Strategy | Expression of Equilibrium
applied intelligence (ai) Finding the Whitespaces of Market Opportunity
“Let us note that art — even on an abstract level — has never been confined to ‘idea’; art has always been the ‘realized’ expression of equilibrium”
— Piet Mondrian
With strategy development increasingly being intertwined with rapidly evolving AI-based technologies, we can become overwhelmed by the dominating narratives and not apply our intelligence effectively about how to utilize these technologies best. Advanced data analytics and AI can help our value enhancement in the marketplace, but it can also harm us if we don’t understand how best to use them. It is imperative, therefore, that we don’t allow ourselves to become intellectually lazy and willingly misinformed about the optimal use of artificial intelligence in our organizations and lives.
Not falling for the self-serving narratives of big tech and big consulting is critical to avoiding undesired outcomes when engaging with AI, particularly generative AI. A clear understanding of these technology tools and how they can improve our marketplace value proposition is paramount. Ultimately, the choices we make about the technologies we use will determine our good or poor outcomes in the new economy.
One thing has become abundantly clear: We must keep our eyes wide open to the pitfalls of over-reliance on big consulting and tech incumbent systems and technologies, apply our applied intelligence and critically think and act in our own best interests.
In a world dominated by the inertia of big tech and big consulting narratives, many intelligent people struggle to think critically in articulating their thoughts. The ability to be skeptical and apply one’s intelligence critically is a superpower inherent in us all. But that superpower must be activated and used effectively in the AI age. We must keep our heads when everyone else around us is losing theirs and continue to apply our intelligence to the right value-creating tasks that can improve the competitive value of our organizations.
The applied intelligence (ai) process offers a disciplined framework for critical thinking and objective analysis — a sanctuary for intellectual consideration and knowledge acquisition.
The emphasis is on logic, which is intrinsic to Einstein’s scientific process of discovery, which encourages us to find our way via the scientific process and not fall for noise and nonsense. Find our authentic voices in the diversity in thinking, creativity and innovation.
The best definition of intelligence, therefore, is intelligence can be defined as the ability to solve complex problems or make decisions with outcomes benefiting the actor and has evolved in lifeforms to adapt to diverse and challenging environments for their survival and reproduction.” AKA, the Sophistication-of-Self-Preservation (SSP) unique to humans and can’t ever be replicated in machines.
Applying Our Intellect
Former MIT professor and the Father of Modern Linguistics, Noam Chomsky, discussed the limits of AI recently on the Practical Wisdom podcast. Chomsky explained why we are making way too much of AI, which is not helpful, he says, to human progress.
He voices his skepticism about the current state of AI, particularly tools like ChatGPT, which he warns are not as capable as many believe. He unpacks the myths around general artificial intelligence (AGI) and cautions against viewing machines as conscious or intelligent beings. Chomsky shares his deep skepticism about artificial intelligence, explaining why even a 2-year-old has more understanding and adaptability than the most advanced AI tools like ChatGPT.
According to Chomsky, AI systems like ChatGPT don’t truly “think” or understand language; they only execute pre-programmed patterns and algorithms.
Highlighting the risks of believing in ‘AI everything’ as the main solution for human problems, Chomsky explains why machine learning lacks the genuine insight or awareness that defines human thought. He challenges common assumptions about AI’s capabilities and explores and provides better insight on the true utility of AI as a technology tool: machines run programs and apply pattern recognition but are not entities capable of understanding or generating language in a truly meaningful way, says Chomsky.
The AI pitch has been overly hyped, and it is neither a revolution nor will it transform everything! While it certainly adds a transformative dimension, there can be no doubt about that, but it is not transformative on its own. No person or technology is an island.
“Beware of false knowledge; it is more dangerous than ignorance,”
— George Bernard Shaw.
In a paper published in 2024, Apple researchers, after testing several LLMs, found that these models are incapable of performing genuine logical reasoning. Apple AI scientists demonstrated that even the most highly praised advanced Large Language Model (LLM) lacked basic reasoning skills, making it unworthy of discussion in comparison to human intelligence and reasoning abilities. This further substantiates what Noam Chomsky has asserted about the capabilities of a two-year-old versus an LLM.
What has been created after all is said and done and billions, if not trillions spent, is a bubble of nonsense that has set back humanity instead of meaningfully advancing it.
Understanding how AI works isn’t difficult, yet the ecosystem in Silicon Valley and their courtiers have created substantial hype, making AI appear more complex and amazing than it truly is.
In brief, AI employs ‘deep learning’ (which is merely a concept or theory, not an actual entity); these ‘learning’ algorithms identify trends in data. They then extrapolate from the data, generating new information along the same trend line. Attention! This is not learning. This is merely training the AI with vast amounts of data fed for analysis, including the biases of the programmer (another problem to solve), which allows the training data/system to advance more trends… and so forth.
The AI can subsequently be queried for outputs, creating an illusion of intelligence without any real intelligence, merely programming that often hallucinates — so it can’t be relied upon.
In Our 1000-Year Struggle Over Technology & Prosperity, the subtitle of a book by two MIT professors, Daron Acemoglu and Simon Johnson, titled Power And Progress says:
“A thousand years of history and contemporary evidence make one thing clear: progress depends on the choices we make about technology. New ways of organizing production and communication can either serve the narrow interests of an elite or become the foundation for widespread prosperity.”
Our choices matter! But if we allow others to be the arbiters of our lives, e.g., big tech and big consulting, we sacrifice not only our individualism but our future prosperity. The authors of Power And Progress tell us that it doesn’t have to be that way; their survey of the last 1000-years of technology and progress reveals that:
“Cutting edge technological advances can become empowering and democratizing tools, but not if all major decisions remain in the hands of a few hubristic tech leaders.”
Each of us has the mental capacity or will power to resist being dominated, not succumbing to the brute force tactics of big tech and large consultants that prioritize their business models and financial interests over optimal client-centric solutions. Therefore, applied intelligence (ai) assists individuals and organizations in separating noisy abstractions and moving us towards the internal strategy development to help them effectively compete and win!
Regarding strategy and technology: if AI is regarded as anything other than a really helpful tool that can expedite processes and tasks through its primary capability of scanning vast amounts of data for pattern recognition and identifying statistical regularities for humans to analyze and derive insights. Then we are wasting an incredible amount of time, deceiving ourselves and indulging in science fiction. There is no consciousness associated with AI, as per the definition of intelligence stated earlier.
There is no thinking happening with AI because thinking requires consciousness, and AI doesn’t have consciousness, so it can’t think nor can it understand the real world — it lacks awareness of meaning.
The ai Strategy Process
A Harvard Business Review highlights that 97% of senior leaders have said strategy is the most important thing to their organization’s success, but 96% said they lack the time and the right tools to effectively engage in strategy development within their organizations, says HBR.
At its core, applied intelligence (ai) is an augmenting process which adheres to Einstein’s process of discovery, and yes! It’s the same process that led him to the discovery of the Theory of Relativity. Einstein said the discovery process is the essence of the scientific process and basic common sense. This, too, is the fundamental approach ai takes to best leverage technology and innovation, helping users develop robust and high-velocity strategies for winning in the digital age.
Since the founding of McKinsey and Company in 1926 by James O. McKinsey, management consulting has always been about being more than it is, and over the many decades, it has attached itself to neoclassical economic narratives: ideologies about efficiencies by cutting human resources. Management accountants look to ‘drive efficiencies’ primarily by cutting costs, and one of the easy ones has always been cutting human resources and moving to “contracts;” of course, the consultants then get those contracts. It’s a scam!
The big tech/big consulting industry continues to leverage these self-serving neoclassical economic narratives in their financial and political interests. Similar to today, what Elon Musk has been able to pull off with the United States government — cutting government employees; we can guess who will get all these new government contracts? Same game, different times.
On the corporate side, consulting advisory firms have never proven to increase sustainable growth over the long-term! The evidence suggests that it does nothing for long-term growth, but despite all this, organizations, particularly those with scaredy-cat CEOs, continue to call on consultants. Primarily to have someone to blame in front of shareholders when the shit hits the fan and things don’t work out. This is a cynical, dirty, and not-so-secret occurrence in the corporate world: #blametheconsutants.
Big consulting and big tech enjoy a symbiotic and mutually beneficial relationship; sucking up all the oxygen and leaving no room for more honest, practical, and cost-effective solutions that can make strategy development more broadly accessible to all.
6ai Technologies, however, seeks to disrupt and offer an alternative to brute force one-dimensional strategy development offered by big consulting firms. Which serves to hollow out our organizations.
Generative AI and open source are democratizing access to technical capabilities once dominated by incumbents. DeepSeek confirms that, and 6ai is creating a useful platform interface designed for strategy development. Allowing for easy navigation and creation of highly useful fact-based strategies. Enabling those without technical backgrounds the ability to develop highly effective strategies without having to learn complex software or digital tools.
Replacing big consulting and big tech-dominated solutions with easy-to-use solutions at a fraction of the cost is the mission of applied intelligence’s (ai) proprietary six-step (6ai) process that guides the user through a step-by-step scientific discovery strategy development process. Retrieving highly relevant information from verified and reputable sources that can be taken as empirically warrantable.
6ai is an AI-assisted but human-centric proprietary solution that builds strategy through its six-step applied ai process. Ideas and objectives are guided through our Insight Engine’s IVA (Information Valuation Assessment) process. Ensuring facts, iteration and logic are applied purposefully to the problem for coherent and empirically warrantable outputs — turning insights into useful and executable strategies for real-world application.
LLMs lack basic reasoning, and nuance can’t be programmed, so we are going nowhere with AGI Sci-Fi. The human executive decisioning function will always be required and plays a supervisory role, which allows the ai-process to enhance and maximize human general intelligence by purposefully utilizing narrow (AI) machine memory capacity. This process is then integrated into human-first workflows, offering a reliable, user-friendly, do-it-yourself strategy development process to achieve great things.
Facts, too, can be “statements about phenomena, but they don’t exist on their own; they are always conceptualized, which means that they are, if only implicitly, constructed theoretically,” says cosmologist Stephon Alexander. Accordingly, it is useful to have a process to evaluate information to look behind the facts because facts, too, can be theoretical concepts promoted by a motivated few. We must take nothing at face value and hold up analysis to scrutiny.
Hence, the first step to applied intelligence (ai) is using the principles and values to guide the decisioning process: applying mathematical robustness to strategy development. Similar to integrals in calculus, ai performs a series of steps along the way to strategy completion. Each step passed confirms or ensures that we are on the right track to the whole strategy. The integral process is essential to solving the whole problem and providing viable solutions.
Strategy is hard work with lots of complexity, and the amazing computational power of computers coupled with authentic human intelligence is the optimal approach. But strategy can’t ever be 100% automated.
So, like most things, balance is best. Like in politics, it’s the political centre that’s most effective, and in economics as well, it’s about finding the dynamic equilibrium. The right robustness and velocity for the most productivity outputs.
When things stray from equilibrium, they often break down, and when humans go to their respective corners of competencies or feelings, nothing good is usually achieved. Things get stuck in the abyss of noise and nonsense, and low or no productivity happens — stuck in theoretical constructs that don’t align with reality.
The comparison then is that the human-based consulting, the manual process for strategy development is on one side; call it the Right, backwards, fear of progress and change, clinging to the past because they can’t compete with modern competition. This side resists useful technologies even when they can make things better for them — fear of being replaced dominates. Then there is the pure automation side, i.e., AI; call it the Left… the brute force, everything AI approach. Both are extreme and not helpful to human progress.
We must find the progressive middle ground and get on with it. We can’t stop technology and change, so let’s stop sulking and make hard decisions on how we want to design the future of work in our best interest and not the interests of the big tech and big consulting industry.
As with ecology, a balanced relationship, equilibrium, between living organisms, including humans, and their physical environment is necessary for civilizations to thrive; there is no doubt about how nature works and finds its equilibrium.
The applied intelligence (ai) core value proposition offers a practical software solution for optimal strategy development — the equilibrium solution between human and machine processes. Maximizing the core values of each to effectively build a compelling single practical solution everyone can use.
The Strategy Canvas
How a company uses advanced technologies to create value has become the defining business challenge of our time. The applied intelligence process incorporates ‘both sides’, helping to make the right decisions to either protect a business’s position, re/pre-establish relevancy, or prepare for the future.
There are two fundamental approaches to AI. The first is exclusionary and impractical, the far right side of automation, the pursuit to make AI competitive, surpassing, and replacing human intelligence. This is the AGI pursuit, science fiction, in the sole interest of the OpenAIs of the world — the usual suspects, the Silicon Valley ecosystem world.
The second is our ai approach, inclusive and human-centric, based on reality and understanding the limitations of technologies. This approach does not pursue any alternative to human intelligence. Instead, it takes an augmenting approach, using generative AI, as necessary, to amplify human intelligence, practically, purposefully and responsibly — augmenting human intelligence capacity, capabilities, and ingenuity.
The six-steps (6ai) is an easy-to-use system that guides users through a proprietary insight engine, anchored by logic and human empathy, with a back-and-forth interaction process (voice and text) between human and machine, in pursuit of useful insights. A higher dimensional level of useful information retrieval from relevant and reliable sources turns insights into strategy that can be taken as empirically warrantable.
6ai-IP includes purposeful functions: Focused Language Models-Templates (FLM-T) — smaller and more precise. Focused is better than large and hallucinating LLMs. The Strategy Development Canvas (SDC) brings it all together in a dynamic and continuously active way, platform ready and accessible to teams.
By embedding the right process algorithms in its functionality, we focus our ai decisioning systems and language models to pull highly relevant and useful information downstream and continue to move through the six-step process diligently. Utilizing technologies’ extraordinary enterprise worth and applying it to the right value advancing tasks and processes, to deliver risk-adjusted growth for the modern enterprise!
Highly accessible and at an extraordinary price point in subscription form. Anyone inside the organization can design and run strategy: from high-level, multi-billion-dollar corporate strategies to personal growth strategies at an infinitesimal fraction of the cost.
If we continue to over-hype AI and not deliver, which is the case currently, people simply won’t use it. It is best then to be honest about what AI can and cannot do and how it can be useful as a strategy partner.
AI can’t replace critical human persuasion, passion, negotiation, vision and leadership — ai’s mission is to be practical with user-friendly experiences, for robust integration of humans and machines in the pursuit of internal strategy development at scale!
Whitespaces of Market Opportunity
Many of today’s leaders have risen by applying their expertise and niche skill sets within their respective specializations; however, in the digital age, this has become relatively less critical to the enterprise. Data and insight generation is becoming increasingly important to decision-making and strategy formulation.
The rapid pace of ever-advancing innovation is increasingly putting pressure on leaders to enhance their organization’s decisioning resources. The long-time successful specialists and trailblazer executives are now confronted with the reality of an advancing hyper-competitive digital economy. Accordingly, strategy has risen to the top of organizations’ priorities in the new global economy.
Using data science for effective decision-making is part of the applied intelligence (ai) belief in the scientific equilibrium being the best solution to pursue in getting things done. This represents the interception between human intelligence and amazing AI/data memory capacity and capabilities. The combined power gives organizations their best competitive advantages.
Internally driven strategy development, then, is about developing your own clear playbook and integrating with advanced technologies across the entire organization. It’s about a real culture shift, depending on your qualified people inside the organization. Not outsiders.
A world where anyone can construct a series of processes to identify the whitespace in industries or sectors that can offer opportunities to generate 100M + market opportunities. Full picture views to identify the whitespaces of opportunity — there are four main components to this:
01. Understanding the Landscape: The first step of knowledge extraction is to identify all of the entities and structural data within a set of documents from the target industry: the people, places, concepts, numbers, sentiment, patents, articles, quotes, etc. A series of custom classifiers extracted and resolved those entities, storing them in a knowledge base. Then, we identify relationships between pairs of entities using unsupervised methodologies. Every piece of data that is captured retains its provenance, giving full transparency on the decisions made by the downstream algorithms.
0.2 Confirming the POV: the ai software assists us in constructing models of reality based on streams of millions of documents. By de-duplicating and reconciling statements made by multiple observers, we create an ensemble version of the corpus. For any given event, there can be thousands of varying descriptions, from the people involved to the tiniest details. Taking a multi-document approach allows us to capture this variation as signals rather than noise. The multi-document multi-observer approach improves the performance metrics of our insight engine.
0.3 Identifying Opportunity & Areas of Risk: Strategy development must have a natural risk management function to it. A good strategy must not only identify the opportunity but also the risks. For example, which areas of R&D are likely the next big things? What’s the best way to execute? Identify the potholes in the road ahead. Strategy mapping and validation of innovation functions through mathematical patterns within patents, scientific papers, and capital allocations. We can drill down on the areas of the organization’s unique value proposition or IP that may be highly contested in the marketplace and how to develop Blue Ocean strategies to create new demand — making the competition irrelevant. By understanding the relationships between established sectors’ macro and micro processes, leaders can identify and isolate the whitespaces of market opportunity for growth.
0.4 Decisioning: At this point, we can make well-informed decisions with the highest probability for future success. Do we exploit the opportunity and develop it, do we find a target acquisition, a partnership, sell an asset, develop IP in-house, etc? After the ai has done the heavy lifting and laid things out sequentially, humans can now make executive decisions with a level of confidence.
We must not stop learning and staying true to the scientific process. We can’t limit our research or hold back on challenging incumbents or conventional wisdom. Acquiring knowledge and developing strategies to make our lives better is at the core of an advancing civilization. Which remains a human endeavour! We must not take sides and be dogmatic or hubris with our approaches to strategy. Intelligence is not about knowing all things; it’s about narrowing your focus relative to the problem you want to solve.
This is why, logically, LLMs can’t ever be the best solution for human-centric strategy development. Using highly focused data science, advanced analytics, and specialized cognitive IP to test and relentlessly iterate ideas against prevailing marketplace reality is what must be pursued.
