1) Enterprise History
GLOBAL ENTERPRISE GROWTH
Over the past 250 years, enterprises have grown from small groups to literally millions of people. And since people have a wide range of intelligence attributes, company owners, executives, managers, and employees bring a wide range of intelligence to every step of a business process. Yet, the bigger the companies grew, in particular those with complex products, services, and operational requirements, the harder it was to manage those organizations. Many organizations have reached a point where scalability is no longer meaningful and is extremely hard to manage. The economics of many global enterprises are driven largely by value maintenance and very little by profitability, even with no perspective on progress. They are in survival mode until they die, without knowing when.
ENTERPRISE INFORMATION TECHNOLOGY
For more than five decades, enterprise software has been built around predefined business processes. While these systems successfully automated repetitive work, they assumed that the optimal sequence of activities could be designed in advance. Whenever markets changed, customers behaved differently, supply chains were disrupted, or priorities shifted, people—not software—had to adapt. Just the cost for updates has grown into the millions. Let alone purchasing or licensing the software and fees for service contracts.
Yet THE BIGGEST PROBLEM could not be eliminated: Software-based solutions are dumb. No intelligence whatsoever. If I made a spelling mistake by adding a company name that was already in the database, a second account was created without warning. And that is only the most trivial problem. Without noticing, we all agreed:
People type in data that is stored in a database, and others or the user themselves can retrieve it in different ways.
Thats all
No matter how many agents and tools you glue onto such a system, it will not become intelligent. Even worse. Almost all early agents are written in Python. So they are created with code as their own backbone. Only when intelligence is needed do they call an LLM.
So now we have two code layers, one on top of the other, and an orchestrator is needed to make it all work – just to be able to say “AI”.
Today’s AI enterprises –> Lipstick on a pig.
2) The Cognitive Enterprise
THE AI PARADOX
Today, with rapid advances in artificial intelligence, systems have become so powerful that we have experienced a phenomenon known as part of the AI Paradox: “the more we use AI, the more people we need.” But in this case, the AI contributes a large amount of intelligence that humans can’t provide, and at the same time, such an artificial intelligence level requires humans to operate in dimensions that were previously unimaginable.
THE COGNITION OF AN ENTERPRISE
Of course, an ENTERPRISE is just a legal entity, an abstract concept of the human brain. Not a real thing, just a virtual entity represented by a group of people – also known as a COMPANY. Now this is changing because that very structure is changing. It’s no longer only people who intelligently perform tasks like creating a product, shaping models, creating ways to market those products, selling and delivering them, servicing those products, and more. Now there are other forms of intelligent existence: The AI.Like our Intelligence is not a thing but a construct that our neurons in the brain brought forward, the intelligence of the AI is not a thing but constructs the AI’s model are bringing forward. Now join both to one.
The cognition of Human and Artificial intelligence unfolds a new level of intelligence that constitutes The Cognitive Enterprise.
Similar to the current Enterprise, just an abstract legal entity, is the Cognitive, just an abstract intelligent entity. But the switch from a one-dimensional legal record to a multi-dimensional intelligent entity is mind-bending.
THE COGNITIVE ENTERPRISE
At BlueCallom, we created the first Native AI Enterprise Platform, the first Enterprise Workflow Intelligence architecture, and the first PROacting AI design that makes workflows no longer a data-in, data-out relationship between AI and humans but a proactive one, where AI can also trigger users based on ideas and findings.
It’s the world’s first Cognitive Enterprise Technology, turning the idea and concept into a real product that companies can build on.
Native AI Solutions, Native AI Design, Native AI Framework, and Native AI Tech are available through a “Common Creative” License. We don’t want to uphold progress through patents. Together we are developing with an innovative mindset, and as such, we get farther than any of us alone.
3) Cognitive Enterprise Benefits
ACCELERATING WORKFLOWS
Probably the biggest advantage is Workflow Acceleration. By using intelligent, adaptive, and situation-responsive workflows, friction can be significantly reduced, user guidance can be enhanced, and situational awareness can be amplified. The result is faster response times, shorter go-to-market cycles, more accurate and more intense marketing, faster delivery, faster service, and, altogether, a hard-to-compete-with competitive advantage.
DOUBLING PRODUCTIVITY
When the Cognitive Enterprise has reached its full potential, it is twice as productive as a competitor with the same number of people, skills, and intelligence level.
REDUCED HUMAN DEPENDENCY
The Cognitive enterprise is less dependent on individuals because the Workflow Intelligence can help new employees t step in almost immediately. Illness, vacation, accidents, maternity leave, or leaving the company is far less dramatic. It is certainly a cut but doesn’t risk the operation.
IT COST REDUCTION
Cognitive Enterprises are built on “Agentic IT” not software. That reduces technology, development, customization, and service costs by roughly 50%.