and states, understanding that something may happen, something may change or may be different through variations. Good planning skills help in everything from scheduling to orchestrating complex projects and products. They are based in our natural abilities to predict and determine the best course of action.
• Organization & Time Management: Keeping track of information and structuring your environment, tasks, and time. This includes creating order, aligning desired outcomes and metrics, and managing deadlines. Working with teams (that fall into the correct RACI)to understand the Rough Order of Magnitude (ROM Estimation), the resources' Velocity and Capacity, and the RAID will allow more effective organization and time management across teams of all sizes.
• Task initiation & Goal-Directed Persistence: The ability to start tasks promptly and persist until completion. Sitting down to begin a annual or quarterly planning, difficult analysis, or starting that next task and then sticking to the work over months. Ensuring you set the lead and enable your teams to be accountable and responsible for their own objectives and the tasks they need to complete is the way to deliver.
• Metacognition (Self-Monitoring): The process of "thinking about thinking" or monitoring & evaluating you and your teams' cognitive performance. Metacognition lets you observe how you're thinking about a task and how you are doing it. For example, realizing that a strategy isn't working and needs adjustment. Strong self-monitoring, awareness, and Sprint Retrospectives helps an individual and teams to catch mistakes, double-check work, results, and change approaches if needed. In essence, these are the feedback loop mechanisms that guide improvement.
• Emotional Control: Managing one's emotional responses, especially in pursuit of long-term objectives. This involves staying calm under stress and regulating mood so that emotions (like frustration, anger, or excitement) don't derail decision-making. For instance, a trader or AI won't panic-sell during a market dip if they can stick to the strategy. Emotional regulation is closely tied to inhibitory control as we mentioned above, it's about inhibiting outbursts or anxiety so you can respond thoughtfully.

Artificial Intelligence (mid-2025) Abilities in Cognitive Flexibility, Planning & Prioritization, Organization & Time Management, Task initiation & Goal-Directed Persistence, Metacognition (Self-Monitoring), and Emotional Control: With the rise of artificial intelligence, an intriguing question is how well AI can perform tasks that require what we think of as executive functions. Today’s AI systems have superhuman strengths in some areas relevant to executive function, but also glaring weaknesses in others, especially when it comes to the flexibility and judgment that humans possess.

We'll dive into each of these main functions of Executive Functions and AI in future Tech Tuesdays so stay tuned, but here's a teaser for the future:

AI has proven exceptionally good at problem-solving in well-defined domains. For example, algorithms can solve complex optimization problems or beat humans at strategic games by planning many moves ahead. In structured environments with clear rules and goals, AI’s logical planning abilities and sheer speed are unmatched (AI vs Human Intelligence) However, in open-ended, real-world scenarios, AI struggles. Humans excel at planning in the face of uncertainty, using intuition and creativity to outline a course of action even when many factors are unknown. AI’s planning capabilities, while powerful in narrow contexts, often falter with complex, unstructured problems or novel situations. For instance, an AI can optimize a supply chain under known parameters, but if a completely new disruption happens (say a one-off black swan event), the AI might not know how to adjust unless that scenario was in its training data. Humans can imagine and mentally “play with” ideas to devise new solutions (NIH.gov Article), but AI typically lacks this flexible imagination.

Artificial intelligence, for all its advancements, highlights both the power and the limits of these executive functions. AI can turbocharge certain aspects (like data analysis, speedy problem-solving, and even elements of planning), showing us how much more we can do with enhanced “cognitive tools.” At the same time, where AI falls short – in adaptability, common sense, ethical judgment, and self-awareness – we gain a new appreciation for the sophisticated capacities of the human frontal lobe. The current state of AI suggests that human executive functions are not about to be fully automated away. Instead, they are becoming more important: humans need to use EFs to orchestrate AI tools effectively, deciding when to trust the data and when to rely on intuition, how to adapt strategies that AI proposes, and how to ensure that our technology usage aligns with our larger goals.

In practical terms, the rise of AI is leading to a model of augmented executive function. By delegating certain tasks to AI – be it crunching numbers, monitoring information streams, or drafting initial plans – human executives can alleviate their cognitive load and focus on what humans excel at. The future likely belongs to those who can harness AI as a collaborator, using it to extend their executive control. As one expert insight noted, the most effective outcomes arise when AI’s computational power is paired with human creativity, adaptability, and emotional intelligence, yielding a result that neither could achieve alone

This Week's Practical Executive Suggestion:

Executives in finance can amplify their impact by explicitly cultivating context-aware decision-making practices within their teams. One practical way to achieve this is by systematically pairing critical financial data analysis with structured "context-checking" sessions, ensuring that underlying assumptions, environmental factors, and evolving market dynamics are clearly understood and documented. By encouraging routines such as brief, regular "context retrospectives," leaders can guide their teams to flexibly adjust strategies, proactively manage cognitive biases, and sharpen impulse control, ultimately transforming raw information into actionable financial insights and agile, informed decisions.

Conclusion:

In conclusion, executive functions remain at the heart of what makes for capable leaders and professionals. They are also the blueprint for what we aim to instill in our AI systems. By understanding our own cognitive strengths and weaknesses, and by recognizing how AI can complement (but not replace) them, we can design workflows and tools that automate the tedious and illuminate the complex. This allows human executives to do what they do best: think strategically, make wise decisions, and guide their organizations forward in an ever-changing world.

What executive function do you see AI struggling with the most today? And what would you prioritize building next?

More about the author:

Nick Baguley is an AI visionary and transformative leader known for pioneering breakthroughs at the intersection of Artificial Intelligence, Big Data, and financial innovation. From shaping national Big Data initiatives at the White House OSTP and NSF to spearheading the development of Experian Boost, driving nearly $1B Mastercard acquisitions, and now revolutionizing Knowledge Process Automation as CTO at DeepSee.ai, Nick’s career has consistently been about enabling positive disruption. With deep strategic clarity, unmatched technical acumen, and a human-centric vision, he empowers organizations to embrace change, redefine possibility, and achieve scalable impact.