By: Dr. Marty Trevino

Despite untold global investment in analytics and technical systems, including AI platforms, most organizations report marginal improvements in strategic decision-making performance. The fundamental problem isn't computational power, data availability, quality, or algorithmic sophistication; rather, it's the incongruent design of modern systems with the human brain, which creates cognitive friction when the brain is forced to interact with interfaces designed around deterministic precepts and technological constraints rather than cognitive science principles.  

In the realm of strategic decision-making, cognitive friction reveals itself as the mental effort required to translate between the brain's natural interrogation, thought, and higher-order processes and artificial interface paradigms. While invisible to traditional metrics, cognitive friction is 'felt' by the user, and visible manifestations are almost always present in the form of avoidance or the retreat to "gut" decision making. Senior leaders report difficulty describing this phenomenon in words; thus, it is 'brushed off' as the way things are, and more tangible things remain the focus of technical teams. In addition, systems are developed by technologists and data "purists" who subscribe to false tenets of decision-making and have little understanding of the way the brain interrogates, forms mental models (reference frames), and makes decisions with data.

A  unique solution may lie in a fusion of technology and neuroscience in what we will call the Intelligent User Interfaces (containing Agentic and World Model capabilities). This conceptualized dynamic system, where AI continuously constructs and reconstructs personalized information environments based on individual cognitive signatures, creates a level of complementarity that is not present in today's first and second-generation user interfaces.

The Cost of Cognitive Friction

The Productivity Gap

Enterprise technology investments consistently underperform expectations. A Deloitte Study stated that "67 percent of those surveyed (senior managers or higher) say they are not comfortable accessing or using data from their tools and resources." The hidden culprit is cognitive friction — the misalignment between the design thinking of User Interfaces (UIs) and the brain's decision-making process with data, as well as the mental effort required for interacting, perceiving, and interpreting data and information on user interfaces.

Decision-Making Degradation

Paradoxically, more data and sophisticated analytics often correlate with slower, less confident decision-making. Research from Harvard Business School demonstrates that executives provided with comprehensive dashboards take 40% longer to reach strategic decisions compared to those working with targeted, cognitively-optimized information presentations.  

The root cause traces back to misaligned design and cognitive load. Traditional interfaces are what I call 'abstractism' to the brain. My statement doesn't need extensive proof, as 30 years ago, no human had ever encountered a dashboard or visual analytics. We can also adopt a more scientific approach. Let's consider the scientifically validated concepts of memorability. Human memory has several unique qualities; two are that it is time-sequenced and invariant. This means we recall individual items within chains of events, and our brain can remember an entire sequence from a single aspect or component of that sequence.   

Recent cognitive science research confirms that human spatial memory is primarily viewpoint-dependent, with individuals recalling more effectively from perspectives they have both seen and verbally described. We observe this in everyday examples: "remember the BBQ last summer," someone might say; "No," might be the response, followed by "the one where Aunt Mavis burned the beans"—"Oh, yes… And the BBQ was terrible, and the weather was so hot," the person then recalls a series of events starting from a single element, all of which is viewpoint dependent and spatial. This understanding is crucial for reducing friction between humans, technology, and AI, and for enhancing their complementarity. Memory is closely connected to emotions and isn't meant to recall events exactly; instead, it preserves associations and outcomes, helping us repeat positive experiences and avoid negative ones. Eye-tracking experiments from decades ago by Alfred Yarbus demonstrate that data exploration is highly individual. Research also shows that how a person investigates data orinformation is heavily shaped by their psychological trait and