HR Leaders

AI is moving faster than most organisations can redesign themselves, so how do you stop transformation becoming a series of disconnected technology fixes?
In the most recent HR Leaders Podcast episode, I had an insightful conversation with Judith Wiese, Chief People and Sustainability Officer (CPSO) of Siemens AG.
She explains how Siemens is rethinking its operating model, skills infrastructure and approach to AI as it becomes a more connected technology company. From simplifying the foundations underneath HR to embedding learning into everyday work, Judith shares how Siemens is preparing its people and organisation for a world where transformation never really stops.

5 things you’ll learn from this episode:

The three-part AI model Siemens uses to separate everyday adoption from the much harder challenge of redesigning business processes
Why one of the biggest barriers to scaling AI has nothing to do with the technology itself
The unglamorous HR foundations Siemens believes need to be in place before personalised learning and skills strategies can really work
How Siemens is using skills data to uncover far more internal career opportunities than traditional CV matching could reveal
Why Judith believes the ability to keep learning may become more valuable than much of the knowledge employees already have today

🙏 Thank you to our series partner, Leapsome
Meet Leapsome: The AI-powered HR platform that raises your talent density. By unifying core HRIS, ATS, performance reviews, and learning into a single platform, Leapsome turns deep people data into measurable employee growth.
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What if AI isn't replacing jobs, but quietly redesigning the tasks inside them?
In the most recent HR Leaders Podcast episode, I had an important conversation with Sultan Murad Saidov, Former CEO / Founder and Investor at Beamery. He explains why task intelligence could become critical to workforce planning, how AI is changing the work inside existing roles, and why deciding what gets automated should become an HR question, not just a technology question.
Drawing on more than a decade of building Beamery and working at the intersection of AI, skills and workforce data, Sultan explains why skills alone are no longer enough to understand where work is heading.
5 things you’ll learn from this episode:
Why looking at tasks instead of job titles changes how leaders understand AI's impact on work
The research Sultan references suggesting 75% of jobs may need redesign because of AI augmentation
How digital twin teams could help leaders model workforce decisions before making them
Why reducing junior roles may create a long-term talent and career pipeline problem
Why Sultan believes HR and technology teams should jointly lead the redesign of work

🙏 Thank you to our series partner, Arist

Meet the end-to-end AI agent for enablement that finds talent gaps, builds personalized interventions, and delivers learning directly in the flow of work → https://arist.com/resources/webinars/agent?utm_source=hr_leaders_podcast&utm_medium=sponsored&utm_campaign=hr_leaders_podcast_cr_june_2026
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Constant tech shifts and viral noise are quietly exhausting your workforce and killing critical thinking.
In the latest HR Leaders Podcast episode, I spoke with Laura Maffucci, Head of HR at Globalization Partners. She explains why HR cannot rely on corporate spin, unvetted AI add-ons, or forced office returns during times of rapid change.
Most organizations do not lack technology tools. They lack transparent communication, psychological safety, and a clear process for building learning agility. And even when tools are enabled, a harder question remains:Are you actually solving an operational problem, or just adding tool overload?

5 things you’ll learn from this episode:

The unconventional quarterly award designed to celebrate smart operational failures
The quiet credibility trap behind performative return-to-office mandates
The hidden data flaw causing 70–80% of enterprise AI bots to give bad advice
The three core human traits rendering static technical skills obsolete
A simple peer-led initiative driving AI adoption far better than formal training
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What if the self-doubt holding you back isn't proof of failure, but evidence of growth?
In the most recent HR Leaders Podcast episode, I had an important conversation with Maharukh Dalal, founder of The Career Accelerator for Women by Maharukh Dalal. She explains how senior leaders can overcome imposter syndrome by closing the internal identity gap, reframing self-doubt into a signal of growth, and shifting self-perception to drive executive execution.
Drawing on two decades of corporate leadership across finance and hospitality, Dalal explains how mindset precedes execution. This conversation offers senior HR and business leaders a clear playbook for mastering the mental side of executive performance.
5 things you’ll learn from this episode:
The psychological gap that stops capable leaders from taking action
A simple two-word shift that instantly turns daily dread into agency
What a 1980 university experiment reveals about how people actually perceive you
The advice Rafael Nadal’s coach gave him during his worst slump that applies to executives
Why relying purely on willpower and discipline eventually fails even top performers

🙏 Thank you to our series partner, Arist
Meet the end-to-end AI agent for enablement that finds talent gaps, builds personalized interventions, and delivers learning directly in the flow of work → https://arist.com/resources/webinars/agent?utm_source=hr_leaders_podcast&utm_medium=sponsored&utm_campaign=hr_leaders_podcast_cr_june_2026
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AI could influence 90% of jobs. David Lloyd says AI literacy is still only around 38%.
That gap is where many enterprise AI strategies begin to break.
In the latest HR Leaders Podcast episode, I spoke with David Lloyd, SVP Platform Engineering & Chief AI Officer at Dayforce. He explains why HR cannot wait until the end of an AI transformation to address skills, trust and organisational change.
Most organisations do not lack AI ideas. They lack trusted data, safe environments and a clear process for deciding which ideas deserve to scale.
And even when an experiment works, a harder question remains:
Can it scale from one employee to 5,000?
5 things you’ll learn from this episode:
Why three to six months is too long to judge an AI pilot
The three questions that decide whether an AI idea moves forward
What is really driving the rise of shadow AI
Why adding AI across a fragmented HR stack creates more chaos
How a three-person governance team can approve ideas in under five days

🙏 Thank you to our series partner, Fluide
Work is changing too fast for learning to take weeks. Learn how Fluide turns skill gaps into live adaptive learning in 3 steps and see performance move by Friday. Try FLuide now → https://fluide.ai/
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