Been recently asked what the perfect profile for an Chief AI officer is. IMO no perfect profile, just depends on the problem you want to solve and the bottlenecks you're facing. A long post made short with an image (yes IA is great when you have ideas and absolutely zero design skills).

Weekly wrap-up #5 : Economic scrutiny, organizational transformation and workforce adaptation redefine AI’s next phase as sustainable execution overtakes technological performance as the decisive competitive advantage.

2025.28: the challenge of dual organizations, the AI economy is sputtering, society is worried...

Economic scrutiny, organizational transformation and workforce adaptation redefine AI’s next phase as sustainable execution overtakes technological performance as the decisive competitive advantage.

bduperrin.substack.com

Weekly wrap-up #4 : AI spending pressures, implementation challenges and governance tradeoffs reveal that long-term value depends less on adoption than on disciplined execution and organizational change.

2025.27: ATS, AI, and legal risks in recruitment, AI budget time bombs, AI agents and implicit rules...

AI spending pressures, implementation challenges and governance tradeoffs reveal that long-term value depends less on adoption than on disciplined execution and organizational change.

bduperrin.substack.com

Weekly wrap-up #3 : Why AI adoption is outpacing value creation, forcing organizations to rethink work, governance, software capabilities and the economics of automation.

2026.26 : The dilemma of laying off or growing, AI & operations, Meta's mistakes...

Why AI adoption is outpacing value creation, forcing organizations to rethink work, governance, software capabilities and the economics of automation.

substack.com

Weekly wrap-up #2 : Why AI’s future depends less on better models than on organizational design, cost discipline, governance, and the ability to continuously adapt.

2026.25 : Management hidden's face, the risks of automation, AI's risky funding...

Why AI’s future depends less on better models than on organizational design, cost discipline, governance, and the ability to continuously adapt.

bduperrin.substack.com

Btw my weekly wrap-up (issue #1) : as AI moves beyond model performance, economics, infrastructure, organizational design, ROI pressures and public skepticism increasingly shape adoption decisions.

2026.24 : AI, costs, infrastructure, employment, and work organization

As AI moves beyond model performance, economics, infrastructure, organizational design, ROI pressures and public skepticism increasingly shape adoption decisions.

substack.com

Trying to find my way back to bluesky. Not easy to find the right balance between many platforms that matter to me for some reason. I'll possibly share my thoughts and concerns later on since I think many of you have been through the same process.

AI First unfolds in three stages: acceleration (efficiency), extension (new capabilities), and transformation (redesign of roles and flows). Only by reaching this third level can AI shift from tool to design principle and deliver true organizational impact.

The promise of AI: acceleration, expansion, transformation

Artificial intelligence is often presented as a driver of efficiency, a means of working faster or reducing the burden of repetitive tasks. This perception is w

duperrin.com

The real AI challenge for businesses isn’t chasing model upgrades, but building “programmable” organizations. Agentic AI needs clear goals, structured knowledge, and local context. True impact requires managerial clarity, strong infrastructure, and a political response to shifting work dynamics.

Can AI Help Reverse the Oversimplification of Management?

For leaders to be programmers of their organisational OS, they need AI's help in embracing complexity and reality, rather than relying on simplistic data proxies

academy.shiftbase.info

AI often impresses but rarely convinces, because users don’t need wow, they need utility. Flashy demos don’t translate into real gains if everyday tasks aren’t improved. What matters isn’t how far the model goes, but how much faster it helps where time is actually lost.

AI is Impressive. So Why Does No One Care?

Silicon Valley is obsessed with engineering “wow” moments. But for the rest of the world, a “super-smart” AI that can’t handle basic arithmetic isn’t a miracle, it’s a distraction

theintelligencefabric.com

AI only transforms organizations when teams rethink how they work. Without structural change and shared goals, local gains remain isolated. Real impact comes from collective adoption, role redefinition, and embedding AI into a coordinated, team-driven transformation. www.duperrin.com/english/2025...

Collective appropriation of AI: the only condition for tangible impact

Business still tend to associate an employee's use of a tool with an increase in their performance or even a transformation in their working methods. They are d

duperrin.com

AI only boosts productivity once a structural transformation threshold is crossed. Without rethinking workflows and building "architectural literacy", its use remains superficial. Productivity gains don’t come from access alone, but from deep integration into how work is organized.

“The LLM productivity cliff”: New research offering a different lens on AI productivity

The dominant story about large language models is simple: give workers AI, and productivity rises. But workplace evidence is uneven.

dataconomy.com

Fear in meetings signals deeper dysfunction. When people hold back, group effectiveness drops. Psychological safety, not control, drives performance. Inclusive leadership, where mistakes and questions are welcome, turns meetings into real workspaces, not zones of silence or self-protection.

No one should be afraid to walk into a meeting

Everyone has had the experience of walking into a meeting. The door opens, faces are closed, you take your seat, you breathe a little too loudly, some people lo

duperrin.com

Pernod Ricard’s digital shift succeeded by fostering demand instead of imposing change. Through local pilots, support, and adjusted expectations, AI tools once seen as intrusive became valued aids. The real transformation was cultural, proving adoption grows through trust, not pressure.

How a French Spirits Company Created Employee Buy-In for AI

Digital transformation often stalls when employees resist new technology. To overcome this common challenge, French spirits company Pernod Ricard drew upon four strategies: proving value through A/B t...

hbr.org

“AI First” covers divergent realities : tech investment, strategic vision, organizational change, or experimentation. Without clarity, it risks becoming an empty slogan. Defining its meaning helps turn intention into structured action aligned with each company’s true goals.

AI First: four definitions that have nothing to do with each other

Since the concept of “AI First” was born, it has become, if not a real trend in organizational transformation, then at least a real topic of discussion

duperrin.com

AI is reshaping jobs unevenly: seniors are let go for tech that’s not ready, while entry roles vanish, blocking young graduates. This misaligned shift, driven by hype over results, weakens internal learning and innovation. A reset is needed to align talent strategy with real AI capabilities.

The AI layoff trap: Why half will be quietly rehired

New research shows entry-level jobs disappearing while experienced workers lose positions to AI that doesn't exist yet.

hrexecutive.com

AI adoption is slow but real, held back by tech maturity and organizational inertia. Impact lies in gradual process improvement, not flashy demos. Early adopters gain agility, but long-term value depends on smart data use and aligning AI with existing workflows, not replacing them outright.

Gregg Popovich shows that great leadership blends trust, adaptability, and human connection. His style balances rigor with flexibility, tailoring support to individuals while staying rooted in clear principles, proving that authority grows stronger when it listens, adjusts, and stays consistent.

Leading means learning to make room for others, an imaginary interview with Gregg Popovich

At a time when businesses are rediscovering the importance of trust, adaptability, and care in leadership, Gregg Popovich's career path offers us some fascinati

duperrin.com

Digital twins, once space tech, now model cities, bodies, and systems in real time. By blending AI, simulation, and live data, they test scenarios, cut costs, and boost performance. Their true power lies not in AI alone, but in mastering data engineering at scale.

Surprising things about digital twins

While digital twins are becoming increasingly popular, implemented, and understood, there are still many surprising things about digital twin technology

processexcellencenetwork.com

Automation and AI reshape skills, but short-term productivity hides a deeper risk: the erosion of skill renewal. As junior learning tasks disappear and roles become hybrid, skills act like volatile assets. Without sustained investment, firms fuel a fragile productivity bubble.

L’automatisation fragiliserait la capacité de renouvellement des compétences - IT SOCIAL

L’automatisation et l’IA transforment profondément la structure des compétences dans les entreprises. Mais au-delà des pénuries de talents largement commentées, une fragilité plus profonde se dessine....

itsocial.fr

"AI First" means prioritizing AI as a starting point, not excluding humans. Confusing it with "AI Only" leads to blind automation. True AI strategy blends tech with human judgment, aligning tools with intent and structure rather than chasing automation for its own sake.

AI First is not AI Only: clarify your intentions before transforming your business

When businesses talk about their ambition to become "AI First", there is often confusion about associating this orientation with widespread automation, as if a

duperrin.com

In 2025, HR tech saw widespread AI adoption, major consolidation, and ROI-driven choices. Applied and generative AI spread across all HR functions. M&A activity rose, while HR’s role shifted toward strategic impact, moving beyond a cost-center logic.

HR technology trends in 2025: AI adoption, ROI focus, and market consolidation

UNLEASH speaks to Ralf Hofmann, Managing Partner & Co-Founder at Drake Star to discuss the top trends in the HR technology market over the past 12 months, as well as looking forward in 2026.

unleash.ai

When managers shift from quick fixes to active observation, teams self-regulate, tensions ease, and decisions flow better. Inspired by agile thinking, this approach favors timing, clarity, and collective intelligence over control or rigid action plans.

Le Manager est l'observateur de son système

Quand le manager devient un observateur attentif de son système, le système commence à évoluer… dans le bon sens

qualitystreet.fr

“AI First” means starting with AI as a design choice, not excluding humans. Confusing it with “AI Only” leads to blind automation. True AI strategy balances tech with human judgment, focusing on structure, intent, and performance, not automation for its own sake.

AI First is not AI Only: clarify your intentions before transforming your business

When businesses talk about their ambition to become "AI First", there is often confusion about associating this orientation with widespread automation, as if a

duperrin.com

In 2025, HR tech saw mass AI adoption, platform consolidation, and ROI-driven decisions. Applied and generative AI spread across all HR functions. M&A surged as firms moved from point solutions to integrated systems. No bubble in sight, just a strategic shift toward efficiency and impact.

HR technology trends in 2025: AI adoption, ROI focus, and market consolidation

UNLEASH speaks to Ralf Hofmann, Managing Partner & Co-Founder at Drake Star to discuss the top trends in the HR technology market over the past 12 months, as well as looking forward in 2026.

unleash.ai

When managers shift from quick intervention to active observation, team dynamics improve. Inspired by agile and lean thinking, they see the organization as a living system. Management becomes less about control, more about timely support, clarity, and fostering collective self-regulation.

Le Manager est l'observateur de son système

Quand le manager devient un observateur attentif de son système, le système commence à évoluer… dans le bon sens

qualitystreet.fr

AI in hiring doesn't just reflect fairness but it redefines it. A study shows how algorithmic tools replaced human judgment with standardized metrics, sidelining context and diversity. When fairness is coded into systems, it must stay open to debate, not be mistaken for neutral truth.

New Research on AI and Fairness in Hiring

AI promises to make hiring fairer by reducing human bias, yet it often reshapes what fairness means—and locks in one definition. A three-year study of a global consumer-goods firm found that their alg...

hbr.org

HR too often acts downstream, fixing damage caused by flawed management systems. Rooted in an administrative legacy and reinforced by managerial disengagement, HR remains reactive. Repositioning HR around work design, integrated with operations, shifts focus from repair to performance.

HR is not the management's fire department

In many businesses, human resources departments don't intervene at the right time. They arrive when everything is going wrong, when a manager is losing control,

duperrin.com

Organizations accumulate invisible debts: technology debt and workforce debt. They don’t appear on balance sheets but erode performance through poor tools, outdated processes, overload, and underinvestment in skills. Short-term fixes create long-term drag.

Your business is in Debt - and it’s not Financial

Most organisations carry debts they don’t see. Not financial debts, but something far more crippling: Technology debt and Labour debt.

bloorresearch.com

Organizations are complex systems. Linear models fail; value emerges from interactions, feedback loops, and adaptation. Leadership means setting boundaries, observing behaviors, and redesigning the frame, not controlling outcomes or optimizing rigid structures.

People Are Complex - Our Systems Are Not

People Are Complex but the governance of organizations does not differentiate between their simple, complicated, and complex systems.

engagedorgs.com