A turning tide is not obvious. Each wave is the same as the one before but flotsam is moving in a new direction. Stories are flotsam on the tide. They show a new direction. Here are stories everyone is now hearing. Names have been changed.
Operations director, Tjerk, sees rapid implementation of AI across his organization. He has an idea that the executive board might benefit. Could AI consolidate and report operational performance, capacity utilization, demand forecasts, inventory levels, contingent staffing needs, supplier performance and risk indices?
He told Thomas, Head of IT, to look into it. How hard could it be? All around the organization, there was daily new evidence of AI adoption at whiplash rates.
Suzanne, Global Supply Chain Performance Manager in London, is approaching retirement. After paying EUR 4000 for professional tax guidance, she got identical advice from an AI.
An excited Marcus in HR brought Tjerk the results of a market-research assignment, given to a job applicant. The candidate had used AI to forecast the strategies of the organization’s major competitors. Tjerk struggled to hide his shock at the revealed insights.
Michaela, executive assistant to the Head of Finance in Paris, is relieved to be no longer responsible for knowledge management processes. Notes and reports now go through unfiltered to everyone in the room – and to some who were not.
Maria is an ambitious junior lawyer in Milan. She had spent most of her time on document review. With AI-automation she now deals only with those flagged as uncertain; and is building a different, and sharper, judgment on risk than her predecessors.
Gasim in the Omani Logistics Centre monitors global freight. Previously he would escalate half of all non-conforming movements. With AI support, he now deals with 90% of exceptions himself.
The CEO was quietly proud of his son, Paul. Formerly a code-writer, Paul is now a solutions architect on five times the salary. His colleagues were laid off when code-writing went to AI. He is hoping to get into Tech Leadership before AI reduces the need for solutions architects.
Tjerk tries to make sense of it all. People adapted – as they always do – but he knows this is different. It reminds him of the film, “Everything, Everywhere, All at Once”. Where is leadership in all of this?
Emergent Complexity
That was when Tjerk resolved it was time for the board to exploit AI. He asked Thomas to launch a control-tower project.
Thomas was in Tjerk’s office and had brought three external consultants with him. Tjerk wondered why Thomas needed support.
After hearing their prepared response, Tjerk stared at Thomas for a moment. Then...
“Let me check”, Tjerk said. “Are we, or are we not, in the second quarter of this century? Because your excuse is straight out of the last one. How is it possible we are still stopped dead by data integrity?”
Tjerk was surprised at his own emotion. The frustration was raw.
Those who recognize this frustration see three problem areas: complexity, information, and leadership.
Complexity
Complexity is emerging at operational level. Staff are constantly finding new opportunities for AI in both their working and private lives. It is catalyzing spontaneous, bottom-up change and giving staff agency to initiate it. This drives heterogeneity. Intelligence is moving away from the centre and towards the edge of the organization. Line-managers from a culture built on standardization and control are challenged.
Information
Information leakage has a new form, and not just via transcription and chat-log apps. Companies now radiate data just by existing. It’s called data-exhaust, reminding us how military aircraft must hide their heat-signal. With the help of AI, a company’s operational and strategic intentions can be inferred by third parties from its data signals. Where are these coming from? Should they be controlled? What are competitors, analysts, investors, suppliers, customers and activists able to learn from them?
Leadership
Productivity-driven strategies to grow earnings and stock price have been the focus of leadership. The complication facing executives today is whether doing the same things more efficiently is enough. New competition, alternative solutions and changing requirements have always been a risk but AI has shrunk the time from first awareness to critical action needed.
One question stands above the others:
How does the board learn to look outward — before it is too late to matter?
The Tide Turning
Although hard to see at the time, the formative years of today’s business leaders were a period of relative stability in business, geopolitics and society. Success was achieved through productivity-driven gains – faster, cheaper, better. Three decades have passed since publication of “The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail” by Clayton Christensen. The predominant management trend since then has been ‘digitization of the status quo’. This is shown by a remarkable conclusion in a Sandler report by the Ruby Group “What CEOs actually want” (December 2025).
B2B CEOs entering 2026 are focused on:
Predictable revenue generation
Scalable systems and repeatable processes
Sales performance and pipeline execution
Leadership development and talent readiness
Measurable business outcomes and ROI
These are no more than internal productivity metrics. They live in scientific management and balanced score cards. They are the domain of supervisors and managers. Not leaders. The CEOs who prioritize them are indistinguishable from general managers.
Executives with this internal productivity mindset see the emergent complexity from AI as a threat or ‘governance stress test’ to the administrative order to which their careers have been committed. They turn to internal guardrails, ‘plumbing’ and workflow-policing rather than scanning the horizon for threats and opportunities.
Three things make the old arrangement untenable. Before arguing that boards have to change however, it is necessary to explain why the former modus operandi was right for its time. In a stable environment, it is expensive to commit resources to scanning the horizon, and even more so to maintaining a capability to respond to threats and opportunities that are not only infrequent, they are slow-moving. The organization is able to handle them with existing resources whose primary role is optimizing and controlling present operations. It does not matter that external awareness gets a lower priority. After all, scanning of the external environment is genuinely difficult. What does it even look like? How do you measure it? How do you know when it has worked? Its outputs are qualitative, probabilistic and often unwelcome. It is much easier to fund and justify a control tower than a function whose product is “we think something might happen“. Effort devoted to such ethereal activity is not only hard to justify, it may distract the organization from essential operational improvement and cause it to fall behind its peers. External scanning and evaluation was de-prioritized for understandable reasons. Most organizations took this path and do not have it today. That can be absolutely the right thing to do – maintain an inward, productivity focus – in a stable environment.
The environment is however no longer stable. This is not a temporary condition. Complexity and intelligence is emerging at the edges of the organization. Experience in optimizing complicated systems is inadequate for dealing with complexity. The formerly predictable ‘five forces’1 (supplier power, competitive rivalry, substitution threat, buyer power, new entrants) are now AI-turbocharged. The acceleration of AI-driven change means that the gap between a threat first being visible and becoming critical is shrinking. Reactive response, which worked when threats moved slowly, is no longer adequate.
The external overview of your own organization is now available to everyone. A potential acquirer, an activist investor, an aggressive competitor can now generate a sophisticated, strategic picture of your organization in hours. Without external vision, your organization is not just impaired — it is so in an environment where others have night-vision goggles and first-person-view drones.
Described formally in ‘The Brain of the Firm’ by Stafford Beer2 in 1972, external overview capability, System 4 in Beer’s Viable Systems Model, was never easily acquired. Continuous environmental scanning needs analytical capacity, pattern recognition across disparate domains, and synthesis of weak signals into coherent models. That was a long way off in 1972 but, despite the difficulties, many organizations before 2000 had corporate planning departments responsible for long-range vision and scenario planning. Post 2000, McKinsey’s ‘Corporate Horizon Index’ reports a compression of time horizons as companies replaced human insight with risk and stress-testing metrics on current operations.
AI makes the external overview easier to create. The reason it was hard — continuous environmental scanning requires enormous analytical, inference and predictive capability— is why AI is good at it. The capability that Beer described as necessary, but left organizations to struggle with, is technically accessible for the first time.
The capability cannot be purchased as a product or implemented as a project. It is not a reporting tool. It is an organizational capability — a way of thinking, asking questions, and acting on uncertain and incomplete information about the future. AI makes it feasible, but only if the organization understands what it is and resists the temptation to treat it as a technology project. It requires people who are oriented outward, who are protected from the distraction of current operations, and who have the authority to bring unwelcome findings to the board.
AI supports that capability. It does not replace it. Organizations that commission an AI to do their environmental scanning – and believe the output – will get it wrong.
Stories in corridors, cafeterias and conferences tell us the tide has turned, that the flow has changed. Who is watching the flow; who is interpreting it — and do they have the standing to tell the board what they see?
1Porter’s Five Forces - https://en.wikipedia.org/wiki/Porter%27s_five_forces_analysis
2Anthony Stafford Beer - https://en.wikipedia.org/wiki/Stafford_Beer