Part 62 - How do we build the knowledge business of the future?

Magne Bjella

16 hours ago

10 min read

The knowledge business of the future is built when people, expertise, customer insights and artificial intelligence are connected to learn and create value.

We have come a long way.

Through this AI series, we have attempted to understand artificial intelligence from many different perspectives.

How the technology works.

How it finds and processes information.

How websites are understood.

Why structure, context and academic content matter.

How knowledge is organized.

How AI affects search.

How the online store can evolve from a product catalog to

universe of knowledge.

How the customer gets new tools.

How work tasks can change.

And why human judgment, professional competence and responsibility are still crucial.

Now we are left with the last question:

How do we build the knowledge business of the future?

This could have been the longest article in the entire series.

But maybe the answer doesn't really need to be that complicated.

The knowledge business of the future is not built by collecting the most

possible technology.

It is built by connecting what the business already consists of:

people, knowledge, customers, technology, experience and learning.

Artificial intelligence can make the connections between these stronger.

But technology is still a tool.

It is what people and businesses do with it that determines whether

it creates value.

Magne and the AI Buddy sit together at a table surrounded by books, notes and a laptop while discussing artificial intelligence, knowledge and learning. Around them, connections between human thinking and technology are visualized through symbols for knowledge, ideas, analysis, search, networks and artificial intelligence. The watercolor illustrates the professional dialogue that runs through the AI series, where Magne asks questions and explores the possibilities while the AI Buddy contributes with explanations, perspectives and knowledge. The motif also shows the series' basic idea: Artificial intelligence is a powerful tool for finding, structuring, analysing and developing knowledge, but the value arises in the interaction between the technology and people who ask questions, evaluate the answers, learn and use the knowledge further.

A knowledge business is more than a business that has a lot of information

Knowledge only creates value when people can find it, understand it, use it and develop it further.

Most businesses have enormous amounts of information.

Documents.

Emails.

Product data.

Reports.

Presentations.

Routines.

Customer history.

Project files.

Analyze.

But large amounts of information do not automatically make the business

to a knowledge business.

What matters is what the business can do with it.

the knowledge .

Can employees find what the business already knows?

Can experiences from one project be used in the next?

Can customer questions lead to better products and services?

Can professional knowledge be shared between people?

Can mistakes lead to learning?

Can new knowledge challenge old ways of working?

And can AI help businesses do this faster and better?

Then we start to approach something important.

Knowledge management in the AI age is about making the organization's entire knowledge accessible and usable.

Structured and quality-assured knowledge provides both humans and artificial intelligence with a better foundation

Throughout the series we have talked a lot about structure.

It may sound technical.

But it's actually about something very human:

To make it easier to understand.

When the business knows:

what information is available,

where it is found,

who is responsible for it,

which source is authoritative,

how knowledge is interconnected,

and when it needs to be updated,

knowledge becomes easier to use.

This applies to the employee.

It applies to the customer.

And that applies to the AI systems the business uses.

AI can help find, compile and make knowledge available.

But a good answer needs a good knowledge base.

Messy knowledge does not necessarily become wiser by getting an AI interface.

Organizational learning becomes more important as artificial intelligence accelerates the pace of change

The competitive advantage of the future may lie in how quickly the business learns and translates the learning into better practice.

A knowledge business doesn't just store what it already knows.

It teaches.

The customer asks a question that the business cannot answer.

The business has then discovered a knowledge gap.

An employee finds a better way of working.

Then new knowledge has emerged.

An AI system gives a bad answer.

Then the business has learned something about the knowledge base or

the work process.

A project fails.

Then there are experiences that can make the next project better.

This is how the business can develop a continuous circle:

experience → reflection → knowledge → action → new experience.

"The ability to learn faster than your competitors may be the only sustainable competitive advantage." — Arie de Geus

In an era where technology is rapidly evolving, a business's ability to learn can become at least as important as the technology it purchases.

Magne and the AI Buddy walk through Chinatown in San Francisco and converse as they pass the characteristic entrance gate, Chinese lanterns, shops, restaurants and people in the vibrant urban environment. The watercolor uses the journey through Chinatown as a framework for the AI series' exploration of artificial intelligence, knowledge and learning. The motif symbolizes how understanding is developed through context, language, culture, experiences and connections, and how information gains greater value when seen in a larger whole. Magne and the AI Buddy represent the exploratory dialogue between humans and artificial intelligence, where questions, curiosity, source criticism and reflection are used to move from information to understanding and further to knowledge.

The knowledge business of the future combines explicit knowledge with people's tacit knowledge

Experience, professional judgment and practical expertise are part of the company's invisible capital.

Not all knowledge is found in the documents.

Some of the most important knowledge is found in humans.

With the employee who knows the customer.

The professional who has seen the same problem a hundred times.

The leader who understands why a previous solution failed.

The customer service representative who knows which questions reveal the customer's

real needs.

The technician who hears the sound that something is wrong before the measuring instrument shows it.

This is tacit knowledge .

Something can be documented.

Something can be shared.

AI can help structure something.

But much is developed through experience, collaboration and practice.

The knowledge industry of the future must therefore do two things simultaneously:

make more knowledge available – and continue to develop

the people who create new knowledge.

Artificial intelligence becomes part of the business's knowledge infrastructure

AI creates the greatest value when the technology is connected to good data, expert knowledge, work processes and human quality assurance.

Throughout the KI series, Kompisen has written.

Analyzed.

Explained.

Compared.

Structured.

Suggested.

And occasionally corrected by Magne.

The latter is important.

Heh heh.

Because the AI of the future does not necessarily need to stand alone and deliver

the answer.

It can be part of a larger knowledge infrastructure .

The employee asks the question.

AI finds relevant knowledge.

The systems deliver data.

The professional assesses the result.

Experience adds context.

The human makes the decision where human responsibility is necessary.

New experience is fed back into the knowledge base.

Then we don't get:

human or machine.

We get:

human + knowledge + technology + learning.

Customer insights connect the knowledge business to the world outside the organization

Businesses must learn with customers – not just about them

It is easy to build a universe of knowledge that turns inward.

The business documents what it knows.

But value creation does not happen because the business knows a lot.

It happens when knowledge is used to solve real needs.

Therefore, the customer must be part of the learning system.

What are customers asking about?

What don't they understand?

Where does friction occur?

What are they missing?

Why do they choose the competitor?

What happens after the purchase?

What does customer service say?

What works surprisingly well?

Customer insight is therefore not just input to marketing.

It is input to the company's learning .

"There is only one valid definition of business purpose: to create a customer." —Peter F. Drucker

For private businesses, the connection between knowledge and the customer is absolutely fundamental.

In other parts of society, we use other terms – the citizen, the patient, the student or the audience – but the principle of understanding the people for whom the business or service exists remains.

Magne and the AI-Friend walk through the university environment in Oxford with books in their hands and conversations in front of the characteristic Radcliffe Camera and historic university buildings. The watercolor uses Oxford as a symbol of knowledge, research, learning and academic tradition in the AI series' exploration of how humans and AI can develop knowledge together. Magne and the AI-Friend represent the ongoing dialogue between human curiosity and new technology, where questions, expertise, critical thinking, sources and reflection are crucial to move from available information to real understanding. The motif emphasizes that artificial intelligence can make enormous amounts of knowledge more easily accessible, but that the human ability to ask good questions, evaluate answers, understand connections and use knowledge with judgment is still crucial.

Innovation occurs when existing knowledge is combined in new ways

AI can increase idea capacity, but humans must understand which problems are worth solving

A knowledge business should not only make today's work more efficient.

It must also be able to create tomorrow's solutions.

This is where knowledge and innovation meet.

A customer expresses a problem.

An employee sees a pattern.

A technology opens up a new opportunity.

A professional connects knowledge from two areas that were previously separate

separated.

And suddenly an idea arises.

AI can help explore alternatives and combine information.

But innovation requires more than generation.

Someone must see the opportunity.

Someone must understand the need.

Someone has to challenge the assumptions.

Someone has to experiment.

And someone actually has to implement it.

"Innovation is the specific instrument of entrepreneurship." —Peter F. Drucker

The knowledge business of the future therefore does not just need more information.

It needs a culture where knowledge can be challenged, combined and translated into action .

Psychological safety and knowledge sharing become more important when the business needs to learn quickly

Employees must be able to ask questions, share mistakes, and challenge established truths

There is an organizational prerequisite that AI cannot install.

Trust between people.

If employees are afraid to ask questions, knowledge remains hidden.

If mistakes are hidden, learning opportunities disappear.

If employees protect their knowledge to protect their own position, the business becomes less intelligent as a whole.

If no one dares to challenge management, bad decisions can continue even if the organization has access to the world's best analytical tools.

A knowledge business therefore needs psychological security .

"Psychological safety is a belief that one will not be punished or humiliated for speaking up with ideas, questions, concerns, or mistakes." — Amy C. Edmondson

Knowledge must not just exist.

It must be able to move between people.

Knowledge management is about creating direction, learning and responsibility.

AI strategy cannot be separated from competence strategy, organizational development and the business's purpose

It is tempting to make AI the responsibility of the IT department.

But when technology affects:

work processes,

competence,

customers,

products,

communication,

decisions,

innovation,

and organization,

AI becomes a management issue.

Management must not be able to program the language model.

But it must be able to ask the questions:

Where can AI create real value?
What knowledge do we need?
What skills do employees need?
What should never be automated indiscriminately?
How do we ensure quality?
Who is responsible?
How do we use the winnings?
What should the business improve on?

The last question is perhaps the most important.

Because technology is not the strategy.

The technology should help the business implement the strategy.

The learning knowledge business connects people, customers, data, technology and experience in a continuous loop

Value creation occurs when knowledge moves through the organization and leads to better actions.

We can therefore draw the knowledge business of the future quite simply:

People create experience.

Experience creates knowledge.

Knowledge is structured and shared.

Data provides new signals.

Customers ask new questions.

AI helps us find and process knowledge.

People evaluate and apply it.

Actions create new experiences.

And the business learns again.

It is not a linear production line.

It's a learning cycle .

And the better this circuit works, the greater the value of

both human and artificial intelligence become.

Magne and the AI-Friend walk through a historic street in Florence with the monumental Cathedral of Santa Maria del Fiore and Brunelleschi's famous dome in the background. Surrounded by small shops, trattorias, bicycles and people, they chat as they continue the AI-Series' journey of knowledge through European cities. The watercolor uses Florence – a historic center for art, science, architecture, commerce and human creativity – as a setting for the exploration of artificial intelligence, innovation and knowledge development. The motif symbolizes how new technology builds on knowledge humans have developed over generations, and how curiosity, creativity, expertise and the ability to combine ideas are still central as artificial intelligence opens up new possibilities. Magne and the AI-Friend represent the dialogue between humans and technology and the continuous journey from questions and information to understanding, learning and new knowledge.

Magne's perspective – we started with the technology and ended with the people

After the entire AI journey, one principle remains: technology is a tool for human value creation.

When this series started, the questions were about AI.

What is artificial intelligence?

How does it learn?

How does it generate answers?

How does it understand language?

How does it find information?

Gradually, the questions began to change.

How do we organize knowledge?

How do we create good content?

How do we help the customer?

How does the business use AI?

What is happening with working life?

And now:

How do we build the business?

It's perhaps the most interesting thing that has happened throughout the entire series.

The more we've talked about artificial intelligence, the more we've ended up talking about humans .

My friend's perspective – artificial intelligence has no value until humans use it for something of value .

Future AI should be assessed by what it helps people and businesses achieve

The buddy can process enormous amounts of information.

But the information must mean something.

My friend can type quickly.

But the text must have a purpose.

The friend can analyze customer data.

But the business must care about the customer.

The friend can find knowledge.

But someone must have created it.

Your friend can suggest a solution.

But someone has to take responsibility for it.

The buddy can help people work faster.

But people must decide what to use the freed up time for .

Thus, building the most AI-driven business may not be the most important goal.

It will be about building the best business we can – with AI as one of the tools.

Magne and the AI-Friend stand outside the Old Parsonage Hotel in Oxford and converse in the historic university setting, surrounded by the hotel's characteristic stone architecture, green climbing plants, garden and entrance sign. The watercolor uses Oxford as a setting for the AI-series' exploration of artificial intelligence, knowledge and how information can be organized and connected to larger academic contexts. Magne and the AI-Friend represent the ongoing dialogue between human curiosity and artificial intelligence, where questions lead to new questions and individual articles, technical concepts and topics can gradually be linked to a larger universe of knowledge. The motif emphasizes that technology can help us find and process information, but that humans still need to create structure, understand connections, assess quality and develop knowledge further.

Technical terms for the future of knowledge-based business, organizational learning and artificial intelligence

The concepts that connect people, knowledge, technology and value creation

Knowledge-based Organization - An organization where knowledge and expertise are central resources for problem solving, development and value creation.
Knowledge Management - Systematic work to develop, document, organize, share and apply knowledge.
Organizational Learning - Processes where experience is transformed into knowledge that influences how the organization acts.
Learning Organization - An organization that systematically develops the ability to learn, adapt and improve.
Tacit Knowledge - Experience-based knowledge that is often found in people without being fully documented.
Explicit Knowledge - Knowledge that is formulated and documented so that it can be more easily shared.
Knowledge Sharing - The process by which knowledge is transferred and developed between people and parts of the organization.
Knowledge Infrastructure - Systems, processes, structures and practices that make knowledge accessible and usable.
Absorptive Capacity - The ability of the business to identify, understand, absorb and apply new knowledge from outside.
Psychological Safety - An environment where people feel they can ask questions, share ideas, and point out mistakes without undue social risk.
AI Augmentation - Using artificial intelligence to augment human capacity rather than simply replacing tasks.
Collective Intelligence - Knowledge and problem solving that arise through interaction between multiple people – and increasingly between people and digital systems.

We have come to the end of the KI series

After 62 articles on artificial intelligence, human knowledge, learning and value creation remain the most important common thread

Magne and Kompisen have traveled far.

We've been sitting in a pub in Oxford.

Wandered through the university streets.

Been to San Francisco.

Italy

London

Paris.

Oslo.

We have stood in front of more boards than any of us dare to count.

Heh heh.

But the locations and watercolors have only been the framework for something much larger.

A journey through artificial intelligence.

And now we won't end with:

We have only just begun.

Because that would be wrong.

We have actually come a long way.

We have learned that AI can be incredibly powerful.

We have also learned that it can be wrong.

We have seen that structure matters.

That sources matter.

That context matters.

That customer insight matters.

That professional knowledge matters.

That critical thinking matters.

That trust matters.

That people matter.

And perhaps most importantly:

We have learned that artificial intelligence does not make human knowledge less important.

It can make our ability to develop, share, assess and use knowledge even more important .

The last board only needs one sentence

The knowledge business of the future is not built by humans or artificial intelligence – it is built by people who learn to use knowledge and technology together.

Throughout the series, we have asked what AI can do.

Maybe we should end with another question.

What can we do better because we have AI?

If the answer is:

learn more,

understand better,

share more knowledge,

make better decisions,

create better services,

help customers better,

unleash human capacity,

develop new ideas,

and create more value for people and society,

then the technology has gained a purpose.

Not as a substitute for human knowledge.

But as an amplifier of it.

And that's exactly where the two main characters we've actually written meet.

throughout this series:

the artificial intelligence – and the human one.

One may become increasingly powerful.

But it is still up to us to decide what to use it for .

Magne and the AI-Friend stand on the Golden Gate Bridge in San Francisco, smiling and waving goodbye to the readers at the end of the long AI series about artificial intelligence, knowledge, people, digitalization and value creation. The Golden Gate Bridge's characteristic red towers and cables frame the subject, while San Francisco, the bay and sailboats lie in the background. The watercolor marks the end of Magne and the Friend's professional journey through artificial intelligence and at the same time the beginning of what comes next. The closing message is that artificial intelligence can do increasingly more, but that human knowledge, judgment, creativity, relationships and responsibility are still crucial. AI should be used as a tool to develop people, businesses and knowledge and contribute to value creation. Magne and the AI-Friend thank the readers for following along and remind them of the most important perspective of the series: The future is not created by artificial intelligence alone, but by what people choose to do with technology.

Thanks for the trip.

Magne & the Friend

Academic background and further reading

This series also builds on my own professional journey through the Web Design study , the eMarketing study , Innovation and Commercialization and professional seminars in San Francisco and Oxford . Here you will find the background, professional environments and experiences that have followed the development from the early years of the web to today's digitalization.

⟶ Recommended literature

Portico Publish - Portico Publish is a small, independent publishing and dissemination project built around reflection, knowledge, culture and the people behind value creation.