Hey, did you know that only 4% of Americans ride public transportation?

But surveys show that 84% of communities where it is support it.

I'm Paul Comfort, and on this episode of Transit Unplugged, we dive into

that number to try to explain why.

To help U.S. find that answer, we talk to Mark Aesch.

Mark is CEO of TransPro Consulting, and in this episode he makes a powerful

case that public transit should not be evaluated only on ridership, but

also about its value to the community.

He explains how that shifting our focus from volume or ridership to value

better reflects what people actually want from their transit systems.

And we're joined by Alvin McBorrough.

He's CEO of OGx consulting, and he explores how transit agencies can harness

the power of artificial intelligence or AI to make better decisions and

better serve their communities.

It's a powerful conversation you don't wanna miss on today's

episode of Transit Unplugged with Mark Ash and Alvin McBorough

Enjoy.

Great to be with two of my friends, who are some of the best public transportation

consultants in America, in my opinion.

And that is Mark Ash, who is the head of Trans Pro Consulting.

Mark, welcome to the show.

Great to be on.

Thanks for, uh, making time.

and my good friend Alvin Mc Burrow.

Who is CEO of OGx Consulting.

Alvin welcome.

Thank you, sir. I appreciate it.

As you know, normally we talk to transit executives and uh, once in a while we

bring in people who I think can really help the industry from the private sector.

And that's what this show is all about.

mark and I, recently did a co-presentation.

I. At the invitation of, Scott who heads up CTAA, Scott Borin,

in San Diego at CTAA Expo.

mark and I have been friends for over a decade.

I even had talked with him when I was CEO of the MTA in Baltimore.

But hearing Mark talk about this.

Topic of modernizing value for public transportation and making sure we're

emphasizing the right things for success.

It's all a game of expectations.

And what is it?

That just spoke to me so much.

I said, mark, we gotta get this message out to a broader crowd.

So I'm really happy to have you do that.

And Alvin and I have been talking off and on for the last year or so about the role

of ai, artificial intelligence, and public transportation and how, you know, we feel

like a lot of transit agencies could do a lot more, with less if they utilized.

AI even better.

so I said that's another, message that I don't get a chance to talk

to CEOs about because Mark, really CEOs of transit agencies and you

were one, in Rochester, New York.

You know, they're tied to the existing paradigm, right?

So talk to U.S. some about, your background.

Mark.

Let's start off with you and then just give U.S. an intro to this topic.

Yeah, happy to.

So, I, uh, went to college Paul a hundred years ago, uh, to study

being in the TV news business, and did that for about 18 months.

and quickly learned that the only thing people in the TV news business

do is talk about what someone else did.

And I'm like, I wanna be the one that's doing the doing.

Like I wanna be the one that they're talking about.

That they're producing different sets of results.

And I. Believe that the transit agency that I was the CEO of for eight

years, we did things very differently.

we pushed ourselves to ask very different questions.

We thought about the differences of words, like what's the difference

between customer service, which is an input and customer satisfaction did I

actually deliver the service in the right way to lead to a satisfied customer?

People are quick to use the words, oh, we need to measure our employee satisfaction.

Well do we mean employee satisfaction or do we mean employee engagement?

Do we want the hearts and minds engaged, you know, to produce maximum value?

So to your point, all of that, led to a lot of national news coverage.

I wound up writing a book, with a publishing wing of Walt Disney, and

it was a logical jumping off point.

I loved the work that we were doing, but it became all right SmartyAnts,

like you could do that with one agency.

Can you scale it?

could you begin to work with a number of like-minded, passionate executives

to bring measurable performance to their agencies and proud?

We're celebrating our 15th, year of doing that to work with public sector executives

that care deeply about their results.

That's excellent.

Thank you so much, mark.

I look forward to unpacking that even more in the next few moments.

Alvin, let's move over to you.

You're based out of Denver, right?

Give U.S. a little bit of your background and what you all do.

I.

So I'm, particularly on the opposite side of Mark.

Started off not necessarily in tv, but pretty much working as a technologist.

So prior to starting OGx consulting, uh, used to be with Cisco Systems,

primarily on the services side, where we will come into organizations primarily

come in with the understanding that, look, there were challenges that most.

Clients were faced with mostly C-level executives looking to scale their entire

network or their entire solution platform.

So, as being part of Cisco services, uh, were tasked with going in,

trying to understand what the pain point was, creating some economic

value for these stakeholders, and trying to help them skill and

deliver that pla particular platform.

So from the onset, one of the big things that I would like to

say that we were part of earlier.

This was the early onset of what we call at the time, infrastructure

as a service, which has now become what we call cloud computing.

That's what everybody's referring to now.

at the onset, Cisco was at the, um, virgining stage of setting that

whole industry up, and we were some of the pioneers at that early stage

to be able to get this moving.

So somewhere along the line, I decided that that was just the right

time to be able to make the pivot.

And focus on building something for myself.

And this was when I was finishing up my MBA at the University of Chicago.

So that's when I decided to make the pivot and just go directly into consulting.

And hence we've come into this space, that we love so much, especially the

public transit, where we see a ton of opportunities for U.S. to be able to,

leverage some of the words of Mark.

Help our clients elevate their performance and also move them to the

next level of how they can leverage, technology, leverage strategy,

leverage management philosophy, and how we can help them propel,

themselves to the front of the line.

And they're doing a whole lot more with less at this particular point in time.

Something that we often talk about Paul.

Thank you so much.

The next round of questions will be, you know, tell U.S.

more about how AI is being used or could be used.

We'll talk about that in just a few moments.

Lemme swing back to Mark.

you and I, as I said, met when I was at MTA in Baltimore, which was, uh, about

10 years ago, eight to 10 years ago.

And, One of the first things I told the staff when I had a, a big staff

meeting, MTA Baltimore is the 11th largest transit system in America.

We had 5,000 employees and contractors and a lot of senior management.

So I gathered all the senior management together because I came in as a

change agent, not a cheerleader.

And uh, I told them, you know, I'm not here to make friends.

I'm here to make a difference.

And, I don't care about ridership.

One of the first things I said to the team as a whole, I said, ridership is actually

the one thing that we can't control.

What we can focus on are other inputs such as safety, efficiency,

reliability, we called it back then customer service, world class,

customer service, Disney style.

Uh, I know you've got it even refined, even further.

Tell me what you think about that and what are we getting wrong in the industry?

Well, there's a reason, Paul, that you and I are friends 10 years later because

we were, one of the few that were singing out of the, uh, the hymnal, 10 years ago

that ridership, was a flawed concept.

the fundamental point of it is, that if ridership is the singular definition

of success, we're not very good at it.

I mean, ridership has been in a steady decline for 75 years.

And the reality is if you correlate ridership against one

metric, it's very, very clear.

If you go back decades, there's a singular metric that ties to public

transportation ridership, and that is.

The price of a gallon of gas, something that we have no involvement in.

And so we're tying the success of our industry to a metric that has

no involvement with U.S. whatsoever.

And so, you know, the point that I make is that if we're going to tie

our success to two questions, number one, what is our ridership level?

And second, what is our revenue level?

How much public money can we get, you know, put into our

hands to deliver service?

We don't control our own destiny.

And so I have been, quite loudly leading a conversation of how do

we move the definition of success from one of volume to one of value.

And I will never understand and I'll continue to lead the conversation that.

If serving more bad coffee is the definition of success, that's not

a diner that I wanna work, right?

I mean, how, how do we serve amazing coffee like they do in San Antonio?

Highest customer satisfaction in the country?

How do we serve amazing coffee?

So people wanna invest in U.S. to open more coffee shops.

Toledo, Ohio is a great example.

They embraced, a model of measuring value.

The voters passed overwhelmingly providing them with more resources

to open more coffee shops.

And so I think we have example after example of agencies that have

moved from the volume mindset to the measurable value mindset, not episodic

storytelling, measurable value.

Uh, critically, and I'll put a, I'll put a bow on all this Paul, to, to wrap.

We have some national results that we've been tracking for two

years now across the country.

4% of people in most communities use the public transportation system, but

across the country in most communities, 84% find value in their public

transportation system 20 times more.

And so that 84%, right, they don't care if we move 4.1 or 4.2, like they don't care.

They want U.S. to bring measurable value.

And how do we talk to that 84%

. Alvin, that's a perfect segue into what we're gonna talk about next,

which is how do we bring value?

How can we use technology?

I mean, I work for a technology company.

That's our message every day.

If you use technology effectively, you can help improve the lives

of the people you're serving.

How are we using ai, , you know, we're all just fooling around the edges with chat.

GPT, how can transit systems use it to do what Mark is saying,

which is provide prove value?

Oh, so absolutely there are a ton of opportunities that when you look

at artificial intelligence or what we would call AI, for instance,

is having transformational impact on public transportation sector.

especially from around when you look at operational and safety improvements all

the way to rider experience and long-term planning, there are a ton of opportunities

that we see across the board.

for instance, having been on the periphery of playing in this space.

For a couple of years now.

We started off with it not being called ai, but you know, at one point

in time it was predictive analytics data, all of those other things.

But coming up to where we are right now, leveraging artificial

intelligence and also machine learning, the way I usually like to

look at it is in the bucket of four.

Perspective.

The first one is around the passenger experience, The next one will be

around operational, efficiency.

The third one is going to be around safety and security, and the final one is just

gonna be around planning and policy.

So within this construct, it's easy for U.S. to take passenger

experience, for instance.

So asking the question about how a public transportation agency

can take advantage of that.

for instance, if we look at real time, estimate time to arrival and

alerts and all of these other things.

Now there are some examples in, in the place, which I will certainly go

into later on, uh, to be able to talk about the examples on how these other

agencies are leveraging this now.

People are now leveraging that to be able to be something that can help

them predict, if there is supposed to be a delayed, if there is supposed

to be on time arrival, how are they getting to that next level?

When you look at chatbot for instance, that's another big area

again, where we've seen, a lot of agencies begin to leverage that.

This one again, is basically helping the passengers help to plan them around the

trips, answering the frequently asked questions, and also reporting on issues.

If there is something that is there and I need to know, there is an alert,

how can we easily get this one out?

So on the passenger side, those are opportunities.

On the operational side, as we've known for a long time, predictive maintenance

has been one of these key things that has really hampered a lot of public

transportation agencies, but most of them are now moving to this space

where they're now beginning to predict.

Primarily now calling that ai, leveraging some AI algorithms that can easily

predict if there is a machine or critical component within the system

that's supposed to fail, when is the most likely time that will break?

What kind of impact we can have on that, how your organization can

easily get ready to be able to help.

Prevent some of these things from happening.

can also look at route optimization as another area again, where, when

you look at traffic and you look at ridership, how do we combine that data?

How can we help better optimize route?

Let's assume that a road is closed.

What is the best step again for U.S. to optimize our route?

How can we alert our clients or our stakeholders, passengers,

for instance, of early onset?

Then when you look at it from the security perspective, again, there

is a great example again that I would like to share and I think this is a

client of ours that is doing something like this with especially computer

visioning, especially around surveillance.

So that's another area again, how you can easily leverage computer visioning.

To be able to surveil and how you can easily alert your stakeholders

of any, if there's anything of concern that is in this space.

then from there you can just also talk about planning.

now artificial intelligence is giving U.S.

the opportunity to.

And the capability for U.S. to be able to plan well in advance,

especially if we start looking at demand forecasting, for instance.

I know Mark mentioned about the fact that we want to be able to forecast how many

passengers we'll see along these lines.

What are some of the things that we can look at it when it comes to ridership

growth incidents that we can identify, and how we can easily help, propel our

transit agencies to help prepare for them.

That's another great area.

Again, we'll be seeing a lot.

The final one that I would like to do on as part of planning would just be

around the digital twin, for instance, and this one again, is about leveraging

simulation for U.S. to help plan and project on future policies if there

are supposed to be opportunities there.

If the impact here, let's assume that the impact from the FTA, we

realize that there will be a little bit more less funding this year,

so what is that impact going to be?

How can we leverage the digital twin to be able to plan and prepare for that as well?

So there are a ton of things that AI can possibly do, and I believe that this is

the right time that public transit agency should seriously consider artificial

intelligence as one of those tools or one of those, emerging technologies

as we'll call it, that will be able to help propel them to the front of the

line if they want to continue to be su sustainable and focusing on the right

things that they need to be doing as well.

. What do you think of that Mark?

The role of ai?

it's fascinating to think about, you know, Paul, you and I are old

enough that I think I've been through three generations of listening to

the industry, indicate that we have to quote unquote tell our story.

And you know, to the point that I was making just a minute ago, that

over here you've got 4% right?

In most communities that use over here, you've got.

84% that find value in the public transportation system.

And the reality is we don't need to tell our story.

We need to tell their story.

Right?

Mm-hmm.

That the 84% who live over here, what would a politician do with that?

Right?

A politician would pull the community and they would talk not to the

4%, they would talk to the 84%.

Mm-hmm.

And I think to the point that Alvin's making, right, so that the 84% are

very clear on why they see value.

They're very clear on why it's 84%.

Number one, public transportation connects people to jobs.

Yeah.

We should talk about connecting people to jobs.

Number two, we, provide service for people that are elderly and disabled.

Mm-hmm.

So maybe rather than complaining about the a DA as an unfunded mandate, yeah.

Maybe we embrace that as an opportunity.

Meet you, brother, because there's 84% over here.

Right.

We talk to them.

And the third reason that 84% is over here is that they believe that

we provide low income people with connectivity to jobs and education.

And so.

I think the opportunity is not to talk about quote unquote choice riders, but

to actually talk about that third element of value, which is how we connect people

of lower income households to jobs.

Let's be proud of that, not ashamed of it, and have, choice Rider conversations.

So I think the point vin's making about ai.

Is how do we talk to the 84% and the three reasons they find value

rather than this endless pursuit of how do we get 4% to be 4.1%?

That's not how the 84% thinks about the value of public transportation.

They don't care if it's 4.1 or 4.2.

They care about jobs, helping people that are old and disabled and connecting

people of lower incomes to work.

Let's use AI to have their conversation, not tell our story.

What do you think Alvin?

Yeah, just to beck on what Mark is saying is that, if you

recall, we had the Pato principle.

You know, uh, right.

20% of the outcomes that where we're, it's, to drive 80% of what we're looking

for comes from, you know, 20% of the activities or 20% of the stakeholders

that we need to be able to focus on.

So again, leveraging, this particular platform that's we, we

we've come to embrace pretty well.

I know most people see it through the lens of, the first thing is chat, GPT

or one of these other things of those nature that I'm using tropics, I'm using

Google and all of these other elements.

But I think it's, if we look at it holistically, I think one of the

industries that is U.S. sectors that we can focus on at this point,

that is well prepared for U.S.

to be able to move into.

the next level, is the public transit space because it gives

U.S. that opportunity now for now considering all of the challenges

that we're confronted with, right.

Some of them, yes.

It's been systemic, it's been historical.

Others has just been, you know, the recent activities, with regards to

changes in, Directions, that you can see.

So one of the areas here is that how can we, and this is something

that we've been advising a lot of, folks to take advantage of, you

know, is that how can you focus on.

Leveraging, the request for you to do more with less, right?

So that's one area.

So if I've been asked to do something like that, and you can go down the

road and start considering the fact that, okay, if we want to be able to

route our passenger experience, for instance, what are some of the things

that we gotta start thinking about?

How can we make certain that we can easily drive?

Our pasture experience to get U.S. to the next level.

So along that line, that's something again that you start looking at the

data that we currently have in-house.

can we make sense of it?

How can we assemble the data?

How can we go out there and make sure that we can take a logical

approach on how we can, help implement AI across the entire industry.

Right Mark.

Um, one of the best books I've read, I think in the last 10 years is the book

Freakonomics, which really talks about follow the money, follow the incentives.

One of the things, the lessons I learned out of it as a younger

man was, you know, realtors and whose interest do they really have?

You know, the realtor who's representing the seller is not

there to represent you as the buyer.

Uh, and so you and I are in alignment on the important things that we need

to value the three priorities of people, the 84%, and that we need

to be speaking to that as a transit agency leader just like a politician

would, to win support votes, et cetera.

How do we incentivize those results?

Yeah, it's, it's a great question.

I thought the book was phenomenal as well, and I, I, the realtor

example sticks with me.

Paul, I'm surprised to know you.

I are aligned.

So to me, I think there's three elements of reform.

You and I talked about this first one, right?

So we've gotta modernize the definition of value.

This, ridership and revenue mindset is not gonna set the industry up, you know,

for sustainable success in the future.

I think the second one, which is the question you're asking here.

Is, how do we as an industry inspire the Federal Transit Administration

to move from a compliance mindset to a performance mindset?

So let me give an example of what I think that means.

You will have the FTA, you know, ask you 27 times a year if you've

got happy buses, They'll ask you about state of good repair.

They'll ask you about mean distance between failures.

But you know what?

They won't ask you.

Do your happy buses actually create happy customers, right?

Like there's this overfocus on, did you fill out all the forms properly?

Did you use the number two pencil?

Are you creating happy buses versus are you creating happy customers?

And I'm very optimistic, that Congressman Molinaro is really going to lead a reform,

not incremental, lead a reform of the FTA.

To begin to think about outcomes versus input.

So what do I mean by that?

So this concept of, you know, how long do you keep a bus and mean distance

between failures and state of good repair?

How do we move from whether my bus is on time or not, to whether

or not I've got happy customers?

Let get a specific example.

Years ago at New York City Transit, all they could talk about in

meetings was on time performance.

What's our on time performance?

How are we performing?

What's our on time performance?

You know, where the customer rated on time, performance,

and level of their happiness.

Seven, it was the seventh most important thing.

So even if they became amazing at it and got to a hundred percent, the

impact on the outcome of customer satisfaction was gonna be incremental.

So.

I'll pick a realtime example in Trim Map.

two weeks ago, trim was recognized for having the most improved

customer satisfaction in the country.

Their customer sat in Portland, went up 15% in one year.

The best part of it, it went up on purpose, like they

actually worked on the right.

Inputs in the right order to drive the outcome they desired

of higher customer satisfaction.

And so that recognition comes from really being able to think about those things.

Let me make two points, Paul, which I think are critically important in this

in regards to the incentives that you're talking about from this reform minded FTA.

The first is.

Agencies receive federal aid in regards to quote unquote unlinked passenger trips.

So what does that mean?

Unlinked passenger trips.

That means if I can make you transfer, I get to count you twice, and if you have to

transfer coming home, I've now moved the same person four times, so my incentive.

As an agency to get more money is to cause you to be unsatisfied.

I'm gonna make you transfer multiple times.

If we took a plane, you could go straight from Baltimore to Tampa.

You're like, I'm in.

If you gotta stop in Atlanta, you're like, like what am I doing that for?

We are incentivized to get more federal money to make people transfer.

We actually did the analysis on this.

You guys will find this amazing, a family of three.

That uses public transportation to go to and from work, run their

errands, junior goes to high school, goes to practice afterwards.

The FTA would tell you that family of three.

Is 58,000 customers during the course of the year.

It's a family of three, right?

Mm-hmm.

So how do we begin to create so that the metrics are, tied to that?

The second one there's a disconnect between the FTA funding and

the way we provide, service is this concept of revenue miles.

So agencies get federal aid based upon revenue, miles,

drive more miles, get more aid.

What that leads to is a. Fundamental disconnect between supply and demand.

So over the last 10 years, industry-wide demand is down 28%.

Mm-hmm.

Supply is down 1% because agencies are incentivized to run revenue

miles as opposed to think about efficiency and value to the community.

So I'm very hopeful that Congressman Molinaro is gonna lead a discussion

of how do we move from these?

Input metrics that are incentivizing agencies to think about happy buses

as opposed to incentivize them to think about happy customers

and value to their community.

. For those of you who don't know, uh, Congressman Mark Molinaro

is the FTA, the Federal Transit Administration, administrator nominee,

and he's passed the Senate Banking Committee on a bipartisan vote.

And as of the time of this recording in early July, he still was set up

for a vote, but my understanding is Mark, he's a special employee now, kind

of working in there somewhat anyway.

Yeah, I have exactly that same counsel and I, I'm optimistic based on,

watching the congressman's work when he was a county executive Oh, right.

Dutchess County, New York.

Right.

Very performance focused, very outcomes focused.

And, and I think as an industry to be able to have, someone at the head of

the FTA to really think about these questions from a non-traditional

mindset and really think about how do we bring maximum value to the 4%.

And maximum value to the 84% that find value.

I think the industry is gonna find a friend in, uh, the former congressman.

Thank you, Alvin.

As we wrap things up, give U.S. uh, a little more, on just what Mark was

talking about is how, how we can use AI.

To help U.S. tell that story, how we can take artificial intelligence, pull

together the reams of data that are coming into a transit agency all the time,

and maximize the messaging, to the 84%.

How can we use AI to tell our story better?

So, Paul, it is interesting that, we just had this conversation and Mark raised

the whole thing around performance.

So one of the key areas here is primarily.

From the standpoint that, you know, AI is data driven, so whatever inputs we

have will become that particular piece that we can expect to get out of there.

So, based on that, I think that as we continue to go down this path and as we

continue to think about it, AI would just be that in enabler that we can definitely

leverage to, for U.S. now to become.

A little bit more data reach.

I mean, in our environment we're pretty much data reach, but, literally see,

uh, we have, uh, the ability not to be able to execute on the data that we

currently have at this particular point.

So with U.S. in, adopting and embracing the whole tech, concept or technology,

uh, that we're embarking upon, uh, with ai, I would say that it gives

U.S. that ability for U.S. now.

To position our agencies in a whole better light because now we have the

data for to, for U.S. to be able to up our actions, especially if that's the

new direction that we're hoping to get to where we become more performance,

we get pretty much incent for the performance that we're able to deliver.

I think it's critical for U.S. to be able to embrace it.

So once again, going over some of the key areas that we've seen opportunities

emerge around, like operational, you know, excellence or operational improvement and

efficiency, leveraging AI in that space.

One of the key areas will begin to look at, will be predictive maintenance.

So again, we know that we have, most public transit entities, we've been

asked to be able to address the issue with MAP 21, the FAST Act, and how we

can easily help optimize our assets.

So if we're leveraging AI, that can help U.S.

In the process of predicting when a machine is supposed to fill, when

a pot is supposed to go down, how soon can we replace that?

I think that there will be enough incentive for U.S. to be able to leverage

that data to help position U.S. and we can prepare for that particular one.

Another area, again, that we gotta also look at will be

around passenger improvement.

So Is there a way that we can enhance the passenger experience

when they're riding our buses or our multiple modes of transit?

And if the answer is yes, how can we from the onset, is there a logical way that

we can provide them with the relevant space for them to be able to interact?

With our agencies, even through chatbot for instance, if they can

easily ask these frequently asked questions, when would my bus be here?

How soon do I have to wait?

When is the next?

Connecting all of these things.

If it's on time, we believe that that will be able to enhance the E

experience again for our passengers.

And that becomes another opportunity again for them to say that they want

to be able to participate and get more on the public transportation route.

For them to be able to do that.

then safety again is another big area.

And if that's another issue, again, if we're leveraging things like

the computer vision, for instance, leveraging the data from there for U.S.

to be able to prepare not only just for the, uh, passenger experience,

but from a safety perspective, that we can easily leverage some things along

artificial intelligence that can help prevent incidents from happening to.

Our passengers, that we can minimize those.

I think it becomes another great area again, and also just from a planning

perspective . That's another place that I will say that even from a policy and

planning perspective, that's another area.

, If we start focusing on, it helps U.S. to be able to, with the relevant

data that we currently have, we can now focus on the future demand.

We can forecast our current needs and how we can better prepare for long and

short-term planning With respect to that, because we have the relevant data.

That is helping go to guide U.S. to the next level for how these, decision

makers within, public transit will be able to make the relevant, decisions

at that particular point in time.

You know, Paul, just a quick comment on that if I can.

I would argue to the point that Alvin's making that as an industry,

you know, we are data rich.

And information poor.

Mm-hmm.

Mm-hmm.

And I think the question is how do we take all of that data and

use it to arrive at the top line?

So let me use a an example to illustrate that, you don't measure whether Tom Brady,

you know, threw a number of touchdown passes or was able to run the ball really

fast, or how much weight he can lift, or did he eat the right nutrition, did

he score enough points to win on Sunday?

Like that's the measurement of success.

Yeah, and we can move as Alvin's suggesting from this data rich

environment to actually thinking about information and results.

The fact that we require a transit agency in Montana and Manhattan to

measure the same things is silly.

And how do we make sure we measure what matters?

To bring value to the communities that we represent.

Sacramento is going to think about outcomes different than Syracuse is.

So if they're going to think about outcomes in a different way, guess what?

They're going to measure things in a different way to produce those outcomes.

Are you a running offense?

Do you pass the ball?

Do you run a, uh, you know the option?

And so we have to allow agencies to have individuality in what they

measure to produce outcomes and begin to tie federal aid to be in good.

And what you committed to being good at, right?

Like everyone's gonna think about value in a different fashion.

. Well, thank you both.

Mark Ash, Al mc, thank you for sharing some of your insights

with U.S. that are actionable.

I think for transit agencies, the idea that.

Ridership cannot and should not be, the primary indicator of our success because

it's not necessarily what's valued by the majority of the people in a community.

That's what I'm hearing from you, mark and Alvin.

What I'm hearing from you is we can use artificial intelligence.

More than we are now in transit agencies to produce better outcomes

for the communities that we serve.

I think those messages tie together so well.

Thank you both for the work you do.

If you wanna hear more from Mark or Alvin, we'll put their contact

information, their websites on our show notes, and you can reach out to

them directly if you'd like, any input from them on your specific agency.

Thank you both again for being here for the work you're doing for our industry.

Thank you, Paul.

Paul,

great to see you, Alvin.

Thank you, mark.

Have a good day.

Thanks for listening to Transit Unplugged.

I'm executive producer Julie Gates, and this episode was created by host

and producer Paul Comfort, producer Chris O'Keefe, associate producer Cindy

Raskin and podcast intern Des Gates.

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