Accelerating Growth Using AI - A Look At Complexity And The Metaverse : Blog Series 1/5
When I did my doctoral studies I studied a number of growth disciplines in areas like: complexity science, social network science (relationship and collaboration science), system thinking science, information science, and cognitive science. As a result of this knowledge, I learned how to connect business strategy goals using diverse growth strategies and analyze underlying operating systems that were either enabling relationship strength and growth outcomes or creating negative systemic feedback loops that prevented revenue acceleration.
There is a word in the English language seldom used called quaquaversal which means looking in all directions all at once which represents the field of complexity science and is the reality of the executive mindset that needs to operate in the board room and in today’s fast paced world - what one sees as relevant today may well be obsolete tomorrow.
This blog series will explore each of these discipline areas and connect real life examples of AI approaches that are enabling growth acceleration techniques using these science and social science techniques. This is the first blog in this five part blog series and will focus on complexity science.
This is one knowledge domain that every executive must have as leadership practice priority as it is holistic thinking and is a study of a system. Complexity Science is not a single theory, but a collection of theories and conceptual tools from many diverse disciplines. It is concerned with complex systems and problems that are dynamic, unpredictable and multi-dimensional, consisting of a collection of interconnected relationships and parts. Unlike traditional “cause and effect” or linear thinking, complexity science is characterized by non-linearity. In today’s fast pacing world, to remain competitive and relevant, we have no choice other than to think in all directions at once. The reality is that today our world, organization knowledge and enabling infrastructures, and practices, are living in complex systems and solving our business problems requires holistic systems thinking intelligence versus linear thinking methods and approaches.
With a complexity science perspective is a core leadership competency in a company, there is more likely an appreciation of the complex, dynamic and interconnected relationships occurring within a complex system or problem. Employees will have more curiosity and courage to explore, innovate and discover new possibilities. Dr. Diane Hamilton has one of the top radio shows profiling top CEOs and Leaders that value curiosity and understand the linkages to innovation and complexity sciences.
Let’s consider the realities of AI, where data flows in from many diverse knowledge repositories, inside or outside a company. For AI to be effective, it must have access to all the data relevant patterns to map complex relationships and reduce problems to their smallest parts. Nothing like statistical depth spatial visualizations of what is impacting what.
In many ways in the smarter AI world, leaders have to become data surgeons to get to the lowest common denominator like a cell. When I was a General Manager and senior director at Xerox earlier in my career, we always used the phrase, “ Peel back the onion and look at all the layers in the onion to make an informed business decision as what you see on the outside, is not likely you will see in the inside.”
This type of systemic leadership mental model thinking enables and accelerates more curiosity, more agility (elasticity) in an organizational culture to be able to execute complex business challenges and make more informed decisions to achieve sustainable outcomes.
Remember Einstein once when he once said that the definition of insanity is: ” doing the same thing over and over again and expecting different results.” What he was speaking to was that traditional simplistic or reductionist approaches to problem solving don’t work systemically to solve complex problems.
Complexity science provides an approach that acknowledges and embraces the challenge of complexity and if companies want to seriously grow faster they must learn how to think non-linearly. Let’s look at a few of the complexity science AI software methods that I like to follow and hope these examples are helpful to inspire you to think beyond what you already see.
AI Complexity Science Software Innovations
1.) C3AI - remember this name - Tom Siebel? He is the Chairman and Chief Executive Officer of C3 AI. He was the Chairman and Chief Executive Officer of Siebel Systems, which merged with Oracle Corporation in January 2006. Founded in 1993, Siebel Systems became a leader in application software with more than 8,000 employees in 29 countries, over 4,500 corporate customers, and annual revenue in excess of $2 billion. Tom was the visionary that saw and made CRM before Salesforce knew what it even was.
Well in my view, he is doing it again with his new company C3ai, as he and his leadership team have put the building blocks together to drive AI intelligence across complex value chains using their advanced AI building block solutions.
The C3 AI Suite supports the value chain in any industry with prebuilt, configurable, high-value AI applications for reliability, fraud detection, sensor network health, supply network optimization, energy management, anti-money laundering, and customer engagement. C3AI is looking holistically across all the connecting parts laying infrastructure software foundations to capture all the signals and do the advanced analytics sense making. This is where AI will shine the most as the more data you feed AI models the happier they are and behave.
2.) Meta Platforms - One has to recognize the metaverse trend. "The metaverse is essentially a massive, interconnected network of virtual spaces," states Rabindra Ratan, associate professor of media and information at Michigan State University "In theory, we'll be able to move from one virtual world to another in the metaverse, but we'll be wearing virtual reality goggles or maybe augmented reality." Meta announced on Jan. 24 it's developing a new AI supercomputer, which is a key building block toward bringing the metaverse vision into reality. This is a excellent example of complexity sciences at work to connect all our worldly experiences in a virtual 3D World.
If you look at Meta's (Former Facebook name) social media sites Facebook, WhatsApp, and Instagram draw engagement and place targeted ads for an audience of 2.9 billion monthly active users. Their reach is staggering. The software, virtual reality (VR) equipment, and data centers that Meta engages with the metaverse, along with its massive user base, creates a daunting vision of what’s to come. Just imagine all software purchasing experiences happening in a virtual 3D world. Technologies like virtual reality, a computer-generated simulation of a 3D image or environment, and augmented reality, superimposing a computer-generated image on a user's view of the real world, will play a significant role in bringing the metaverse to life.
As a notation: Meta’s financials in the last 12 months, revenue of $112 billion grew 42% compared with the prior 12-month period. Also, trailing-12-month net income of $40 billion grew by 59% versus the previous 12-month period as slower growth in expenses more than offset the increase in income taxes. Meta’s stock has also risen 13% over the last 12 months.
Which companies are performing the best given their AI investments worth watching for 2022? include:Microsoft Corporation (NASDAQ:MSFT), NVIDIA Corporation (NASDAQ:NVDA), Amazon.com, Inc. (NASDAQ:AMZN), and Meta Platforms, Inc. (NASDAQ:FB), Palantir Technologies Inc. (NYSE:PLTR).
Each of these companies listed above is applying complexity science approaches of consistently aggregating market supply chains and advancing AI deeply into their company’s growth plans. In the case of Meta a new 3D super highway has everyone wondering what is coming our way?
At the same time, we must recognize that digital natives are changing how we work and interacting in our world. A Pew Research study from March 2021 found that 31% of Americans were almost always online, while 79% were online several times a day. There is no question that purchasing patterns have already shifted away from physical to virtual goods based on the time spent on apps and games.
TV shows like: VR.5, Caprica, Black Mirror, Harsh Realms, or Altered Carbon offer us perspectives of what a 3D meta verse experience might look like.
What does all this mean to board directors and C level executives?
- First, ensure you appreciate complexity and challenge linear thinking methods that are not connected to bigger systems thinking models.
- Second, have a clearly defined business operating model against your supply chain operating structures clearly understood.
- Third, identify opportunity areas where an AI infrastructure end to end could be applied. If you cannot afford E2E operating AI foundations, then cherry pick to learn and grow wisely against a larger ecosystem vision.
- Fourth, ensure you are whipping your data management leadership practices into data wrangling shape and validate by external audits that you are on the right path.
- Fifth, look well beyond where you are and start carving off a part of your world into the Metaverse to learn from. As a early user of SecondLife ten years ago, I knew this reality would re-emerge - this time, with the forces in play and changing demographics, B2B worlds will never be the same.
One only needs to look to your own children’s level of enthrallments and attachments to their computers, digital phones and 3D enjoyment(s). It is not a matter of if - its a matter of how fast all of these AI enabling constructs will all come together. And there is no question - this will not be a linear system at work, rather we have a complex system at work and hence why teaching complexity sciences should be a foundation in all academic programs globally.
Too many companies are still operating in functional silos, where collaboration DNA and relationship velocity is not being tapped to accelerate revenue and growth.
The next blog will focus on the importance of the social sciences in particular those AI companies applying social network and relationship theories and methods, beyond what companies like Meta are doing, in advancing B2B business models to see what needs to be seen - or simply stated See More to Grow More!
References:
See Britannica detailed definition of Complexity Science
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