"The future won’t belong to humans or machines, but to those who master the hybrid skill set combining AI literacy and human literacy."

The future of work is not about humans versus machines. Instead, it belongs to those who master a unique hybrid skill set. This blend combines AI literacy with essential human capabilities. Literacy in today's world lies in the ability to learn, unlearn and relearn - this has never been more true as it is in today's partnership with Agentic AI.

Andréa and I delve into the what these combined forces could look like, and how to build the framework for operational implementation. Digital transformation requires a hybrid skill set that fulfils the three different facets of transformation (cognitive, behavioural and emotional), which in turn align with the aspects of workplace culture (how we think, act and interact).

We discuss how to build a culture of trust in AI, essential for successful collaboration and highlight a critical distinction : humans interpret data semantically, giving it meaning and purpose, while AI processes it syntactically, based on patterns and probabilities. This difference impacts decision-making and ethical considerations.

Leaders of the future must be honest about and clearly see what tasks should be augmented using AI and how the time saved should be spent, i.e. what does AI do best now and, consequently, what should humans do better?

How are you ensuring that you, your teams & your organisation are developing the skills necessary to complement AI’s analytical power and drive results together.

The main insights you'll get from this episode are :

- Democratising access to a hybrid skill set means defining how to navigate the ‘fear vs. opportunity’ narrative of human potential in a world of AI, harking back to ‘man vs. machine’ as opposed to embracing a ‘man with machine’ approach.

- Digital transformation requires a hybrid skill set that fulfils the three different facets of transformation (cognitive, behavioural and emotional), which in turn align with the aspects of workplace culture (how we think, act and interact).

- The cognitive transformation element, i.e. decision-making, is the most problematic for leaders as humans still believe in the old way of making decisions; leaders are most exposed to this risk due to their past successes.

- In the words of Rasmus Hougaard, “ego is the worst enemy of leadership” and hampers effective decision-making - AI makes new things possible and humans are taken aback by the exponential rate at which we must learn and unlearn.

- Prompting, data sense-making and re-perception mean that we need to craft better input for AI but also ask humans better questions - unexpected questions open our minds to novelty and creativity.

- Our inherited educational model rewards good answers, not good questions, yet this stifles creativity and re-perception; the latter goes against the human (and educational) grain, but AI tools represent a good sparring partner.

- Rather than a product-centric approach, we are now called upon to make sense of data, but AI and humans interpret data differently: humans interpret it semantically (adding their own perspective); AI interprets it syntactically (as tokens without understanding meaning).

- The problem inherent to AI is that it does not understand or give meaning to its decisions and has no conscience about the action taken - humans must have responsibility for giving data meaning and not outsource this to AI.

- AI learns on a binary basis without context; tasks that are too demanding...

"Any AI you use today will be the worst AI you will use. You need to really learn how to challenge AI and learn how to have AI challenge you."

Rasmus and I delve into the research and questions of how leaders can embrace AI to become more human in their leadership, and how can this accompany them on the journey of navigating uncertainty and a more transactional workplace.

Currently less than 20% of leaders are ready for AI, despite it being a strategic necessity – it is an uncomfortable prospect that AI will take our jobs, but we can counter this by embracing AI and being better human leaders.

AI democratises knowledge, strategic thinking and decision-making - it will flatten organisations and leaders must embrace this, aiming to embody gratitude, humility and selflessness. This shift from ego to eco, and from doing to being is the key to leveraging what AI can enable in our humanity. Leaders must guard against cognitive laziness and human disconnection caused by AI, and actively challenge its outputs to ensure true human engagement.

AI surpasses humans in information access and processing speed, making it unwise for humans to compete in those areas. Instead, leaders should focus on what AI cannot replicate : Awareness involves understanding oneself, emotions, biases, and others. Wisdom is the ability to ask good discerning questions, distinct from AI’s knowledge. Compassion stems from a true intention to support & connect on a human level, which AI lacks despite its ability to process emotional data.

Rasmus shares his research and insights from his latest book 'more human' and from working with leaders and companies across the globe on how to create more human centred leadership in today's workplace.

The main insights you'll get from this episode are :

- AI augmented leadership requires three core competencies of awareness, wisdom and compassion: AI will have more information and faster processing power than any human brain but cannot be completely human.

- AI can help make us more aware if we use it as a sparring partner, providing it with everything there is to know about us to help us make decisions based on multiple different perspectives - context and mindset are vital here.

- Our neuroanatomy is uniquely human in that we perceive, discern, then respond (sentience). In terms of leadership, this translates to awareness (of biases, emotions and systems), discernment (wisdom not knowledge) and compassion.

- We are formatted to ‘do’, but AI requires us to react using our soft skills and human traits - being human at work is the blueprint for future leadership, driven moreover by purpose.

- It is the choice of every individual leader to ask not just what AI can do for me, but also to me: AI makes us cognitively lazy given that it is confidently both wrong and right - we must not fall prey to accepting its output without question.

- AI also has huge user bias – we must challenge it and have it challenge us, deploying mental hygiene when engaging with AI to make us more aware, wise and compassionate, fostering a mindset of equanimity.

- Having an AI proxy carries the risk of putting information in the hands of a tech firm, but once it has all the requisite information, it can provide very helpful answers in the form of outside-in views with psychometrics, etc.

- Asking AI for compassion-based responses highlights blind spots and gives actionable feedback to push us back into human compassion and awareness, e.g. asking for the worst possible outcomes of a potential decision.

- The workplace...

"Holistic transformation is not just how are you implementing a piece of software, AI is a really good opportunity for us to start to explore this"

Lindsay and I have a rich conversation diving deep into holistic transformation, the impact of AI, and how to navigate change in today’s rapidly evolving world. Organisational change management is often deployed too late, which speaks in favour of taking a holistic approach to transformation and asking from the outset: How do people change? How do they view themselves and their work?

Digital transformation is not just about implementing new software but also about how people change their thinking. AI is an excellent example. To get actual value from it, individuals need to rethink their roles and personal value. It’s about micro and macro changes happening together.

It is as ever, centred around the inner work we need to do as leaders to ensure that we are mastering what keeps us human, as well as looking at challenging the status quo constantly. AI is changing business models and the way we work, causing some organisations to dispense with this ‘inner work’ and hoping AI will do it for them. Curiosity is key! If people aren’t curious, they won’t help identify risks or roadblocks.

We talked about how important it is to show up as ourselves, even in professional settings. We also discussed gender parity and how much more we need to do. Lindsey shared her strategy for dismantling stereotypes: present all facets and encourage others to do the same. The more people meet others who don’t fit their stereotypes, the more likely they are to abandon them.

How can we create the conditions for curiosity to be present, and for leaders to learn, unlearn and relearn to enable more holistic and sustainable change ?

The main insights you'll get from this episode are :

- Change must be internal first of all, as well as holistic, and also on a micro and macro level; AI is changing business models and the way we work, causing some organisations to dispense with the ‘inner work’ and hoping AI will do it for them.

- Yet 95% of AI pilots fail because it is not a plug n play solution – even companies that are taking an informed approach to AI have individual employees seeking their own tactical solutions.

- AI means that we must all be good prompt engineers to succeed in the future, but many people underestimate the learning and effort this requires, and want to jump straight to the productive output, skipping the hard work.

- It also demands organisational and individual buy-in, understanding how it changes people’s value proposition to the organisation and that they must redefine their inputs, outputs and added value, maybe redefining their identity.

- It is crucial at the beginning of a transformation project to understand where authority sits and how decisions are made – decision-makers must lead the process – and how much curiosity there is.

- A lack of curiosity is the biggest obstacle to change, and organisations must be open to different (external) perspectives and to pivoting mid-way through the project if necessary.

- A ‘levels of agreement’ exercise with the people involved can help to determine the way forward, seeing failure as a point of learning that is painful but productive – but overidentifying with a job makes it very difficult to fail.

- Particularly in the age of AI, we should try and separate ourselves from our jobs and find a working environment that suits us, where we can present multiple facets of ourselves to address bias and be authentic to elicit a positive...