When people talk about AI as if it’s one big thing, it makes it harder to deal with in any meaningful way. On the flip side, it can sometimes seem like there are 9,768 small AI tasks or tools to keep up with – and that doesn’t make the AI wave any easier to address either.
If you aren’t clear about what problem you’re solving – or even how to think about it – it can be difficult to make progress. Activity or avoidance gets substituted for strategic momentum.
When I think about AI, I often run specific situations or client questions through 10 filters to help hone in on the real challenge:
1. Positioning
Where are you in the overall landscape of your industry? And how is that industry changing?
Many businesses fail to adapt quickly enough because of the way they define their industry and how they think about competing within it (or outside of it).
For example, McCormick produces spices, but it considers itself to be in the flavor industry because it understands that its customers don’t want spices – they want to change the flavor of their food. If someone figures out how to create more suitable flavor alternatives, spices become less relevant. It’s not the product but the job that product does.
Your thinking needs to “color outside the lines” even more now. How will AI shift the frontiers of your industry? What real role do you play for your customer?
2. Delivering
How are the basic components of your business model (and others you compete with) shifting?
This has both an external and an internal component. How are the very ways you reach customers evolving? What capabilities are becoming table stakes because AI is making them too easy?
An external example: Something that once signaled a large advantage (such as removing friction from an online customer buying experience) may no longer be as valuable if the customer is using an agent to complete the process rather than doing it themselves.
An internal example: embedding previously cost prohibitive AI software into delivery to enhance the customer experience. Once it becomes common practice, it becomes table stakes.
3. Strategizing
Given how you define your industry and what it takes to reach customers and deliver, where will you choose to play and how will you win?
If you’ve properly assessed the landscape and the business model, then you’re well on your way to creating the choices that lead to true differentiation.
The biggest watch out is to make sure you’re properly differentiating – especially if you’re using AI to help you with strategy. AI pushes towards homogeny. Now is the time to consider what’s missing, what’s emerging, what’s never been done, what could be, and what’s really needed.
4. Building
What capabilities do you need to build on? Which do you need to explore for the first time? And which do you need to forget about?
At this point, it’s clear that AI can’t be ignored. But that doesn’t mean it needs to be a core capability all by itself. Too often, leaders think of AI like a tech upgrade, trying to make sure people understand and experiment with the tech instead of how it fundamentally alters their business and what needs to be embedded.
How a company chooses to incorporate AI into its business largely depends on how well it understands how people inside work together with each other and with technology to create strategic capabilities. This includes knowing what you’re already good at as well as what you need to build on – and what you need to start experimenting with ASAP.
You need to know yourself deeply to do this – I’ve watched too many companies skip over this part because it can be difficult to get to the level of nuance needed. It’s hard to see what often becomes second nature or “the way we do things.” Break it down into small, connected parts – and when you think you can’t break it down further, try again.
With this nuance you can make better moves. Depending on where and how a company is competing, it might make sense for AI to be the foundation for a capability a company builds all by itself. It definitely makes sense to incorporate it into workflows, incorporate agents, and to use it to strengthen existing capabilities. In some cases, it doesn’t make sense to encourage mass trial, adoption, or conversion with every piece of your business – not every tool is critical.
5. Organizing
How will you organize to support and form your most critical strategic capabilities?
Hiring and firing decisions are too often considered primarily through the lens of an org chart that can be seen on paper, standard department names, total headcount, or a line item expense. True organizational design goes beyond these basics and looks at how the organization is configured to deliver on its strategic capabilities.
Again, this means understanding how people work together with technology to create those capabilities. Companies that effectively incorporate AI don’t simply look to replace headcount – they deeply understand how the work gets done, and reimagine how it can be done.
You’ll see a lot more from me on this topic in the future, as it’s one of the more misunderstood areas I continue to encounter.
6. Thinking
Is AI helping you think, or giving you the illusion of thinking?
In Thinking Fast and Slow, Nobel Prize winning author Daniel Kahneman breaks down a number of cognitive biases that humans use to shortcut their thinking. When they do, they make decisions that seem logical or intuitive, but go against the actual desired outcome.
One of those cognitive biases is the idea that the more information we have, the more we think it means. In other words, we attribute meaning to information simply because it exists, not because it matters, or because it’s good.
AI does an incredible job at providing information. I’ve watched too many leaders become delighted at what it produced when what it produced was not of good quality or sound thinking. After all, it feels good to believe something is “done.”
Don’t let it shortcut or substitute your thinking.
7. Learning
Is AI helping you learn, or is it destroying your foundation?
An MIT study found that for those that used ChatGPT as a substitute for writing, entire regions of the brain deteriorated over time.
Those that know the science of learning know that mental capacities and overall knowledge and skills expand because smaller blocks of knowledge and skills have been built over time – they provide the foundation from which more can be done over time.
Or as I like to say, if you never hike small hills, it’s going to be more difficult to hike bigger ones.
The study is still in its infancy and was conducted with students, but it’s not too much of a stretch to think about how this applies with adults. Think about how often we talk about cognitive deterioration in retirement because people “didn’t keep their brain active.” If you value a certain strength – be it physical or mental – it’s important to give it regular exercise.
8. Solving
How well are you articulating the real problem to solve? Are you pretending a problem is simpler than it is?
An Apple study found that when solving complex problems, LLMs (large language models; generative AI) “completely collapsed.” After a certain level of complexity, they start creating more simple reasoning or lose the plot.
Humans, too, tend to err on the side of making problems more simple than they are. We study disciplines and create departments as if they are separate fields and functions without considering the interconnectedness of each of them and how that impacts the outcomes we want to create.
Avoid over-simplifying or letting AI do so just for the satisfaction of having a quick answer. That answer may not be good, let alone good enough. It often likes to flatter you, was built by humans with human biases and blind spots, and will feed your delusions if you let it.
9. Leading
Are you using AI to replace connection and communication? Or augment and expand it?
The human part of leadership is the hard part. Each time a new technology comes out we try to use it to replace the more difficult side of leading – the emotional side, and the tough conversations.
Some of the generative AI tools and agents can be great to help you prepare and practice for tough conversations.
But if you’re sending an AI notetaker to a meeting, it’s worth questioning how important that meeting actually is, and what signal you’re sending.
If you don’t need to be in the meeting, design it so that your presence or lack thereof isn’t hindering progress. If you’re sending notetakers to meetings, consider whether you are doing so to avoid making decisions about real priorities—and whether the meeting needs to happen at all. Not every meeting is a yes, even if it appears to come at a relatively small cost in the moment.
Not only are these red flags that often indicate poor governance, role clarity, strategic clarity, and organizational design – but a missed opportunity to build connection points and relationships with real humans that have the potential to make the rest of the work easier for you (or more difficult given your lack of connection).
10. Living
If you can do it, does that mean you should do it?
With most advancements come tradeoffs and unintended consequences. Not all can be predicted, but many can with a bit of thought, scenario planning, and reflection.
This means taking the time to think about those tradeoffs and second- or third-order consequences that should be considered if we care at all about what happens in the long-term – in our lives and in our world. As one example, AI data centers have required an incredible amount of water at a time where water usage is becoming of greater concern.
In More Than Words: How to Think About Writing in the Age of AI, John Werner argues that writing is a tool for thinking, learning, and feeling – all critical for understanding who we are, what we really believe, and how we move about the world.
In Managing the Gray: Five Timeless Questions for Resolving Your Toughest Problems at Work, three of the five questions Joseph Badaracco presents involve understanding your very human self and making very human judgements that defy perfect, linear reasoning.
In a time where technology is moving quickly, bringing the whole of your human self to your life and your business is perhaps one of the greatest roles you could play – at work and in the world at large. As my friend, top global futurist, and future-of-work extraordinaire Diana David says in her newest TEDx, YOU are the missing piece in the AI revolution. No matter what seat you sit in.
Lean into and grow your ability to wrestle with more complex problems, to unlearn and relearn, and to grapple with more complex feelings and identities. This is where we as humans shine, if we so choose.
To being fully human,
Amanda