CEO Radar
What matters for CEO decisions.
International business coverage in English — on strategy, transformation, leadership, management systems, people and risks.
All publications
63 articles- 01
Why major projects fall behind before work begins
McKinsey shows how a capital-project schedule can assume rates of work that the team cannot physically achieve. For CEOs and project owners, this is a question of planning quality, contractor transparency and early action on deviations.
- 02
A new CEO and the founder: how to avoid two centres of power
When a founder remains chair after a new CEO arrives, the formal handover does not always change the informal routes through which decisions are made. For investors and senior leaders, this is a question of authority design, not just personalities.
- 03
Profitable but short of cash: where working capital gets trapped
McKinsey explains why cash flow depends on sales, procurement, inventory and capital-project decisions, not only on the finance department. This is a shared management task for the CEO and CFO.
- 04
How large companies can keep their ability to grow
Fortune’s new Future 120 list and BCG’s methodology suggest that long-term growth depends not only on a product or sector, but on ambition, capital allocation, capable teams and a culture that can renew itself.
- 05
High standards do not require a harsh leadership style
The Fortune column separates accountability for results from performative severity. For CEOs, the distinction is a way to address mistakes without making people afraid to report the next one.
- 06
When 80% of managers started in hourly roles, culture has a path
Danny Meyer’s experience shows how internal moves become part of a management system. The question for CEOs is not how to copy an 80% figure, but how an entry-level job can become a credible route into running a business.
- 07
Creator partnerships become a growth system, not a series of one-off posts
BCG explains why creator partnerships need an owner, enduring relationships and measurement across the customer journey. For CEOs, this is a question about the brand’s operating model, not a count of sponsored posts.
- 08
A threat to relocate works only if the CEO can actually move
A large employer’s bargaining power has limits: it depends on local talent, partners and infrastructure. CEOs must count not only possible government concessions but also the cost of signalling a move.
- 09
A weak job market does not guarantee team loyalty
Even when finding another job is difficult, employees can disengage from their employer. Low turnover is not enough evidence of a healthy culture or an effective retention strategy.
- 10
Remote work can preserve individual output while weakening mutual help
Research discussed by Fortune distinguishes personal KPI performance from the less visible work colleagues do for one another. For a CEO, the issue is team design rather than a simple choice between home and office.
- 11
AI requires rethinking the org chart, not just adding a tool
An unchanged structure can use AI to accelerate existing processes without improving the way work is done. The management value emerges when leadership redesigns roles, decisions and hand-offs.
- 12
CEOs should treat expectations about AI as a strategic signal
Public feedback about hopes, concerns and desired changes can be collected systematically and linked to product and research decisions. An AI strategy should listen beyond the company’s own experts.
- 13
The CEO bubble is an information risk, not just a personality flaw
Special treatment can gradually change what a leader regards as normal. A CEO needs people and routines that make disagreement possible before isolation distorts decisions.
- 14
A leaner organisation does not mean the work disappears
Before removing roles or management layers, CEOs need to know which work will stop, which will be redesigned and which will quietly move to remaining employees.
- 15
Test the strategy before an activist investor does
Investor activism increasingly scrutinises capital allocation, portfolio choices and operating performance. A credible value-creation plan should survive that challenge before it becomes public.
- 16
A divided economic outlook calls for trigger-based plans
When executives are almost evenly split on growth prospects, one confident forecast is a weak basis for major capital and hiring decisions.
- 17
Help teams reframe uncertainty without denying the risk
Leaders cannot remove uncertainty, but they can help teams test assumptions, see options and learn from bounded experiments instead of treating every setback as a permanent verdict.
- 18
Risk reporting should change decisions, not just fill a quarterly pack
A risk report is useful when leaders can see changes in exposure soon enough to act and compare the cost of possible responses.
- 19
Change fails because of how people experience it, not because of the slides
The practical lesson for CEOs is to design transformation as behavioural change, rather than a stream of messages or an implementation plan. This applies to any major change, from ERP implementation to post-merger integration.
- 20
The IPO window is opening selectively, so readiness needs its own system
This article invites CEOs to see a stock-market listing as a test of company maturity rather than a date in the calendar. It is about operating consistently as a public company without failures in reporting, controls or governance.
- 21
AI is reshaping staffing models, while job cuts become a tool for reallocating capital
This article invites CEOs to assess headcount as a portfolio that needs continual adjustment to new priorities, rather than a static cost line. It offers a useful signal for hiring, restructuring and shifting budgets towards AI.
- 22
Agentic AI scales through processes, not the number of agents.
Early adopters of agentic AI are moving from counting bots to rethinking processes and ROI. For CEOs, successful transformation begins with a specific business problem rather than a technology demonstration.
- 23
A structural cost reset is a governance challenge, not a one-off saving
Costs have moved beyond finance into governance and competitiveness. CEOs need to rebuild the system of cost control, data and accountability rather than merely adjust individual budgets.
- 24
Communication rules need to be discussed, not taken for granted
Many intergenerational workplace conflicts arise from unspoken expectations about interaction rather than poor ethics. CEOs need to make communication norms explicit to reduce friction and lost productivity.
- 25
Do not confuse readiness to lead with a vocal desire to be in charge
This article helps CEOs distinguish genuine leadership readiness from ambition alone. It supports more accurate succession decisions and helps avoid overlooking strong but more cautious candidates.
- 26
Manage regulatory risk through prioritisation, rather than trying to cover everything at once.
The ECB explicitly says that a more complex environment requires greater focus, simpler supervision and timely correction of weaknesses. For CEOs, this signals closer scrutiny of governance, operational resilience, business models and regulatory fragmentation across markets.
- 27
Bank modernisation should be a continuous capability, not a one-off project
CEOs need to change not only their portfolio of initiatives but the architecture of modernisation itself: moving from temporary programmes to a permanent operating function. That calls for a different approach to funding, governance and accountability for technical debt.
- 28
To make time for strategy, CEOs must deliberately delegate work and authority
The practical lesson is that senior leaders who take on too much lose focus on strategic decisions and exhaust their teams. Delegation becomes a mechanism for building organisational capacity, rather than simply a leadership style.
- 29
Do not confuse a familiar speaking style with people’s real potential
Managers may mistake a familiar speaking style for stronger social skills. For CEOs, this means checking talent assessment criteria and access to opportunities for bias.
- 30
How CEOs should rethink their relationship with the board
The board can be a partner in the CEO’s strategic thinking as well as an oversight body. The key decision concerns how the relationship is structured, rather than how often meetings take place.
- 31
Bridging the gap between AI investment and business results through enterprise orchestration
This article gives C-suite leaders a strategic view of how to turn disconnected AI initiatives into an integrated system that delivers measurable value, addressing the critical gap between AI investment and actual business performance.
- 32
How organisations maximise AI’s value: governance, accountability and workforce adaptation
This article gives C-suite leaders practical data and insights into how organisations generate measurable business value from AI investment beyond efficiency alone. It highlights governance, financial discipline and workforce adaptation as essential to scaling AI.
- 33
Skills-based volunteering as a strategic tool for leadership and business development
This article offers leaders a new perspective on corporate volunteering, positioning it as a strategic tool for developing leadership, strengthening business resilience and solving complex problems, rather than charity alone.
- 34
The AI operating model: five shifts for leaders
As AI capabilities become widely available, the operating model—and how well it combines technology with human judgement and proprietary data—will distinguish leaders from competitors. This article outlines five key shifts executives should consider.
- 35
Adaptive operating models and leadership in the AI era: from reaction to continuous evolution
Deloitte’s article stresses the need to move from traditional operating models to adaptive systems that let organisations evolve continuously amid rapid AI-driven change. It highlights the critical role of leadership judgement in coordinating people and AI.
- 36
Developing an AI strategy that creates value: from ambition to execution
This article gives CEOs a practical guide to developing and implementing an AI strategy that aligns with financial and organisational goals and delivers measurable value, while avoiding fragmented efforts and risks.
- 37
Financing the AI build-out: the hidden risks of opaque infrastructure funding
This analysis highlights significant financial risks associated with large-scale investment in AI infrastructure, particularly through opaque financing mechanisms. It is relevant to CEOs making capital allocation decisions.
- 38
The AI operating model: five key shifts for leaders
This article gives senior executives a strategic view of how AI fundamentally changes operating models, with concrete directions for adaptation and competitive advantage.
- 39
Strengthening the CEO–board relationship: three key factors
This article offers senior leaders practical guidance on improving their relationship with the board, which is critical to strategic governance and effective decision-making.
- 40
Closing the judgement gap: why AI transformation needs human intelligence, not just data
This article offers senior leaders a critical view of why AI investment may fall short of expectations. It shifts attention from adding more data and models to developing people’s ability to interpret their signals, which is essential to better decisions.
- 41
Board-level AI strategy: closing the gap between ambition and execution
This article examines the gap between board approval of an AI strategy and the understanding and support needed to execute it. It helps CEOs assess readiness, accountability and realistic expectations.
- 42
KPMG creates a group to build AI-led businesses: lessons for corporate innovation
This example offers CEOs practical insight into organising AI innovation and keeping large companies agile and competitive.
- 43
Why AI is contentious: the moral and social challenges for business
The article explores the reasons for public opposition to AI beyond economic and existential concerns. Its focus on data used without consent matters for leaders building ethical, sustainable AI strategies.
- 44
Before looking outside for talent, companies need to see the talent within.
Information about employees’ capabilities becomes a management asset when leaders beyond the current team can use it.
- 45
Who has the right to disagree with AI? An organisational design question.
Employees need clear authority to challenge AI recommendations and accountability for decisions as well as tools.
- 46
AI governance begins with shared responsibility.
Even strong rules will fail if the business sees data as IT’s responsibility alone.
- 47
An operating-model problem, not a shortage of product talent
The article challenges the tendency to blame product failures on talent, arguing that operating models and systemic dysfunction are often the root cause.
- 48
KPMG Global Family Business Report 2026: challenges and transformation amid uncertainty
The report offers strategic insight for family and founder-led businesses navigating economic uncertainty, accelerating technology and leadership transitions, including AI governance and talent management.
- 49
AI governance as a strategic differentiator: control, traceability and accountability
Effective AI governance goes beyond compliance and can distinguish market leaders. The article explains how to approach governance strategically to support sustainable growth and reduce risk.
- 50
The COO’s role in agentic AI transformation
COOs can turn AI ambition into operational results at scale by connecting adoption with business outcomes and coordinating work.
- 51
Leading transformation in the AI era: from ambition to execution
The material explores the leadership capabilities needed for continuous AI-led transformation and the gap between ambition and delivery.
- 52
AI governance as a strategic pillar: from compliance to value creation
KPMG connects AI governance with value creation, risk management and organisational transformation, making it a strategic priority beyond compliance.
- 53
Five AI lessons for CEOs from Asia-Pacific
The article draws on Asia-Pacific companies to offer practical guidance on leadership, business context, model choice and common barriers to AI adoption.
- 54
Why CHROs must play a central role in AI transformation
CHROs need to join AI strategy discussions early to redesign work, define human–AI collaboration and govern a hybrid workforce.
- 55
Four COO priorities for agentic AI transformation
The article sets out leadership priorities for redesigning operating models and organisational structures to create lasting value from agentic AI.
- 56
Workforce policy in the AI era: focus on the value of human work
Brookings offers a nuanced view of AI’s labour-market impact beyond the extremes of mass unemployment or universal augmentation. This matters for talent strategies that reflect changes in expertise and economic opportunity.
- 57
AI governance: closing the trust gap in autonomous systems
EY examines the gap between formal AI governance policies and confidence in operational controls, particularly as agentic AI emerges, and recommends stronger accountability and oversight.
- 58
Sustainable growth starts with customers: deeper relationships, lasting success
The article invites CEOs to treat existing customer relationships as a source of sustainable growth, with practical ways to deepen those relationships and identify new opportunities.
- 59
AI as a driver of growth and sovereignty: strategic challenges for business
The ECB president’s speech provides macroeconomic context for AI investment, productivity and technological sovereignty, helping leaders think about long-term growth and capital allocation.
- 60
The COO in the AI era: reimagining operations
The article explains how AI is changing the COO role and which capabilities and approaches matter for operational transformation.
- 61
A leadership framework for responsible AI in healthcare: lessons across sectors
The article offers a structured approach to responsible AI adoption centred on outcomes, ethics and people, with lessons for trust and effective integration across industries.
- 62
The future of business intelligence: from reactive dashboards to proactive AI and ontologies
The article invites leaders to rethink business intelligence, moving from dashboards to proactive, agent-based systems that use AI and ontologies to anticipate needs and automate decisions.
- 63
AI transformation starts with people: leadership, mindsets and behaviour
Successful AI transformation depends on workforce readiness, changing behaviours and leaders who support continuous learning and responsible use.