I Have a Future in Mind.I Want to Show You.

I have been thinking a lot about artificial intelligence lately.

Not necessarily because of what it can do today, but because of what it could mean for us tomorrow.

Like a lot of people, I've found myself going down some pretty interesting rabbit holes. How does AI actually learn? How does it recognize patterns? What happens when intelligent systems begin communicating with one another? Could artificial intelligence eventually develop awareness?

And what happens if we build something capable of making decisions faster than we can fully understand the consequences?

Those are fascinating questions. Some are unsettling.

But somewhere in the middle of exploring all of this, my thoughts started going in another direction.

I started thinking about how humans learn.

How we're conditioned.

How our environments influence the way we think, behave, and experience the world.

And how much of what we consider normal is really just the result of systems someone designed long before we had the ability to imagine something different.

Then I started connecting those thoughts to education, employment, development, infrastructure, agriculture, energy, water, and the economy.

I know. That's quite a jump.

But that's generally how my brain works.

I see something in one industry and immediately start wondering what it means for another. One question leads to five more. Eventually, connections begin forming between things that initially appear to have absolutely nothing to do with each other.

And somewhere in all those connections, I started seeing a future I hadn't really considered before.

What if artificial intelligence gives us an opportunity to rethink not just how we work, but how we build the world around us?

Not to create a world controlled by technology.

To create one where technology helps us become more capable, more curious, and perhaps even a little more free.

I want to show you what I mean.

First, let me explain why I see things this way.

I've spent much of my career studying people.

I started in hospitality, where understanding the consumer wasn't some abstract exercise.

You had to understand why people traveled, what they valued, what made them comfortable, what frustrated them, and what made them choose one experience over another.

Eventually, my work expanded into brand strategy, development, and understanding how consumer behavior influences larger business and investment decisions.

And one thing became increasingly clear.

You can build something extraordinary on paper that makes absolutely no sense for the people expected to use it.

A beautiful hotel that doesn't understand its guest.

A destination designed around an investor's vision without understanding the surrounding community.

A retail concept that looks impressive but completely misses what its customer actually values.

A development that makes financial sense independently but creates problems for the infrastructure and communities surrounding it.

I've watched how decisions made early in a project influence everything that happens afterward.

That's why I have become far more interested in what happens before something gets built than what happens after.

But I also see the world through another lens.

I'm a mother.

I understand what it's like to raise children who don't all experience the world or learn in the same way.

I understand the parent trying to manage school, work, appointments, responsibilities, and everything else life throws at them.

I understand the desire to build something meaningful while still wanting time to enjoy the life you're working so hard to create.

And I understand what it feels like when traditional systems don't necessarily recognize someone's abilities.

Those experiences have shaped how I think about people.

I don't believe we're all meant to process information the same way.

I don't believe productivity should be confused with sitting at a desk for eight hours.

And I certainly don't believe the most intelligent person in the room is always the one with the most credentials.

But many of our institutions were built around standardization.

We ask children to learn within relatively fixed structures.

We ask employees to demonstrate productivity through predefined roles and expectations.

We develop communities through separate planning, financing, infrastructure, and regulatory processes.

Then we wonder why so many people struggle within those systems.

I'm not suggesting all standardization is bad. We need structure, accountability, and consistency.

I'm asking whether we're willing to reconsider which limitations are actually necessary.

Because sometimes the problem isn't the person trying to function within the system. Sometimes the system itself needs to evolve.

Now imagine the year is 2040.

I don't want you to picture flying cars or robots walking around your neighborhood.

I want you to picture something much more ordinary.

A Tuesday morning.

Your home.

Your children.

Your job.

Your community.

The kind of life most of us are living right now.

Except we've made some different decisions about how technology fits into it.

7:30 AMYour child goes to school.

Imagine a little boy who is incredibly intelligent but struggles in a traditional classroom.

He asks a million questions.

His attention moves quickly between subjects.

He learns things almost effortlessly when he's interested, but struggles to retain information presented in ways that don't engage him.

Maybe he has ADHD.

Maybe he simply learns differently.

For years, his parents have watched him become frustrated trying to fit within an educational structure that doesn't always recognize what he's capable of.

Now imagine something different.

His teacher has access to AI tools that help identify which instructional approaches work best for him.

Instead of spending hours memorizing information from a textbook, he's learning about ecosystems by exploring a creek.

He asks why certain plants grow near water.

The technology helps his teacher turn that curiosity into lessons about biology, chemistry, environmental science, and mathematics.

Suddenly, subjects that seemed unrelated become connected through something he's genuinely interested in.

He's not spending his entire day interacting with technology.

He's spending more time interacting with the world.

His teacher is still teaching. His classmates are still learning together. He still has responsibilities and challenges.

But the learning experience has become more adaptable.

And perhaps most importantly, he begins developing confidence in his own abilities.

What if we used artificial intelligence to help children become more curious about the real world instead of creating another reason for them to stare at a screen?

This isn't simply wishful thinking.

The OECD's Digital Education Outlook 2026 identifies potential benefits from AI-supported personalized learning, while also warning that using AI to complete assignments can improve immediate performance without producing lasting learning.

In other words, helping a child finish their work isn't necessarily the same as helping them learn.

That distinction matters.

Because the future of education shouldn't be measured only by how quickly students complete assignments.

It should also be measured by what they understand, what they retain, and whether we're developing people who know how to think for themselves.

9:00 AMYou go to work.

Let's say you're a parent working full-time.

You spend your day moving between meetings, emails, administrative responsibilities, and the actual work you're supposed to accomplish.

By the time you're finished, there's dinner, homework, laundry, and everything else waiting at home.

But because technology allows us to remain connected constantly, work doesn't always end when we leave.

Now imagine AI eliminates several hours of unnecessary administrative work each week.

Meetings become shorter.

Reports take minutes instead of hours.

Information moves between departments without someone manually transferring it.

Problems are identified earlier.

You're able to spend more time doing the work that actually requires your judgment, creativity, and experience.

That part is becoming increasingly realistic.

In a 2025 National Bureau of Economic Research field experiment involving 7,137 knowledge workers across 66 companies, workers who used an integrated generative AI tool spent approximately two fewer hours per week on email during the latter half of the experiment. They also reduced time spent working outside regular hours.

That's meaningful.

But here's where my mind immediately goes.

Who gets those two hours?

Does the company increase its expectations?

Does the employee receive additional responsibilities?

Does the business reduce its operating costs?

Or does that parent actually get to leave work earlier?

Maybe they make it to their child's baseball game.

Maybe they finally take that afternoon horseback riding.

Maybe they have time to start something they've wanted to learn for years.

Or maybe they simply sit outside and enjoy an evening without feeling like they should be doing something productive.

I don't think every hour we recover needs to become another opportunity to work.

And I don't believe the measure of human progress should be how much more we can squeeze into every day.

What if increased productivity meant we could accomplish what matters in less time, instead of being expected to accomplish more in the same amount of time?

That's not a technological decision.

That's a business decision.

And it's one we need to be discussing before organizations redesign their operations around AI.

12:00 PMYou finally have time to be curious.

This is one of the possibilities I find most exciting.

What happens when people have more freedom to explore things outside their professions?

Imagine a mother who has always wanted to learn architecture.

She doesn't necessarily want another degree or a new career.

She's simply curious.

Now she has access to tools that can help her understand structural design, materials, engineering principles, and architectural history in ways that previously might have required years of specialized education.

She can ask questions.

Build models.

Explore ideas.

Learn at her own pace.

Perhaps that curiosity eventually becomes a business.

Perhaps it doesn't.

Maybe it simply becomes something that brings her joy.

I've always been someone who follows my curiosity across different industries.

One day I might be studying Western consumer behavior.

The next I'm trying to understand the economics of a real estate development.

Then I'm researching materials for my own home, questioning why certain products are distributed the way they are, or connecting something I noticed in retail to an opportunity in hospitality.

Those interests don't always have an immediate commercial purpose.

But interestingly enough, they often connect later.

And I wonder how much human potential goes unexplored because people don't have the time, resources, or confidence to follow their curiosity.

What if AI made learning more accessible without making the experience of discovery any less human?

I think there's an extraordinary opportunity there.

Not simply to produce a more skilled workforce.

But to create a world where more people have the freedom to discover what interests them.

Now let's look beyond the individual.

Because this is where my thinking really started expanding.

Imagine a developer wants to build a new community.

Traditionally, they might evaluate available land, construction costs, financing, market demand, zoning, and projected returns.

All essential considerations.

But what about the systems that make the community possible?

Water.

Electricity.

Transportation.

Agriculture.

Food distribution.

Healthcare.

Education.

Employment.

Environmental resources.

Government services.

And yes, the cultural and spiritual needs that contribute to people's sense of belonging and purpose.

Every one of these systems influences the others.

Yet we frequently evaluate them through separate industries, institutions, budgets, and areas of expertise.

A developer may understand the financial model.

An engineer understands the infrastructure.

An agricultural specialist understands the land.

An energy specialist understands power generation.

A water specialist understands supply and demand.

An economist understands financial constraints.

A community understands what it's like to actually live there.

All of those perspectives matter.

But who is responsible for connecting them before the major decisions are made?

There are organizations and specialists already doing interdisciplinary systems research and integrated planning.

The challenge is ensuring those perspectives inform decisions early enough to change what gets built.

That's where I believe increasingly capable AI could become incredibly valuable.

Not because it should replace those experts.

But because it could help them identify relationships, dependencies, and competing priorities that are difficult to evaluate independently.

Let me give you an example.

Imagine we're considering a major development in an agricultural region.

The land is available.

The capital is interested.

The development could create jobs.

But the region has limited water resources.

That immediately raises questions beyond traditional real estate development.

How much water does the proposed project require?

What does that mean for existing agriculture?

Could alternative infrastructure reduce demand?

What energy would that infrastructure require?

Could improvements to the energy system support other businesses?

What happens to operating costs?

Could the project create opportunities that benefit the surrounding community?

And what happens if we decide not to build it?

Suddenly, we're not just evaluating whether a project is financially feasible.

We're examining the constraints and levers that determine what is possible.

One investment might solve several problems.

Or it might create five new ones.

The purpose of connecting intelligence across industries isn't to eliminate those trade-offs.

It's to understand them before we've committed so much capital that changing direction becomes nearly impossible.

I believe some of the most consequential opportunities of the next several decades will come from recognizing connections between systems we've historically treated as separate.

And that's the part of this future that fascinates me.

But there's another future we need to consider.

I want you to imagine the same family, the same city, and the same level of artificial intelligence.

Except this time, nearly every decision is made around maximizing efficiency.

The child's school uses AI to measure performance, but the learning experience becomes increasingly automated and impersonal.

The parent's employer saves hours through automation but simply increases output expectations.

The community becomes more technologically advanced, but residents have less influence over decisions that affect them.

The city can collect more information than ever before, yet its services remain fragmented.

Everything is connected digitally.

But people feel increasingly disconnected from life.

Now ask yourself something.

Is that progress?

It might be according to certain financial or operational measurements.

But is it progress for the people living there?

I think this is one of the most important questions we need to address as artificial intelligence becomes more deeply integrated into society.

And the public's concerns are real.

A 2025 Pew Research Center survey found that 50% of American adults were more concerned than excited about AI's growing presence in daily life.

Yet 73% said they would be willing to let AI assist with at least some everyday activities.

And 61% wanted greater control over how AI was used in their lives.

I find that combination particularly interesting.

People appear willing to consider the benefits while remaining concerned about what they might lose.

That should tell us something.

The consumer isn't necessarily asking us to stop developing technology. They're asking us to consider what that technology means for their lives.

And I think we need to listen.

The people making these decisions need to understand more than the technology.

Imagine sitting in a room where a company is deciding how to deploy artificial intelligence across its operations.

The engineers understand what's technically possible.

The financial team understands the expected return.

The operations team understands the efficiencies.

The legal team understands the risks.

All of that expertise is essential.

But I want to know who's asking about the people.

Not just whether they'll adopt the technology.

Whether it actually improves their experience.

Whether it makes their lives easier or simply creates different responsibilities.

Whether it strengthens human capabilities or gradually replaces opportunities to develop them.

Whether it gives people greater independence or makes them more dependent on systems they don't understand.

And whether a decision that makes sense for one company could create unintended consequences across several other industries.

I don't believe these questions should be an afterthought.

Consumer intelligence needs to be part of the conversation before major decisions are made, not simply used afterward to convince people to adopt what's already been built.

And by consumer intelligence, I don't mean tracking every behavior or using increasingly sophisticated algorithms to manipulate people.

I mean understanding what people actually value.

The things they say.

The things they don't always know how to articulate.

The frustrations they've learned to accept.

The experiences they wish they could have.

And the difference between what a company believes someone wants and what that person is really trying to accomplish.

I've spent years working to understand those distinctions.

Sometimes the greatest opportunity isn't giving consumers more of what they're already buying.

It's recognizing the need that existing products and systems haven't adequately addressed.

I believe that same thinking belongs in conversations about artificial intelligence, infrastructure, education, development, and the future of our communities.

Not instead of technical expertise.

Alongside it.

So where do we go from here?

I don't think we need another person promising that AI will solve humanity's problems.

And I certainly don't think we should give artificial intelligence the authority to decide what a good life looks like.

Human beings have different values, beliefs, ambitions, and ideas about how they want to live.

Those differences deserve to be protected.

What I am interested in is something more practical.

What if we used artificial intelligence to better understand the constraints, dependencies, and opportunities across the systems we're already building?

What if researchers in water, energy, agriculture, transportation, education, capital, government, development, and environmental science could examine their findings together?

What if we could model how a decision in one industry might affect another before committing billions of dollars?

What if we could identify which constraints, once addressed, could unlock entirely new opportunities?

What if our decisions were informed not only by what was financially or technologically feasible, but by a deeper understanding of the people who would live with the results?

And what if we could actually demonstrate those possibilities instead of simply talking about them?

That last part matters to me.

I've never been particularly interested in asking people to believe in an idea just because it sounds compelling.

I want to show them.

Show them the child who discovers a different way to learn.

The parent who gets more time with their family.

The small business owner who finally has time to create.

The developer who discovers a better opportunity because someone identified a constraint they hadn't considered.

The community that makes a more informed investment because its water, energy, transportation, economic, and environmental systems were evaluated together.

Then measure the outcomes.

What improved?

What didn't?

What did we overlook?

What could we do differently next time?

That's how a vision becomes something useful.

Not by assuming we know what the future should look like.

By exploring what becomes possible when we ask better questions.

I have a future in mind.

I want to be clear about something.

I am not an artificial intelligence engineer.

I am not claiming to understand every scientific or technological challenge ahead of us.

And I don't believe one person should be responsible for deciding humanity's future.

But I do understand people.

I understand the mother trying to hold everything together.

The father working to provide for his family while wondering where all his time went.

The child whose mind doesn't necessarily work like everyone else's.

The entrepreneur who started a business to create freedom and somehow ended up with less of it.

The everyday person who doesn't need to understand how artificial intelligence works to understand how it might affect their life.

And I understand something else.

The most important decisions are often made long before the people affected by them ever realize there was a decision to be made.

That's what concerns me.

Not simply how intelligent AI might become.

But whether we're thinking broadly enough about what we're building alongside it.

Because I don't think the opportunity is just to make humans more productive.

I think it's to help us become more capable without sacrificing the experiences that make life worth living.

More time with our families.

More opportunities to learn.

More freedom to pursue our curiosity.

More opportunities to create, explore, and build.

More thoughtful use of our natural resources.

Better-connected communities.

And systems that recognize the value of different ways of thinking.

I don't expect that future to happen automatically.

I think it will require researchers, engineers, scientists, developers, investors, policymakers, and people who understand human behavior working together in ways they haven't always done before.

It will require challenging assumptions.

Understanding constraints.

Recognizing opportunities.

Making difficult trade-offs.

And accepting that the most efficient solution isn't always the best one.

We have spent generations building increasingly sophisticated systems to support human civilization.

Now we have an opportunity to understand how those systems connect at a level that was previously difficult to imagine.

I believe what we choose to do with that capability could influence the next chapter of human development.

And I think ordinary people deserve to understand what's possible, because they're the ones who will live in the world we're creating.

The greatest achievement of artificial intelligence shouldn't simply be how much more we can produce.

It should be what that increased capability makes possible for humanity.

I have a future in mind.

One where technology supports human intelligence rather than diminishing it.

Where progress is measured by more than productivity.

Where we become better at understanding the consequences of what we build.

And where being more technologically advanced doesn't require us to become less connected to the world around us.

I want to show you that future.

Because whether we want it or not, the next frontier is already here.

How do you want it shaped?