Artificial intelligence promises more efficient organisations. But efficiency is not the same as intelligence, and intelligence is not necessarily the same as humanity.
The Organisation Was Always a Human Invention
We tend to describe artificial intelligence as a technological revolution.
We discuss increasingly powerful models, autonomous agents, automation, computational capacity and the extraordinary speed at which machines are learning to perform activities previously associated with human intelligence.
Yet perhaps we are overlooking a more important question.
What happens to human relationships when the organisations in which we live and work begin to delegate part of their intelligence to machines?
An organisation is not simply a structure designed to produce goods, deliver services or generate economic value.
It is also a social environment.
People enter organisations carrying experience, expectations, ambitions, fears and personal histories. They develop relationships, negotiate responsibilities, build trust, disagree, cooperate and sometimes compete.
Over time, they create something that cannot easily be represented in an organisational chart: a shared understanding of how things work.
Much of this knowledge is never formally documented.
It exists in conversations, professional judgement, informal networks and the ability to recognise situations that have occurred before.
It also exists in the simple act of asking a colleague for advice.
Artificial intelligence is beginning to enter precisely this human environment.
And its consequences may be considerably more profound than the automation of individual tasks.
We Have Spent Decades Making Organisations More Efficient
For much of the twentieth century, organisational progress was associated with efficiency.
Scientific management attempted to optimise work. Industrial automation increased production capacity. Information systems standardised processes. Enterprise software connected departments. Digital transformation promised greater integration, transparency and responsiveness.
Each technological wave introduced new possibilities.
But each also changed the relationship between individuals and the organisations employing them.
Standardisation reduced some forms of individual autonomy while making complex activities more predictable.
Digital systems made information more accessible but also introduced new mechanisms of monitoring and control.
Remote collaboration expanded flexibility while sometimes weakening informal social relationships.
Artificial intelligence represents another step in this evolution, but with an important difference.
Previous technologies primarily automated physical activities, transactions or predefined procedures.
AI can increasingly participate in activities involving language, interpretation, analysis, recommendation and decision support.
In other words, it enters areas traditionally associated with professional judgement.
The question is no longer simply whether a machine can perform a task faster than a person.
It is whether the organisation still needs people to understand why that task matters.
The Invisible Social Value of Work
Imagine two colleagues discussing a difficult problem.
One has more experience. The other brings a different perspective.
Neither has a complete answer.
Through conversation, they gradually identify a solution.
From a purely operational perspective, this interaction might appear inefficient.
Two people have spent thirty minutes discussing something that an AI assistant could perhaps analyse in seconds.
But what actually happened during those thirty minutes?
Knowledge was transferred.
Trust was reinforced.
Professional experience became accessible to someone else.
A relationship developed.
And both individuals may have learned something that will influence future decisions.
Now imagine replacing that interaction with an AI assistant.
The answer might arrive faster. It might even be more accurate.
But the social process has disappeared.
The younger colleague has not necessarily developed a relationship with the more experienced one. The organisation has not necessarily strengthened its internal network of knowledge. The shared experience has not occurred.
This does not mean that AI should be excluded from professional activities.
It means that the value of human interaction cannot always be measured by the time required to produce an answer.
An organisation can become more productive while simultaneously becoming socially weaker.
And this possibility deserves far more attention than it currently receives.
When Knowledge Becomes a Service Instead of a Relationship
For centuries, knowledge has been transmitted through human relationships.
Families, schools, universities, professional communities and workplaces have all played a role in connecting generations of experience.
The transmission of knowledge was rarely perfect.
It depended on access, social structures, individual generosity and sometimes privilege.
Artificial intelligence offers an extraordinary opportunity to democratise access to information and expertise.
A young professional can now consult systems capable of explaining complex subjects, reviewing arguments and suggesting approaches that would previously have required considerable experience or access to specialised experts.
This is a genuine advance.
But there is a subtle distinction between accessing knowledge and becoming knowledgeable.
Knowledge is not simply a collection of correct answers.
It also involves the ability to recognise uncertainty, understand context, evaluate consequences and accept responsibility.
These capabilities develop through experience, including mistakes, disagreements and interactions with other people.
If organisations increasingly replace these learning processes with immediate AI-generated answers, they may inadvertently weaken the very capabilities they expect their future professionals to possess.
We could find ourselves creating organisations with unprecedented access to knowledge but progressively fewer opportunities for individuals to develop independent judgement.
The paradox would be extraordinary: organisations that know more while their people understand less.
The New Geography of Organisational Power
Technology has always influenced the distribution of power.
Those who controlled industrial machinery influenced production.
Those who controlled information systems influenced access to data.
Those who designed enterprise processes influenced how decisions were implemented.
Artificial intelligence introduces another dimension.
Who controls the systems that increasingly influence organisational reasoning?
Who decides which information an AI assistant can access?
Who defines the criteria used to recommend one course of action over another?
Who determines when a human decision should be challenged, supported or replaced by an automated recommendation?
These are not exclusively technical questions.
They concern authority, autonomy and accountability.
Consider an organisation in which employees increasingly rely on AI assistants to prepare reports, evaluate proposals and formulate recommendations.
At first, the technology appears to distribute expertise more widely.
But if the underlying systems, data and decision criteria are controlled by a small group, the organisation may actually become more centralised.
The appearance of distributed intelligence could conceal a concentration of decision-making power.
This is particularly important because algorithmic recommendations often arrive with an impression of neutrality.
A recommendation presented through a polished interface can appear objective even when it reflects assumptions, incomplete information or organisational priorities established elsewhere.
The challenge is not simply to make AI systems explainable.
It is to ensure that people retain the authority, competence and freedom to question them.
The Risk of Organisations Without Memory
An organisation possesses more than information.
It possesses memory.
That memory includes past decisions, unsuccessful experiments, relationships, conflicts, compromises and the reasons certain choices were made.
Some of it exists in documents and databases.
Much of it exists in people.
When experienced professionals leave an organisation, part of this memory can disappear with them.
Artificial intelligence offers an opportunity to preserve and reconnect knowledge that would otherwise be fragmented or lost.
But capturing information is not equivalent to preserving organisational understanding.
A document may record what was decided without explaining the uncertainty surrounding the decision.
A database may preserve the final outcome without capturing the disagreements that preceded it.
An AI system may reconstruct a convincing explanation of a historical decision without knowing whether that explanation reflects what the people involved actually understood at the time.
This distinction matters.
An intelligent organisation should not merely remember its answers.
It should remember its questions, doubts and mistakes.
Otherwise, artificial intelligence risks transforming organisational memory into a collection of apparently coherent narratives stripped of the human uncertainty that made the original decisions meaningful.
Are We Creating More Intelligent Organisations or More Isolated Individuals?
There is another possible consequence of AI adoption that receives relatively little attention.
The gradual disappearance of ordinary human interactions.
Think about how many professional relationships begin with a simple request.
Could you explain this?
Have you encountered this problem before?
What do you think about this proposal?
Can we discuss an idea?
These conversations do more than exchange information.
They create opportunities for cooperation.
They allow people to recognise one another’s expertise.
They help newcomers become part of a community.
They generate the informal connections through which organisations develop cohesion.
Now imagine that an AI assistant becomes the preferred destination for almost every question.
The assistant is always available.
It never appears impatient.
It does not judge the question.
It can provide an immediate and often useful response.
From an individual perspective, this is enormously attractive.
But what happens collectively?
People may become more autonomous in performing tasks while becoming less connected to one another.
Teams may exchange fewer ideas because individuals can independently generate plausible solutions.
Experienced professionals may have fewer opportunities to mentor younger colleagues.
Informal communities of practice may gradually weaken.
None of these outcomes is inevitable.
But neither can we assume that human relationships will remain unaffected simply because the technology is useful.
A workplace in which everyone has an intelligent assistant is not necessarily a workplace in which people are more intelligent together.
The Human Cost of Perfect Efficiency
There is a tendency in contemporary management to treat efficiency as an unquestionable good.
Faster processes, fewer errors, reduced costs and higher productivity are presented as universal indicators of progress.
But efficiency is always efficiency in relation to a particular objective.
A hospital can optimise the number of patients treated without necessarily improving the quality of human care.
A university can automate administrative and educational processes without necessarily improving the intellectual development of its students.
A company can reduce the time spent in meetings without necessarily improving cooperation or creativity.
An organisation can automate customer interactions while making customers feel increasingly distant from the people responsible for serving them.
Artificial intelligence makes these trade-offs more important because it expands the range of activities that can be optimised.
The danger is not that organisations will suddenly become entirely automated.
It is that they may gradually eliminate activities whose social value is difficult to quantify.
Mentoring, informal discussion, professional reflection, empathy and collective learning are not always visible in performance indicators.
Yet they contribute to the long-term resilience of organisations.
An organisation that removes every apparent inefficiency may eventually discover that some of those inefficiencies were the foundations of its human intelligence.
The Social Contract of the Intelligent Organisation
There is a broader social dimension to this transformation.
For generations, employment has represented more than an economic transaction.
Work provides income, but it can also provide identity, social recognition, relationships and a sense of contribution.
Organisations have consequently played an important role in the social structure of modern societies.
Artificial intelligence may alter this relationship.
If machines perform an increasing proportion of economically valuable activities, how will organisations distribute the resulting benefits?
Will productivity gains translate into better working conditions, opportunities for professional development and greater individual autonomy?
Or will they primarily support cost reductions, employment insecurity and a concentration of economic value?
These are not predetermined technological outcomes.
They are organisational and political choices.
Evidence already suggests that governance matters. OECD research on algorithmic management, published in 2025, found that managers recognised improvements in decision-making while also expressing concerns about accountability, transparency and workers’ well-being. The OECD also emphasised the importance of consulting workers when introducing these systems. OECD
The important point is that AI does not arrive in a socially neutral environment.
It enters organisations characterised by existing inequalities, power relationships, professional cultures and different levels of trust.
The same technology can strengthen human autonomy in one organisation and undermine it in another.
What makes the difference is not necessarily the sophistication of the model.
It is the organisational philosophy guiding its adoption.
From Artificial Intelligence to Collective Intelligence
I believe the most interesting opportunity offered by artificial intelligence is not the creation of organisations capable of functioning with progressively fewer people.
It is the possibility of creating organisations in which people can contribute more meaningfully.
Imagine an organisation where AI makes knowledge accessible across departments without eliminating the relationships through which people learn from one another.
Where routine activities are automated, but the time saved is reinvested in professional development, experimentation and cooperation.
Where younger professionals use AI to accelerate learning while continuing to benefit from experienced colleagues.
Where managers use intelligent systems to understand complex situations without surrendering responsibility for their decisions.
Where organisational memory preserves not only information but also the reasoning, uncertainty and context surrounding important choices.
And where technology makes it easier for people with different experiences, cultures and capabilities to collaborate.
This would represent a meaningful evolution.
Not simply from traditional organisations to AI-enabled organisations.
But from fragmented organisational intelligence to a more genuinely collective form of intelligence.
The distinction is fundamental.
Artificial intelligence can increase the capabilities of individuals.
Collective intelligence emerges when those capabilities become connected through relationships, shared understanding and common purposes.
One does not automatically produce the other.
The connection must be deliberately designed.
Intelligence Without Humanity Is Not Progress
Having experienced several generations of technological transformation, from the early Internet to today’s artificial intelligence systems, I have become increasingly convinced that the most significant consequences of technology are rarely limited to the technology itself.
The Internet transformed communication, but its deeper consequences concerned access to knowledge, economic relationships, communities and social behaviour.
Enterprise computing transformed information processing, but its lasting influence extended to organisational structures, management practices and the distribution of authority.
Artificial intelligence is likely to follow a similar trajectory.
We may spend the coming years celebrating systems that reason faster, produce more and automate increasingly sophisticated activities.
But the real measure of progress will lie elsewhere.
Will people become more capable of understanding the world around them?
Will organisations become more open to different perspectives?
Will knowledge become more accessible without weakening independent judgement?
Will professional relationships become richer or progressively more transactional?
Will individuals retain meaningful control over decisions affecting their lives?
And will the economic benefits of artificial intelligence contribute to a more inclusive society?
These questions cannot be answered by benchmarks, model evaluations or computational performance.
They require a discussion about the kind of organisations and society we want to build.
A Final Reflection: The Organisation We Should Fear
Perhaps the organisation we should fear is not the one where artificial intelligence replaces every human being.
That scenario remains largely speculative.
A more immediate and plausible concern is an organisation where people remain physically present but progressively lose their role in creating knowledge, exercising judgement and building relationships.
An organisation where employees execute recommendations they no longer fully understand.
Where collaboration is replaced by individual interactions with intelligent assistants.
Where professional experience loses value because immediate answers appear more convenient than human dialogue.
Where managers confuse algorithmic consistency with wisdom.
And where efficiency becomes the ultimate objective rather than a means of improving human activity.
Such an organisation might be extraordinarily productive.
It might even appear exceptionally intelligent.
But would it still be a good place for human beings?
The future of artificial intelligence should not be measured only by what machines become capable of doing.
It should also be measured by what human beings remain capable of becoming, together.
And perhaps this is the real challenge of organisational intelligence.
Not to build organisations that think instead of people.
But to build organisations in which technology helps people think, learn and live better together.
References and Further Reading
The article is an interpretive essay rather than an empirical study. The following sources provide research context for its discussion of work, autonomy, organisational governance and human relationships.
OECD (2025). Algorithmic Management in the Workplace: New Evidence from an OECD Employer Survey.Research on the effects of algorithmic management, accountability and workplace conditions. OECD publication.
OECD (2023). The Impact of AI on the Workplace: Main Findings from the OECD AI Surveys of Employers and Workers. Evidence concerning AI adoption, working conditions, trust and worker participation. OECD publication.
Shoshana Zuboff (1988). In the Age of the Smart Machine: The Future of Work and Power. A foundational examination of how information technologies transform organisations, work and power.
Richard Sennett (1998). The Corrosion of Character: The Personal Consequences of Work in the New Capitalism.An exploration of how changes in organisational structures affect identity, relationships and social cohesion.
Amy C. Edmondson (2019). The Fearless Organization. Research and practical analysis concerning psychological safety, organisational learning and the conditions supporting productive collaboration.
Francesco Iarlori. The Architecture of Thought: Artificial Intelligence, Organisation and Human Meaning. A broader conceptual perspective on the relationship between artificial intelligence, organisational structures, human judgement and meaning.
