Hi team. A lot of my job is talking to organisations about AI and the people using it: through informal conversations, cross-industry speaking events or targeted workshops designed to help leaders understand the future of work in the Age of AI. And now, having engaged with hundreds of individuals over the past 7 months, trends are starting to emerge.

• •

Speaking to +30 cross industry leaders about Leading in the Age of AI in London, hosted by Mentimeter.
In today’s post, I want to give you a sense of what I am seeing across companies, mainly large enterprises. Big organisations are struggling with AI, in part because of technology challenges (i.e. – tech debt, data and knowledge management issues, cyber security, etc), but more so because they fail to treat AI as a work design, leadership, and capability challenge.

My observations are rooted in anecdotal evidence gathered through dozens of conversations and a small number of interviews with HR leaders for an industry event.1 I offer advice to leaders on what specifically you can do to prepare yourself and your team for the wild ride ahead.

Even if my research methods are not to a scientific standard, I’d argue the vibes are strong and the message is clear: regardless of what your company has decided to do (or not do) with generative AI, YOU must get on the AI train now if you are going to thrive at work in the next few years.

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The gap between the frontier and average AI use is a chasmI spend all day, every day, thinking and learning about AI. I get that I am well ahead of the average person in both my AI knowledge and daily AI use. And while I work very hard to ensure my content resonates with the audience – no matter their ‘AI level’ – I am always surprised at how far most are from the AI frontier.

The majority of people in large organisations have tried AI for ‘assistance’ tasks: transcription, summarising materials, basic research, writing emails, etc. Enterprises have rolled out AI adoption programs that include Copilot access, basic training and traditional tech adoption activities, such as communications campaigns, AI champions, knowledge sharing activities, etc. And while this is a necessary place to start, it’s absolutely not enough to prepare your workforce to leverage AI’s full capabilities.

The gap between what’s happening at the frontier of AI and average AI use is growing day by day. AI progress is not slowing down, and yet, despite this pace, some have created and deployed whole teams of agents to complete end-to-end workflows, whereas most are still using AI chatbots like Google. Companies absolutely need to do more to help their workforce move to AI augmentation. But more than that, individuals need to get serious about their AI use, and their leaders should support them along the way. Their careers and job security depend on it.

What you can do: As a leader – regardless of where you sit in an organisation – you have a Duty of Care to your teams to strongly encourage AI use. Give them time to learn and experiment. Create space to collectively sense-make how AI can and will impact your jobs, and where it can be used appropriately to create real value.

Share

AI adoption and impact are inconsistentWhen generative AI first launched into the mainstream, we started to talk about the Jagged Frontier of AI capabilities: AI is better and progressing faster in some areas than others. Now the same concept can be applied to how AI is impacting knowledge work: the jagged frontier of AI is now impacting jobs in dramatically different ways.

• •

The jagged frontier means some jobs (blue circles) are impacted more than others. Code is a prime example.
For example, 80-90% of code at big tech companies is now written by AI. For a Software Developer, their job has changed significantly in the past 12 months. They now spend their days directing, verifying, and owning the system that writes code rather than creating the code themselves. Yet in the same organisation, some roles, especially those with heavy human involvement, are barely touched by AI.

The impact of AI on organisations will continue to be uneven. A I capabilities will impact some jobs more than others, even within functions and teams, and the cost of compute will continue to be a limiting factor. Leaders will need to get comfortable with the nuance and complexity of this transition: a one-size-fits-all approach just won’t work.

What you can do: As a leader, you now need to hone your ‘dynamic range’: the ability to look far into the future whilst dealing with the day-to-day, all while monitoring the immediate and wider context for potential risks and new information. When it comes to the impacts of AI on your teams, you must be watching the AI frontier to know what’s coming, while looking at what’s immediately in front of you and watching for signals for the changing environment… all while translating this into what this means for your teams, both today and in the future.

Leave a comment

ROI pressure from productivity is still a thingMost organisations are still treating AI like a standard tech upgrade. The ‘business case’ needs to stack up. The expectations from leaders are that AI must prove a return on investment to be approved. And unfortunately, this is often in the form of ‘productivity gains’ (aka headcount savings).

Besides the unnecessary anxiety and change resistance this creates, I genuinely think leaders are focusing on the wrong ROI metrics. Yes there will be some productivity savings with AI, but you shouldn’t try and just take it out of the business entirely. The better question is how are you redeploying that capacity for growth (do much more with the same) and innovation (do new things that weren’t possible before).

Likewise, I believe most companies are misallocating AI on the balance sheet. Expenditure on AI is treated like a technology investment rather than an operational cost. But I believe this is now just a cost to do business. Would you expect an ROI when providing office space, internet access, a phone and a laptop for every person hired? Likely not. And while it’s important to optimise spend and think smartly about who gets what access to AI capabilities, I strongly argue that giving your employees access to generative AI is now just part of doing knowledge work.

What can you do: Unless you’re a C-suite or senior leadership, most of us can’t control top-down headcount targets required as part of an AI strategy. But you can control is your ability to get ahead of the game. I’ve talked to a few leaders who are proactively working with their teams to use AI for productivity gains AND reallocating capacity into other work.2 They are essentially pre-emptively creating a business case to demonstrate value focused on growth and innovation. The hope is that if and when the pressure for headcount savings grows, leaders will have the evidence to protect their teams from indiscriminate reductions.

Share

Everyone is worried about the futureIn the West, most frontier AI is being developed with VC money, for which fast returns on investment are expected. I argue this is why most CEOs of the big AI companies continue to make wild proclamations about how AI will impact jobs – it justifies the record levels of investments made into AI companies and the infrastructure around them.

• •

Just a sample of the headlines about AI coming for all our jobs.
The unintended consequence is that AI is now triggering deep psychological threat responses across knowledge work. If you’re familiar with David Rock’s SCARF model, AI is hitting all five domains at once: Status (will I still be valued if a machine can do my work?), Certainty (no one can tell me what my job looks like in two years), Autonomy (tools and targets are being imposed on me), Relatedness (am I falling behind my peers? Am I still part of the in-group?), and Fairness (why is my role being disrupted while others aren’t?). It’s no wonder people are overwhelmed.

And while I am cautiously optimistic about an AI augmented future, I do believe it’s likely going to get worse before it gets better. I believe the humans who effectively use and orchestrate AI will win out over those who reject it entirely. So it’s in everyone’s interest to get yourself up to speed with AI, and dedicate some time every week to learning and experimenting with the frontier models

What you can do now: Name the threat. One of the most powerful things a leader can do is acknowledge, out loud with your team, that AI is unsettling across all of these dimensions. Then get practical: the best antidote to AI anxiety is AI fluency. When people use these models consistently, they quickly see both the genuine value and the very real limitations, especially in their domain of expertise. But with AI progressing so fast, both value and limitations evolve equally quickly. So the only way to secure your future is to be someone who evolves their work alongside AI, and to help your team do the same.3

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HR is behind the strategic curveGenerally speaking, HR feels far behind when it comes to AI. From an overall business POV, HR is frequently absent from the conversations when the AI strategy is set – despite there being significant people and operating model implications. And then they are left to manage consequences rather than influence decisions and design (I’m looking at you, bad headcount savings projections).

The focus of AI for HR seems to be internal – how you can ‘AI-ify’ existing processes rather than focusing on what the future of work may look like, let alone taking a first principles approach to redesigning workflows for AI. HR business partners often lack the AI literacy to engage meaningfully with enterprise-level technology decisions. I’ve heard many stories where HR practitioner has effectively disengaged from the AI conversations because their work deal with humans, ‘AI won’t impact them’.

Of course, my view is the exact opposite. HR is the function that is BEST PLACED to lead organisations into a future where we can make the most of both human and AI capabilities. They must start thinking strategically about the future of work in the Age of AI NOW: specifically, how they will become orchestrators of work and capabilities, and managers of both human and digital labour. But sadly in HR, few have even realised the scale and size of the AI journey we are all about to go on.

• •

We brought together +25 HR Leaders a few weeks ago to talk about the Future of Work in the Age of AI as part of our first HoRizon Collective event.
What you can do now: If you’re HR, get yourself up to speed quickly about AI – well beyond your functional domain as well. No one will give you a seat at the table to talk AI transformation if you’re using the models in their most basic form. If you’re a leader who really needs HR at the table, at the very least, consider the people and operating model aspects before you invest in AI. Just because AI can doesn’t mean it should, and I have seen many AI projects fail because they started with the technology, rather than the problem they needed to solve.

Check out my website

AI is now a people & culture issueIn the latter half of last year, the AI transformation gap was all anyone could talk about. The August 2025 headline that “95% of organizations studied are seeing zero return on their AI initiatives” drove the conversation into a frenzy. Despite the questionable research methods and the clickbaity, overblown headline, the ‘GenAI Divide’ hit a nerve. Most leaders resonated with the feeling that they were spending a lot of money on AI without seeing much change and impact in their organisations.

Thankfully, I do think leaders have now realised that AI is MUCH more than a technology. A few big organisations are focused on reimagining work with AI rather than focusing solely on what AI can do in and of itself. Many of my fellow Organisation Transformation and Change Management professionals are being asked to ‘help AI work’ in their companies, which is a great signal.

That said, I still think most organisations are measuring the wrong indicators of AI adoption, and they are missing a key component that’s required for transformational change. But awareness is always a great first step.

What you can do now: When thinking about using AI in your team / function / organisation, start with the WORK BEING DONE rather than the people and the technology. Begin with the ‘first principles’ of a workflow by completing this statement: This workflow transforms [inputs] into [outputs] so that [who] can do [what]. This is important to the business because [the outcome / the why]. Then, break down a workflow into tasks to better understand what’s being done (and should stay) by humans, and what potentially could be augmented / automated / agentified with AI. Taking this bottom-up approach will help ensure you are selecting the right tasks to be redistributed to AI and protecting what should stay with your human worker.

Connect with me on LinkedIn

The AI capability build is missingMost big enterprises have an AI strategy and have invested heavily into Copilot and AI adoption activities. Almost no one has started to think concretely about how jobs and organisations will be redesigned for an AI future. And few have invested in building the capabilities required to move their teams from AI assistance to AI augmentation.

Most agree that this rethinking of work is necessary, but no one knows where to start.

I worry that enterprises will continue to take ill-informed people decisions without this redesign. And that many companies will back themselves into a corner by cutting headcount too fast and too deep without considering the capabilities of the humans who remain.

Using generative AI for true AI augmentation requires a different mental model than anything we’ve had before. Some early adopters have figured it out, but I have yet to come across any organisation training this at scale. But if large enterprises really want to transform their organisations with AI, then building this new skill set across your entire knowledge workforce is where you start.

What you can do today: Start building AI augmentation skills. Shameless self-promotion here: I’ve created a six-step method to teach leaders how to design work for generative AI, delivered through the one-day AI Accelerator. You’ll learn how to transform individual workflows for Generative AI, before applying it to teams and learning how to build an AI-forward culture across your organisation.

Share

So what now?Are these observations radical? Not really, but if they tell us anything, it’s that no one has figured this out yet. We are all facing the same sort of challenges, and few are tackling them well, and certainly not all at once.

But what I’ve observed from hundreds of conversations with leaders across all sectors is that those companies that are making material progress in their AI transformation have two things in common:

1. They’ve stopped treating AI as solely a technology project, and

2. They’ve started investing in the human capability to work alongside it.

But even if your company doesn’t have an AI strategy or hasn’t done anything to help the workforce adopt generative AI, as a leader: YOU DO NOT NEED TO WAIT.

There is a lot you can do to help your team on this journey, even if the basic AI tools are not yet available in your organisation. Every section of this post includes something you can do now, with your team, in your context. I really believe the leaders who will thrive through this transition are the ones who start before they’re asked to. They learn, they experiment, they redesign how their teams work, and they build the case for change through evidence and results.

The AI journey ahead is enormous. It’s a scale of change we have not seen since the Industrial Revolution, but instead of a century, transitioning to the Age of AI is going to happen in a decade. But it’s important to stay grounded and not get distracted by the headlines and the hype. Leaders - you have more agency than you think, so start today.

1Considering the current political economy of the world is running on plot and vibes right now, pulling out themes from many chats is more than what most are doing.

2One of the ways I help teams do this is through the AI Accelerator - a one-day (or 3 hours x 3 days) working session designed to help move your team from AI curious to AI innovative.

3And yes, this means paying for a proprietary AI model even if your company doesn’t. If you are privilege to be in the financial position where you are not living paycheque to paycheque, then you can afford the $20/month to access a paid-for version of AI.

🤝 When you’re ready, here are a few ways I can help:• The AI Accelerator: My one-day (or virtual) workshop designed to help your team become truly AI augmented. This is not AI 101 training, rather it teaches you a framework to apply to your own work to make the most of both human and AI capabilities and ensure your team leverages different cultural levers to ensure the changes and new ways of working stick.

• Keynotes & Leadership Talks: I help leaders better understand and positively take action in the Future of Work in the Age of AI. I combine insight, inspiration and provide a roadmap for practical action, tailored to your context. Audiences will leave with cautious optimism, an understanding that they have agency to make a difference in this moment and plan to amplify human potential through AI.

• Strategic Advisory: I work with senior leaders navigating towards the future

of work in the age of AI. Sometimes it’s helping them see what’s coming. Other times, it’s rolling up sleeves to redesign operating models and workflows to be AI-forward. Often it’s both.

🔖. Subscribe for more insights, ideas and practical ways for you to help navigate the future of work in the Age of AI 🤖Subscribe now

Hi team. A lot of my job is talking to organisations about AI and the people using it: through informal conversations, cross-industry speaking events or targeted workshops designed to help leaders understand the future of work in the Age of AI. And now, having engaged with hundreds of individuals over the past 7 months, trends are starting to emerge.

In today’s post, I want to give you a sense of what I am seeing across companies, mainly large enterprises. Big organisations are struggling with AI, in part because of technology challenges (i.e. – tech debt, data and knowledge management issues, cyber security, etc), but more so because they fail to treat AI as a work design, leadership, and capability challenge.

My observations are rooted in anecdotal evidence gathered through dozens of conversations and a small number of interviews with HR leaders for an industry event.#footnote-1" target="_self">1 I offer advice to leaders on what specifically you can do to prepare yourself and your team for the wild ride ahead.

Even if my research methods are not to a scientific standard, I’d argue the vibes are strong and the message is clear: regardless of what your company has decided to do (or not do) with generative AI, YOU must get on the AI train now if you are going to thrive at work in the next few years.

Subscribe now

The gap between the frontier and average AI use is a chasm

I spend all day, every day, thinking and learning about AI. I get that I am well ahead of the average person in both my AI knowledge and daily AI use. And while I work very hard to ensure my content resonates with the audience – no matter their ‘AI level’ – I am always surprised at how far most are from the AI frontier.

The majority of people in large organisations have tried AI for ‘assistance’ tasks: transcription, summarising materials, basic research, writing emails, etc. Enterprises have rolled out AI adoption programs that include Copilot access, basic training and traditional tech adoption activities, such as communications campaigns, AI champions, knowledge sharing activities, etc. And while this is a necessary place to start, it’s absolutely not enough to prepare your workforce to leverage AI’s full capabilities.

The gap between what’s happening at the frontier of AI and average AI use is growing day by day. AI progress is not slowing down, and yet, despite this pace, some have created and deployed whole teams of agents to complete end-to-end workflows, whereas most are still using AI chatbots like Google. Companies absolutely need to do more to help their workforce move to AI augmentation. But more than that, individuals need to get serious about their AI use, and their leaders should support them along the way. Their careers and job security depend on it.

What you can do: As a leader – regardless of where you sit in an organisation – you have a Duty of Care to your teams to strongly encourage AI use. Give them time to learn and experiment. Create space to collectively sense-make how AI can and will impact your jobs, and where it can be used appropriately to create real value.

Share

AI adoption and impact are inconsistent

When generative AI first launched into the mainstream, we started to talk about the Jagged Frontier of AI capabilities: AI is better and progressing faster in some areas than others. Now the same concept can be applied to how AI is impacting knowledge work: the jagged frontier of AI is now impacting jobs in dramatically different ways.

For example, 80-90% of code at big tech companies is now written by AI. For a Software Developer, their job has changed significantly in the past 12 months. They now spend their days directing, verifying, and owning the system that writes code rather than creating the code themselves. Yet in the same organisation, some roles, especially those with heavy human involvement, are barely touched by AI.

The impact of AI on organisations will continue to be uneven. A I capabilities will impact some jobs more than others, even within functions and teams, and the cost of compute will continue to be a limiting factor. Leaders will need to get comfortable with the nuance and complexity of this transition: a one-size-fits-all approach just won’t work.

What you can do: As a leader, you now need to hone your ‘dynamic range’: the ability to look far into the future whilst dealing with the day-to-day, all while monitoring the immediate and wider context for potential risks and new information. When it comes to the impacts of AI on your teams, you must be watching the AI frontier to know what’s coming, while looking at what’s immediately in front of you and watching for signals for the changing environment… all while translating this into what this means for your teams, both today and in the future.

Leave a comment

ROI pressure from productivity is still a thing

Most organisations are still treating AI like a standard tech upgrade. The ‘business case’ needs to stack up. The expectations from leaders are that AI must prove a return on investment to be approved. And unfortunately, this is often in the form of ‘productivity gains’ (aka headcount savings).

Besides the unnecessary anxiety and change resistance this creates, I genuinely think leaders are focusing on the wrong ROI metrics. Yes there will be some productivity savings with AI, but you shouldn’t try and just take it out of the business entirely. The better question is how are you redeploying that capacity for growth (do much more with the same) and innovation (do new things that weren’t possible before).

Likewise, I believe most companies are misallocating AI on the balance sheet. Expenditure on AI is treated like a technology investment rather than an operational cost. But I believe this is now just a cost to do business. Would you expect an ROI when providing office space, internet access, a phone and a laptop for every person hired? Likely not. And while it’s important to optimise spend and think smartly about who gets what access to AI capabilities, I strongly argue that giving your employees access to generative AI is now just part of doing knowledge work.

What can you do: Unless you’re a C-suite or senior leadership, most of us can’t control top-down headcount targets required as part of an AI strategy. But you can control is your ability to get ahead of the game. I’ve talked to a few leaders who are proactively working with their teams to use AI for productivity gains AND reallocating capacity into other work.#footnote-2" target="_self">2 They are essentially pre-emptively creating a business case to demonstrate value focused on growth and innovation. The hope is that if and when the pressure for headcount savings grows, leaders will have the evidence to protect their teams from indiscriminate reductions.

Share

Everyone is worried about the future

In the West, most frontier AI is being developed with VC money, for which fast returns on investment are expected. I argue this is why most CEOs of the big AI companies continue to make wild proclamations about how AI will impact jobs – it justifies the record levels of investments made into AI companies and the infrastructure around them.

The unintended consequence is that AI is now triggering deep psychological threat responses across knowledge work. If you’re familiar with David Rock’s SCARF model, AI is hitting all five domains at once: Status (will I still be valued if a machine can do my work?), Certainty (no one can tell me what my job looks like in two years), Autonomy (tools and targets are being imposed on me), Relatedness (am I falling behind my peers? Am I still part of the in-group?), and Fairness (why is my role being disrupted while others aren’t?). It’s no wonder people are overwhelmed.

And while I am cautiously optimistic about an AI augmented future, I do believe it’s likely going to get worse before it gets better. I believe the humans who effectively use and orchestrate AI will win out over those who reject it entirely. So it’s in everyone’s interest to get yourself up to speed with AI, and dedicate some time every week to learning and experimenting with the frontier models

What you can do now: Name the threat. One of the most powerful things a leader can do is acknowledge, out loud with your team, that AI is unsettling across all of these dimensions. Then get practical: the best antidote to AI anxiety is AI fluency. When people use these models consistently, they quickly see both the genuine value and the very real limitations, especially in their domain of expertise. But with AI progressing so fast, both value and limitations evolve equally quickly. So the only way to secure your future is to be someone who evolves their work alongside AI, and to help your team do the same.#footnote-3" target="_self">3

Subscribe now

HR is behind the strategic curve

Generally speaking, HR feels far behind when it comes to AI. From an overall business POV, HR is frequently absent from the conversations when the AI strategy is set – despite there being significant people and operating model implications. And then they are left to manage consequences rather than influence decisions and design (I’m looking at you, bad headcount savings projections).

The focus of AI for HR seems to be internal – how you can ‘AI-ify’ existing processes rather than focusing on what the future of work may look like, let alone taking a first principles approach to redesigning workflows for AI. HR business partners often lack the AI literacy to engage meaningfully with enterprise-level technology decisions. I’ve heard many stories where HR practitioner has effectively disengaged from the AI conversations because their work deal with humans, ‘AI won’t impact them’.

Of course, my view is the exact opposite. HR is the function that is BEST PLACED to lead organisations into a future where we can make the most of both human and AI capabilities. They must start thinking strategically about the future of work in the Age of AI NOW: specifically, how they will become orchestrators of work and capabilities, and managers of both human and digital labour. But sadly in HR, few have even realised the scale and size of the AI journey we are all about to go on.

What you can do now: If you’re HR, get yourself up to speed quickly about AI – well beyond your functional domain as well. No one will give you a seat at the table to talk AI transformation if you’re using the models in their most basic form. If you’re a leader who really needs HR at the table, at the very least, consider the people and operating model aspects before you invest in AI. Just because AI can doesn’t mean it should, and I have seen many AI projects fail because they started with the technology, rather than the problem they needed to solve.

Check out my website

AI is now a people & culture issue

In the latter half of last year, the AI transformation gap was all anyone could talk about. The August 2025 headline that “95% of organizations studied are seeing zero return on their AI initiatives” drove the conversation into a frenzy. Despite the questionable research methods and the clickbaity, overblown headline, the ‘GenAI Divide’ hit a nerve. Most leaders resonated with the feeling that they were spending a lot of money on AI without seeing much change and impact in their organisations.

Thankfully, I do think leaders have now realised that AI is MUCH more than a technology. A few big organisations are focused on reimagining work with AI rather than focusing solely on what AI can do in and of itself. Many of my fellow Organisation Transformation and Change Management professionals are being asked to ‘help AI work’ in their companies, which is a great signal.

That said, I still think most organisations are measuring the wrong indicators of AI adoption, and they are missing a key component that’s required for transformational change. But awareness is always a great first step.

What you can do now: When thinking about using AI in your team / function / organisation, start with the WORK BEING DONE rather than the people and the technology. Begin with the ‘first principles’ of a workflow by completing this statement: This workflow transforms [inputs] into [outputs] so that [who] can do [what]. This is important to the business because [the outcome / the why]. Then, break down a workflow into tasks to better understand what’s being done (and should stay) by humans, and what potentially could be augmented / automated / agentified with AI. Taking this bottom-up approach will help ensure you are selecting the right tasks to be redistributed to AI and protecting what should stay with your human worker.

Connect with me on LinkedIn

The AI capability build is missing

Most big enterprises have an AI strategy and have invested heavily into Copilot and AI adoption activities. Almost no one has started to think concretely about how jobs and organisations will be redesigned for an AI future. And few have invested in building the capabilities required to move their teams from AI assistance to AI augmentation.

Most agree that this rethinking of work is necessary, but no one knows where to start.

I worry that enterprises will continue to take ill-informed people decisions without this redesign. And that many companies will back themselves into a corner by cutting headcount too fast and too deep without considering the capabilities of the humans who remain.

Using generative AI for true AI augmentation requires a different mental model than anything we’ve had before. Some early adopters have figured it out, but I have yet to come across any organisation training this at scale. But if large enterprises really want to transform their organisations with AI, then building this new skill set across your entire knowledge workforce is where you start.

What you can do today: Start building AI augmentation skills. Shameless self-promotion here: I’ve created a six-step method to teach leaders how to design work for generative AI, delivered through the one-day AI Accelerator. You’ll learn how to transform individual workflows for Generative AI, before applying it to teams and learning how to build an AI-forward culture across your organisation.

Share

So what now?

Are these observations radical? Not really, but if they tell us anything, it’s that no one has figured this out yet. We are all facing the same sort of challenges, and few are tackling them well, and certainly not all at once.

But what I’ve observed from hundreds of conversations with leaders across all sectors is that those companies that are making material progress in their AI transformation have two things in common:

1) They’ve stopped treating AI as solely a technology project, and

2) They’ve started investing in the human capability to work alongside it.

But even if your company doesn’t have an AI strategy or hasn’t done anything to help the workforce adopt generative AI, as a leader: YOU DO NOT NEED TO WAIT.

There is a lot you can do to help your team on this journey, even if the basic AI tools are not yet available in your organisation. Every section of this post includes something you can do now, with your team, in your context. I really believe the leaders who will thrive through this transition are the ones who start before they’re asked to. They learn, they experiment, they redesign how their teams work, and they build the case for change through evidence and results.

The AI journey ahead is enormous. It’s a scale of change we have not seen since the Industrial Revolution, but instead of a century, transitioning to the Age of AI is going to happen in a decade. But it’s important to stay grounded and not get distracted by the headlines and the hype. Leaders - you have more agency than you think, so start today.