Why Every Company Needs a New Type of Operating System Enhanced with Artificial Intelligence


Kyield founder Mark Montgomery on top of NM Oct., 2016, taken by Betsy Montgomery with their dog Austin


The Amazon acquisition of Whole Foods represents yet another confirmation of our rapidly changing business environment driven by opportunities at the confluence of technology and network dynamics. Although only the latest in a powerful trend initially impacting in this case the grocery industry, the business and technology issues driving the strategy are relevant to most and serves as a reminder that digital convergence is not confined to traditional thinking or industry lines.

A sharp devaluation of public grocery companies followed, so apparently many investors share concerns highlighted in the current HBR article “Managing Our Hub Economy”, which warns that “most companies will not become hubs, and they will need to respond astutely to the growing concentration of hub power”. The devil in the details for management is how to respond astutely. The answer is largely an AI OS.

A recent article at MIT SMR describes the complex operating environment: “The Five Steps All Leaders Must Take in the Age of Uncertainty”:

These ecosystems are nested complex adaptive systems: multilevel, interconnected, dynamic systems hosting local interactions that can give rise to unpredictable global effects and vice versa. Acknowledging the unpredictability, nonlinearity, and circularity of cause-and-effect relationships within these systems is a notable departure from the simpler, linear models that underpin traditional mechanistic management thinking.

One of the reasons for the attention in this latest combination is the integration of virtual networks with physical locations, which has been a priority for many companies, including Kroger, which shares many of the same zip codes as Whole Foods. A few days following the announcement Kroger Chairman and CEO Rodney McMullen revealed that he wasn’t surprised: “you could tell that Amazon wanted to do something from a physical asset standpoint and I think Whole Foods is a great fit for them.” Kroger is a well-managed company known for wise use of analytics, which is reflected in McMullen’s advice to investors: “you should assume that we look at any potential opportunities”.

We needed a new operating system” – Doug McMillion, CEO of Wal-Mart Stores, Inc.

The question is will traditional methods be sufficient moving forward? The answer may be found in part by looking at the world’s largest retailer. Wal-Mart was viewed as one of the most stable companies before Amazon entered their core lines of business, eventually leading to the recent conclusion by Wal-Mart CEO Doug McMillon: “We needed a new operating system”. The company recently paid $3 billion for an e-commerce component of a new OS in Jet.com, which may seem excessive to those of us unaccustomed to managing a half-trillion USD in annual revenue, though represents a relatively minor investment if it works well.

Unfortunately for 99.99% of businesses, investing $3 billion in a native e-commerce platform is not an option, particularly one experiencing significant losses. Very few of the remaining .01% could consider doing so for a partial OS. Even Walmart’s bold actions appear insufficient when we consider that the acquisition of Whole Foods was powered less by the core business of Amazon or Whole Foods than the bold manifestation of what was previously learned, resulting in an entirely new and much better business model in AWS (see article on spinning off AWS). Amazon’s strength is its ability to learn rapidly, recognize potential, and then convert and realize interconnected opportunity to new offerings in a fiercely competitive manner.

Competing in such a hypercompetitive and rapidly changing environment can be especially difficult for companies thinking and behaving in a linear manner. The retraining for me personally that began in our lab in the 1990s was a profound voyage initiating from a relatively high level. The technical training and transition involved a sharp learning curve that has only become steeper and more intense with time.

Native platforms are quite different than corporate networks that have evolved incrementally over decades. Understanding related opportunities and risk many years in advance is a critical challenge. One must peer through an asymmetrical prism constructed from tens of thousands of hours of total immersion and make bold bets that are well timed, particularly with AI systems.

Among many lessons learned is that the network economy is not only interconnected, it is also multidimensional and pre-programmed. When managed optimally and competitively the entire experience of the customer is an obsession with little deference for traditional lines.

Important considerations for an AI OS

1 – A competitive AI OS will be necessary for most to survive

Essentially all the evidence we see with mid-size companies to market leaders across most industries is that a strong AI OS is rapidly becoming the new competitive bar. If a company doesn’t have a competitive AI OS platform and the competition does, it will likely negatively impact the entire organization and each individual within it, as well as customers and partners. Google and Amazon are examples of companies that appear to be employing some functions similar to those found in our Kyield OS. While leadership and corporate strengths are critical, employing advanced AI systems is among the most important improvements any organization can make. The question really is how and when.

2  – An organization OS is not a computer OS

Many different types of operating systems exist. A few minutes of reading my book (condensed version) Ascension to a Higher Level of Performance will highlight the difference between the Kyield OS and a computer OS. The standard system is focused on universal issues common to all organizations, individuals, and networks. We have good reason to believe Kyield is among the world’s competency leaders in knowledge systems, which is a sub-specialty of artificial intelligence.

Our focus is a thin yet broad and very deep specialty with little overlap to most others, including AWS, Azure, and Google (Kyield OS integrates well with most others). Although executed with software, the Kyield OS is a ‘low code’ system compared to a computer OS and more dependent upon data and algorithmics. The system operates in the background with a simple natural language interface for corporate, group, and individual administration. The Kyield OS is transparent, non-intrusive, and interoperable so that any function can be added as needed in a highly efficient manner.

A recent note from a Fortune 50 CXO exemplifies the need from a slightly different perspective in response to our recently released HumCat offering—a new model for prevention for human-caused catastrophes, including cyber prevention.

I like your idea of an Operating System. I’m so convinced that the world is too complex and getting more complex every second that human beings cannot manage it in the right way anyway… Now, it is time (for the Kyield OS), otherwise we are on the hook of dark side of cybernetics—cybercrime or cyberwar and nobody can defend us.

3  –  Reinventing AI system wheels is not wise

As I shared with a Fortune 20 team recently, while it may be extraordinarily easy to underestimate the amount of tradecraft and secrets for such an endeavor, it is nonetheless foolhardy to do so (hence the AI talent wars). Fortunately for our customers, we’ve done the bulk of the heavy lifting. It was two decades ago this year that Kyield was originally conceived in the lab as an authentic invention (Optimizing knowledge yield in the digital workplace).

Many research and consulting reports on AI systems are available, and they have improved significantly over the past two years (See reports by MIT SMR & BCG and Nordea as recent examples), but caution is warranted. Some consulting firms are still advising to start small and experiment in areas that no longer need experimentation. Although generally appropriate five years ago, it is increasingly dangerous today as the competitive gap due to AI systems is expanding rapidly.

A good example of an ongoing experiment was highlighted in the WSJ CIO Journal: “Swiss Re Bets AI Can Help Workers Cope with Complexity of Reinsurance”. The goal is admirable, achievable and sounds impressive until reading the subtitle: “The company’s 100 data scientists and AI experts are building software that can read documents on their own.” This is not a new technology. If the article is accurate it appears that Swiss Re is spending between 10-100 times more for a small fraction of the functionality found in our Kyield OS. Other options also exist for the specific function described that would likely be much more wise than a custom effort.

Our friends at Swiss Re are far from alone. Munich Re publishes an IT radar report (with a nice diagram) based on research that “systematically analyzes opportunities, trends and technologies, and provides an ongoing insight into which technologies could be relevant for Munich Re and our customers from a very early phase”. In the current 2017 report Munich Re places predictive analytics in adoption phase while advanced machine learning and robotics process automation in the trial phase. These and other recommendations may raise some eyebrows. Predictive analytics has been deployed for many years as has advanced machine learning for specific purposes. If one is competing with a technical leader—and increasingly most are, waiting too long can be a fatal error. The first mover position, however, is not always an advantage, so such decisions need to be situation-specific.

4  – Method and sequence of adoption

To date the super majority of investment in AI systems have been strategic resulting in a few notable successes. We have also witnessed large and costly errors, including in M&A, VC, internal development, and in system designs and business models by vendors.

Horizontal systems like our Kyield OS serve as an efficient platform to unify the organization and ecosystem. Ideally a native AI OS should be adopted first. Quite apart from significant IP liability risk, since our standard system is focused on universal issues for every type of organization, with improved productivity, security, and prevention, it is difficult at best to justify internal custom efforts that replicate any of this functionality. Strategic functions are best built on top and/or integrated with our networked platform OS so that the organization and ecosystem operate in an optimal manner.

All is not lost, however, for those who have experimented in overlapping areas. The modules within the Kyield OS creates the data structure needed for compliance and then populates across the network in a manner designed to execute the functionality within the system as efficiently as possible, including for accuracy, integration and financial efficiency.


As important as external competition can be in this environment, the degree to which displacement will occur is dependent on a number of factors. All things being equal otherwise, the outcome primarily depends on the incumbent’s actions, its people, systems, and processes. Even though some companies may seem well positioned, the fundamental economic and business environment is rapidly changing. To the best of my awareness, survival from this point forward will essentially require a strong AI OS for the super majority of organizations.

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem ‘yield management of knowledge’, and inventor of the patented AI system that serves as the foundation for Kyield: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. He can be reached at markm@kyield.com.


An open letter to Fortune 500 CEOs on AI systems from Kyield’s founder


Since we offer an organizational and network operating system—technically defined as a modular artificial intelligence system, we usually deal with the most important strategic and operational issues facing organizations. This is most obvious in our new HumCat offering, which provides advanced technology for the prevention of human-caused catastrophes. Short of preventing an asteroid or comet collision with earth, this is among the most important work that is executable today. Please keep that in mind while reading.

In our efforts to assist organizations we perform an informal review on our process with the goal of improving upon the experience for all concerned. In cases where we invest a considerable amount of time, energy, and money, the review is more formal and extensive, including SWOT analysis, security checks and reviews, and deep scenario plans that can become extremely detailed down to the molecular level.

We are still a small company and I am the founder who performed the bulk of R&D, so by necessity I’m still involved in each case. Our current process has been refined over the last decade in many dozens of engagements with senior teams on strategic issues. In so doing we see patterns develop over time that we learn from and I share with senior executives when behavior causes them problems. This is still relatively new territory while we carefully craft the AI-assisted economy.

I just sent another such lessons learned to a CEO in a public company this morning. Usually this is done in a confidential manner to very few and never revealed otherwise, but I wanted to share a general pattern that is negatively impacting organizations in part due to the compounding effect it has on the broader economy. Essentially this can be reduced to misapplying the company’s playbook in dealing with advanced technology.

The playbook in this instance for lack of a better word can be described as ‘industry tech’, as in fintech or insurtech. While new to some in banking and insurance, this basic model has been applied for decades with limited, mixed results over time. The current version has switched the name incubators for accelerators, innovation shops now take the place of R&D and/or product development, and corporate VC is still good old corporate VC. Generally speaking this playbook can be a good thing for companies in industries like banking and insurance where the bulk of R&D came from a small group of companies that delivered very little innovation over decades, or worse as we saw in the financial crisis, which delivered toxic innovation. Eventually the lack of innovation can cause macro economic problems and place an entire industry at risk.

A highly refined AI system like ours is considered by many today to be among most important and valuable of any type, hence the fear however unjustified in our case. Anyone expecting to receive our ideas through open innovation on these issues is irresponsible and dangerous to themselves and others, including your company. That is the same as bank employees handing out money for free or insurance claims adjusters knowingly paying fraudulent claims at scale. Don’t treat the issue of intellectual capital and property lightly, including trade secrets, or it will damage your organization badly.

The most common mistake I see in practice is relying solely on ‘the innovation playbook’. CEOs especially should always be open to opportunity and on the lookout for threats, particularly any that have the capacity to make or save the company. Most of the critical issues companies face will not come from or fit within the innovation playbook. Accelerators, internal innovation shops and corporate VC arms are good tools when used appropriately, but if you rely solely on them you will almost certainly fail. None of the most successful CEOs that come to mind rely only on fixed playbooks.

These are a few of the more common specific suggestions I’ve made to CEOs of leading companies in dealing with AI systems, in part based on working with several of the most successful tech companies at similar stage, and in part in engaging with hundreds of other organizations from our perspective. As you can see I’ve learned to be a bit more blunt.

  1. Don’t attempt to force a system like Kyield into your innovation playbook. Attempting to do so will only increase risk for your company and do nothing at all for mine but waste time and money. Google succeeded in doing so with DeepMind, but it came at a high price and they needed to be flexible. Very few will be able to engage similarly, which is one reason why the Kyield OS is still available to customer organizations.

  2. With very few exceptions, primarily industry-specific R&D, we are far more experienced in AI systems than your team or consultants. With regard to the specific issues, functionality, and use cases within Kyield that we offer, no one has more experience and intel I am aware of. We simply haven’t shared it. Many are expert in specific algorithmics, but not distributed AI systems, which is what is needed.

  3. A few companies have now wasted billions of USD attempting to replicate the wheel that we will provide at a small fraction of that cost. A small number of CEOs have lost their jobs due to events that cost tens of billions I have good reason to believe our HumCat could have prevented. It therefore makes no sense at all not to adopt.

  4. The process must be treated with the respect and priority it deserves. Take it seriously. Lead it personally. Any such effort requires a team but can’t be entirely delegated.

  5. Our HumCat program requires training and certification in senior officers for good reasons. If it wasn’t necessary it wouldn’t be required.

  6. Don’t fear us, but don’t attempt to steal our work. Some of the best in the world have tried and failed. It’s not a good idea to try with us or any of our peers.

  7. Resist the temptation to customize universal issues that have already been refined. We call this the open checkbook to AI system hell. It has ended several CEO careers already and it’s early.

  8. Since these are the most important issues facing any organization, it’s really wise to let us help. Despite the broad characterization, not all of us are trying to kill your organization or put your people out of work. Quite the contrary in our case or we would have gone down a different path long ago.

  9. We are among the best allies to have in this war.

  10. It is war.

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem ‘yield management of knowledge’, and inventor of the patented AI system that serves as the foundation for Kyield: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. He can be reached at markm@kyield.com.

A Million in Prevention can be Worth Billions of Cure with Distributed AI Systems

Deep Water Horizon Rig (NOAA)

DeepWater Horizon Rig, April 2010 (NOAA News)

Every year, natural catastrophes (nat cat) are highly visible events that cause major damage across the world. In 2016 the cost of nat cats were estimated to be $175 billion, $50 billion of which were covered by insurance, reflecting severe financial losses for impacted areas.[i]  The total cost of natural catastrophes since 2000 was approximately $2.3 trillion.[ii]

Much less understood is that human-caused catastrophes (hum cat) have resulted in much greater economic damage during the same period and have become increasingly preventable. Since 2000 the world has experienced two preventable hum cat events of $10 trillion or more: the 9/11 terrorist attacks and the global financial crisis. In addition, although the Tōhoku earthquake in Japan was unavoidable, the Fukushima Daiichi nuclear disaster was also preventable, now estimated at $188 billion excluding widespread human suffering and environmental damage.[iii]

One commonality in these and other disasters is that experts issued advanced and accurate evidence-based warnings only to be ignored. The most famous and costly such example was the Phoenix memo issued on July 10, 2001 by Special Agent Kenneth J. Williams.[iv]  The FBI memo was described as “chilling” by the first journalist who reviewed it due to specificity in describing terrorist-linked individuals who were training to fly commercial aircraft.

Williams was a seasoned terrorism expert who followed the prescribed use of the FBI’s rules-based system, yet during the two-month period prior to the 9/11 attacks no relevant action was taken. If the lead had been pursued the terrorist attacks and ensuing events would very likely have been avoided, including two wars with massive casualties and continuing hostilities.

Government agencies have invested heavily in prevention since that fateful day of September 11, 2001 so hopefully similar events will be prevented.

In corporate catastrophes, however, prevention scenarios are usually more complex than the Phoenix memo case. They are also occurring with increasing frequency and expanding in scale and cost.

The remainder of this article can be viewed at Cognitive World.

View brief video by Mark related to this article and Kyield’s new HumCat product.

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem ‘yield management of knowledge’, and inventor of the patented AI system that serves as the foundation for Kyield: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. He can be reached at markm@kyield.com.

Why the U.S. Must Lead the World with Intelligent Infrastructure

Americans have been through a great deal in the last two decades. In addition to the network effect that consolidated wealth in a few zip codes, we endured rapid globalization that benefited other nations at the expense of our own, the 9/11 terrorist attacks, multiple wars, and the global financial crisis, all within the first few years of this millennium.

To put this series of interconnected events in perspective, the collective shock is roughly comparable to the impact of a small super volcano, a minor asteroid, or a limited nuclear war. Catastrophes of this scale are thought to be of sufficient size to change the course of modern civilization, depending of course upon our response.

The most recent CBO report forecasts the U.S. federal debt at 150 percent of gross domestic product in 2047, which would place the U.S. as the third most indebted nation in 2017 between Greece and Lebanon. This is obviously not where the U.S. wants to be in 30 years. Fortunately, such a decline is unnecessary and well within our power to avoid, though the path is narrow and hazards are many.

Catching up on deferred maintenance is a necessary but insufficient plan for the challenges facing Americans. A modern strategic infrastructure plan should be focused on unleashing the current national economy similar to previous eras with the intercontinental railroad, interstate highway system, or electric grid.

The focus should be maximize benefits from our inventions, engineered systems and technologies to recreate a sustainable competitive advantage. One benefit of lagging behind other countries in infrastructure is that much progress has been made in recent years. Future projects can be embedded with hardware that enable intelligent networks, which can then be managed with distributed operating systems enhanced with artificial intelligence (AI) to meet the diverse needs of our society.

AI systems can substantially resolve many of the destructive forces and high-risk areas facing the modern economy, including the ability to provide far more effective governance in a highly complex data-driven world, prevention of most types of human-caused catastrophes, improved workplace productivity, more effective security, and reversal of the dangerous trajectory in healthcare costs.

In order to realize the full potential of a national intelligent infrastructure strategy, it must be planned in a highly specific manner. Intelligent infrastructure is driven by physics and engineering, which can be easily damaged by misguided or corrupted politics. The value of AI systems is substantially dependent upon the availability and integrity of data. Important priorities include but are not limited to interoperability, security, privacy, business modeling, cost of ongoing maintenance, and adaptability for future innovations.

The combination of technical viability in AI systems with the current macro economic scenario has created a perfect storm for public-private partnerships. Funds with trillions USD under management are in search of improved yields in mid to long-term bonds that offer lower risk profiles and diversification, which allows risk transfer to investors for specific projects rather than tacked on to an unsustainable national debt trajectory. Moreover, the combination of intelligent infrastructure with AI systems can improve productivity, provide attractive return on investment, and create new high paying jobs that will be competitive far into the future.

The federal government should act as the policy and standards body to avoid hard lessons learned in previous national infrastructure programs. A plug-and-play architecture is needed that encourages economic diversification in all states, fosters new business formation and new wealth creation that has the capacity for reversing the increasingly historic wealth gap.

In today’s fast moving hyper competitive world, the U.S. cannot afford to wait a century to unravel the type of monopolies that were cobbled together during the formation of the electric grid. The network economy increasingly represents the entire economy so must be as diversified and dynamic as society if to remain healthy and sustainable.

If the Trump administration and U.S. Congress seize this historic opportunity for a strategic intelligent infrastructure plan, they should find bipartisan support as it can positively impact every zip code in America, which could serve to reunify the nation around common good. Executed well, a strategic intelligent infrastructure plan can serve as a solid foundational platform to solve many of the current and future challenges facing America and the world.

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem ‘yield management of knowledge’, and inventor of the patented AI system that serves as the foundation for Kyield: ‘Modular System for Optimizing Knowledge Yield in the Digital Workplace’. He can be reached at markm@kyield.com.

E-book on AI systems by Kyield

My ebook “Ascension to a Higher Level of Performance” is now available to the public.

Learn about the background of Kyield and the multi-disciplinary science involved with AI systems, with a particular focus on AI augmentation for knowledge work and how to achieve a continuously adaptive learning organization (CALO).




INTRODUCTION ……………………………………………………………………………………..



MANAGEMENT CONSULTING ……………………………………………………………………

COMPUTER SCIENCE AND PHYSICS…………………………………………………………….

ECONOMICS AND PSYCHOLOGY ………………………………………………………………..

LIFE SCIENCES AND HEALTHCARE……………………………………………………………


KYIELD OS …………………………………………………………………………………………..




BANKING AND FINANCIAL SERVICES ………………………………………………………..

THE PILOT PROCESS ……………………………………………………………………………..

EXAMPLE: BANKING, PHASE 1…………………………………………………………………

PHASE 2…………………………………………………………………………………………….

PHASE 3…………………………………………………………………………………………….

PHASE 4…………………………………………………………………………………………….



Visit our learning center to download this ebook and view other publications from Kyield at the confluence of AI systems, crisis prevention, risk management, security, productivity and organizational management.

A Visit From America’s Founding Fathers – New Year’s Eve 2016

‘Twas the week after Christmas, when all thro’ Wall Street,

Not a broker was working, not even a tweet;

401ks were chock-full from the Fed,

In hopes that someone else would put their crisis to bed;

Investors were contented with the size of their yachts,

And dreams teased of eternity on Mars with toy bots;

Small businesses were suffering, employees quite stressed,

Working part-time jobs so that others may rest,

Then storm clouds of democracy began to gather,

So I dashed from my office to see what was the matter.

I threw on my coat and ran to the train station,

Hoping that a miracle could restore this great nation.

The moon shined brightly on glistening ice,

But a cold wind on Main St. punished rolling the dice,

When, to my great surprise what did we hear?

Could that be rumblings of a government we need not fear?

With corporate jets scrambling, and lobbyists screaming,

Something awful scary must have caused this convening.

More rapid than geese in flocks they came,

And he whistled, and shouted, and called them by name;

“Now, PENCE! now, ROSS! now, TILLERSON and COHN!,


To the New York penthouse! to the top of Trump Tower!

Now heal thy economy! Make great again this power!

As surgeons faced with a pandemic of moral hazard,

When trust in institutions remained torn and shattered,

So off to the capitol as physicians they flew,

With jets full of billionaires, and Donald J. Trump too.

And then, high above the plains jet engines roared

Then screeching of tires with titans on board.

As people left offices, churches, and schools,

They whispered to each other “hope we weren’t fools”

They were dressed in fine clothing from head to foot,

Some flashing gold like some kind of crooks;

A belly full of solutions in the cargo bay,

More false promises or will they do as they say?

From heaven above the Founders looked down,

Their eyes – how wise! Their faces full of frowns!

Although they expected the corruption found below,

It still pained to witness this nation they bestowed.

So they sprang to their sleigh, a founding force of seven,

And gathered their writings; then descended from heaven,

They flew straight to the rooftops above the West Wing,

And scurried down a chimney to the room in shape of a ring;

Leaders from all three branches gathered with their teams,

Who sat silently listening, voices finally out of steam,

When ghostly founders read their papers, it was quite a sight!


Copyright © 2016 Mark Montgomery. All Rights Reserved.

Independence Day Lessons on Adaptability and Survival from the Ancestral Puebloans

Aroma Pueblo, by Betsy Genta-Montgomery Copyright 2016

Aroma Pueblo by Betsy Genta-Montgomery Copyright 2016

July 4th, 2016

The photo above represents a learning opportunity especially relating to survival and adaptation. Recently completed by my wife Betsy[i], the artwork was inspired by our visit to the Acoma Pueblo a few months ago, which is one of the oldest continuously inhabited communities in North America. Ancestors of current residents have lived on top of a 360-foot tall rock tower since 1150 A.D.

Their previous home was located on an even more formidable tower across the valley similar to the rock mesa in the center of Betsy’s art piece. Legend has it that a bolt of lightening shattered the steep rock steps leading to their old village so the Acoma people moved to the current location.

Other than the occasional battles with other Native American tribes, the Acoma people lived for generations at a time in relative peace until interrupted by major events that would change the course of history. The first major event occurred in the form of a 50-year drought that forced the Ancestral Pueblo peoples from the Chaco Canyon to other locations throughout the Southwestern U.S.

A second history-changing event for the Pueblos began with the arrival of the Spanish around 1540. The relationship between these two very different cultures was peaceful for several decades until a series of mishaps led to the horrific Battle of Acoma Pueblo. After two days of traditional warfare, modern technology in the form of cannon proved decisive for the Spanish in winning the battle. Tragically, the Spanish officer in charge ordered savage retribution followed by many years of slavery, ultimately leading to the bloody Pueblo Revolt eight decades later when tribes joined together and drove the Spanish out of the region.

Taken together, the Acoma Massacre and Pueblo Revolt represent an extreme case of leadership failure that decision makers from all walks of life can learn from. A single horrific decision by one military leader on a single day nearly two centuries before the American Revolution still brings pain and influences decisions throughout the region over four centuries later, and no doubt influenced many a negotiation.

The centuries that followed offered more turmoil for the region under the control of Spain, Mexico, and then finally the United States in 1848, but today the Acoma people are applying modern business methods in making the best of a challenging situation, seizing opportunities, and improving their future while preserving their cultural roots and traditions. The Acoma Pueblo own and operate cultural facilities at ‘old Acoma’ as well as the Sky City Casino Hotel and travel center, which is a significant employer and economic engine on I-40 between Albuquerque and Grants, New Mexico.

In addition to visiting with the friendly people at the old pueblo, who graciously welcomed a diverse mix of international tourists during our Easter weekend tour, we also enjoyed visiting the San Esteban del Rey Mission. A Catholic mission founded in 1629 that required 12 years to complete, the church is 150 feet long with vigas spanning the entire 40-foot width. The timber used for the vigas were harvested in the San Mateo Mountains 30 miles to the north and were transported by the Acoma people by foot. The adobe walls of the church are seven foot thick at the base on one side and five on the other. Adjacent to the church is their historic cemetery made of soil carried manually up steep steps carved out of the sandstone cliffs.

My takeaway

The Acoma people and their story represent a fine lesson for business and community leaders in adapting to radical changes beyond their control, despite extreme culture clashes and harsh environments. Lessons learned from the Acoma Pueblo can no doubt be applied to many around the world (see UNM business case summary).

Among the most important responsibilities each of us face during our brief life is taking charge of our own learning. Only then can we begin to make decisions as independent thinkers free from indoctrination, conflicting interests or agendas of others, which is prerequisite to becoming mature adults and valuable citizens prepared to contribute, particularly in a democracy in the vital role of informed citizens and consumers. This responsibility to others and ourselves never ends in our conscious lives, so we should grasp opportunities to learn and grow at every reasonable opportunity.

Leaders have a greater responsibility to practice continuous learning in order to maintain a high state of awareness in relevant matters; particularly in the type of highly complex, tumultuous and hypercompetitive environments we face today. Those few I consider great leaders then apply wisdom gained from experiential learning to rise above short-termism to contribute more to our world than they extract.

Although much easier to claim sustainability than to achieve, important lessons on stewardship can be learned from other cultures and eras. Our Founding Fathers of the United States for example studied many cultures and governance models before collectively deciding on a specific type of democracy in our constitutional republic.

Visiting the Acoma Pueblo

The old Acoma Pueblo is located about 60 miles west of Albuquerque a few miles south of I-40 on a good paved road. We spent the night at one of several motels in Grants, NM on our visit, which is a pleasant 40-minute drive by car. Visitors must park at the Sky City Cultural Center located at the base of the rock tower, which houses the Haak’u museum, Y’aak’a Café, gift shop and conference rooms, providing an experience similar to a national park. Walking tours are regularly scheduled with a short mini bus ride from the cultural center up to the village, which consists of over 250 family-owned dwellings still without water or electricity, some portion of which are still full-time residents with the remainder used by families during cultural and religious ceremonies.

About the author:

Mark Montgomery is the founder and CEO of Kyield, which has been a pioneer at the confluence of human and machine intelligence for two decades.

[i] Though quite similar to ‘Old’ Acoma Pueblo, it is not a replica. Betsy has a unique style of mortar sculpture over wood with different thicknesses for depth perception and shapes, natural woods, and oil paint.