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Digital Transformation Architect is the canonical architecture podcast for leaders who need transformation decisions to last.
Hosted by Dr. Darren Pulsipher, the show applies the Open Digital Transformation Architecture (ODXA) to help organizations navigate digital change across people, process, and technology. Each episode focuses on architectural thinking—examining tradeoffs, dependencies, governance, and long-term impacts—so listeners can move beyond trends and tools toward durable outcomes.
Whether you’re a CIO, enterprise architect, policymaker, or transformation leader, Digital Transformation Architect provides a structured, domain-driven approach to designing transformation that aligns strategy, operations, and technology at scale.
And generative AI has really showed
its it that digital transformation,
which is the core foundation,
is problematic for a lot of companies.
MIT just came out
with, a study that showed that
95% of generative
AI initiatives are failing
Welcome to Digital Transformation
Architect architecting
the future of digital transformation.
I'm Doctor
Darren in this podcast is for leaders
navigating the real world
complexity of modern change.
Each week,
we cut through the hype to explore
how strategy, architecture, technology
and people come together across
artificial intelligence, cybersecurity,
data edge and modern infrastructure.
This isn't about chasing tools.
It's about designing systems that endure.
Let's get started.
Hey, it's Doctor Darren here.
I'm glad to introduce you
to a brand new podcast,
primarily focusing on digital
transformation architecture.
And I'm having a lot of fun
putting this together.
We are going to talk about
digital transformation and architecture.
Over, the next couple of years,
I guess, with, a lot of great things
happening, the open
digital transformation architecture
is coming out in July this year.
Keep our fingers crossed
that new standard is coming out.
But today we're going to talk about
why digital transformation keeps failing.
And we're seeing this time
and time again.
And generative AI has really showed
its it that digital transformation,
which is the core foundation,
is problematic for a lot of companies.
MIT just came out
with, a study that showed that
95% of generative
AI initiatives are failing
and why I think I know why.
We've done a lot of research in this space
and is all about digital transformation.
It's all about architecture.
But before we do that, let's find out.
What do we mean by digital transformation?
It's it's this nebulous thing
that we hear all the time.
I have some ideas on on what?
I think, digital transformation is,
I hopefully you agree with me
here, but to me,
digital transformation is sustained.
Organizational change.
It's not just a one time
technology adoption.
And I think that's,
one of the biggest problems
that people are having
is they don't understand that.
They think, oh, if I,
if I just adopt this, one technology,
then I'm done with my digital digital
transformation.
That's not true.
It's organizational,
sustained organizational change.
It's about how an organization operates,
their decision making, their coordination,
their incentives, their governance.
All of this has has a play.
In fact, I've seen time and time again
people ago with technology
first on their digital transformation.
Typically always fails.
I haven't seen very, very,
very few, successes with the technology.
First play I was talking about this
and on my interview podcast,
Embracing Digital Transformation.
My tagline is Leveraging People, process,
policy and technology
for Effective change.
We've
seen this in the research
that, we've done
we've totally seen how people
and the roles and skills
in their behavior, the processes,
the way that we work together,
the policies which are the rules,
the incentives, the regulations
that we, have to sit in sometimes,
and the technology,
how those four have to align in order
for me to have effective change.
And it has to be,
it doesn't happen organically.
It has to be thought out.
It has to be architected.
And that's why we name this podcast
the Digital Transformation Architect,
because I truly believe
that you have to architect these changes.
And they can't just be technology
architecture.
They are full blown
enterprise architecture.
And that's kind of,
the direction that we're heading and,
and why I have this podcast
and this podcast is all about learning,
and in this area
and taking some of the learnings
that I've had in sharing
with, with everyone.
There are great,
examples of digital transformation,
that have failed
some that I perpetuated myself.
Probably one of my biggest failures out.
I'm sure you want to hear
about my failures, right?
One of my biggest
failures was when I was a CIO
and we were deploying a brand new, system
that was for our business owners.
We I, I was part of a multi-level
marketing company.
I was their CIO, and the business owners
are basically our customers, right.
That are coming in, buying our product
and then selling our product.
Right.
So distributors for for no better work.
And we had a system
that was kind of glued together
and it was all put into place there.
You know,
it was actually it was actually barely
holding on every day.
So I got my architect hands on.
I said, all right,
we're going to architect a new system.
I brought in vendors
and we did a technology play.
First.
We did not touch the people.
We did not train people up on it,
including our distributors.
We did not, change our processes.
We tried to fit the processes, that
we already had into this, new technology.
And we didn't have any policies in place.
The minute that we deployed,
the minute that we deployed, it failed
miserably.
Miserably failed.
We had a DDoS attack
that happened at the same time
our our customers,
our distributors were outraged.
It was a total disaster. Why?
When I go back and I look at it,
I did not involve the four dimensions
of digital transformation
people, process, policy and technology.
I did technology play wholeheartedly.
Technology play, total disaster.
We had to roll it
back, to to the old system.
And then gradually over time,
we were able to to make the change
when we better understood the dynamics of,
the people
and the processes
that were involved in the policy,
the regulations that we had to fit in
so hard.
Oh, that was a hard lesson to learn.
There are lots of other examples
that we're seeing out there,
especially when we talk about
generative AI.
Generative AI, we're finding that
there's a lot of what I call
science projects that are going on.
And these science projects
are really interesting, right?
People are doing kind of these one offs.
I do a lot of these,
small, proof of concepts.
And, it's really interesting
because I can get it to run on my laptop.
I can get it to run on my server.
But when I try to take it
to the enterprise, it falls apart.
And that's what we're seeing with
a lot of generative AI, solutions today.
They work in very isolated areas.
And, and the reason
why we're seeing that is
because, I'm not looking at things
holistically and systemically.
I'm doing
like point solutions here and there.
And when I start putting
in into full systems
and I start looking at the process around,
the processes
that I'm changing, the processes
I need to fit into, things
start falling, on the ground.
And this is a big problem
for the adoption of generative AI.
A lot of, companies are dumping,
billions, trillions of dollars.
If you look at the industries
overall, trillions of dollars
are being spent with no ROI yet.
And I truly believe one of the reasons
why is we're all in the POC phase,
and we're not taking a holistic
or systemic architectural approach
approach to this.
And, and we've seen this before.
And the good news is,
is it'll come around, but it takes time.
We saw this with the adoption
of ERP, enterprise resource planning
systems, systems.
All of the great,
benefits of using an ERP.
And we're not seeing the ROI as quickly
as we had hoped and as quickly as we were,
were wanting it to happen.
Same thing with cloud technology.
It took a while and then we moved
and we did like lift and shift
disaster costs too high.
We had to change our processes.
We did change these things.
So there's a lot that was
that are going on.
Examples of this is a persistent problem.
We've had this problem
for for a long time,
but we don't seem to figure out
the best approach to to make digital
transformation really happen.
We do get some wins periodically,
some great wins periodic.
And it happens quickly.
The adoption of email, for example,
and how that change process
has changed a lot of things.
It was
we took something
that we already understood really well,
and that was era office memos,
and we mimicked it.
And we had technology mimic a process
so the processes didn't have to change
right away.
We kind of grew into new processes
that that change.
So there's a lot of, really interesting,
things that happened there.
But these recurring failure patterns
that we're seeing,
we had to look at these, and,
and I spent some time on my PhD
dissertation, which was on the convergence
of OT operational technology,
and it, cybersecurity best practices
was all about digital transformation.
And the results
that I got out of those impediments.
What was causing the problems of
these are not coming together
like they really should write,
for best practices.
You would think that they would.
But there was friction there.
It wasn't happening.
And what we found was in that, research,
I seen the same thing in other research
as well, in other industries.
And in other situations.
And the number one thing that we're seeing
here is the misalignment
between intent and execution
across those four dimensions,
people, process, policy and technology.
Right.
What we found is
you'll have enterprise architects
that will go out there and,
they'll talk to the business owners
and they have their strategy all captured.
And then they
then they architect the processes,
but they don't align sometimes.
So this alignment in the day to day
decision making is not aligned
to the strategy,
to the processes, to the technology.
And now we start having problems.
So what organizations tend to do is
they tend to put governance on top of this
and say, you will do these things,
but the governance ends up being siloed.
Either by department or location
or function.
And we've seen this, time and time again,
we tend to see that,
functions are localized
to individual departments
and, or have functional groups
in those departments. So
because they're siloed and
because they're localized,
a lot of times we miss
and we start creating
not just functional silos but data silos.
There's
a whole bunch of interesting things.
And the reason why is because locally,
the team is locally going
to optimize without coherence
to the rest of the system.
I do this myself.
I'm totally guilty of this.
If I want to get something done,
I get it done
without regard
to how it fits into the overall system.
Right?
It could be as simple as,
hey, how am I going to enter in,
customer information in my CRM system?
Maybe I have some techniques I developed
myself that I could do really quickly.
I may share it
with a couple other people in my, group,
but I'm not looking at systemically.
How could we resolve this
problem across across the board?
So we have that.
We have those types of issues.
Other teams
tend to succeed in isolation really well,
but once I try and move that
to the enterprise level,
it tends to have issues
with that because,
the, the culture,
the group, there's a lot of tacit
knowledge problems there.
It's it's hard to get that in,
in a full blown enterprise.
So we got to come up with ways
of doing that.
Another problem that we see is outcomes
tend to decay over time,
especially if they're ignored.
If said I did, this is one time it worked.
I'm just going to keep doing that
and there's no continual improvement.
Then they tend to decay.
Their benefits tend to decay over time.
This is another major issue.
Things are moving
very quickly as well in the industry.
It is very rare in large enterprises
that you have people
that stick around
for 4 or 5 years or longer,
and sometimes these digital
transformations can take years to happen.
So what happens is these people leave
and that that progress
that you made in the cultural change
aspect start going away as well.
And new people get hired in and,
you know, things change, processes change.
Policies may stick there,
but no one's adhering to them anymore.
So this is a big problem, especially with
generative AI thrown into the mix.
The biggest problem we have
with generative AI thrown into the mix
is it's moving, very rapidly.
The capabilities, the, risks are there.
They're very, very fast.
And organizations
can't keep up with that speed
because of all, all of these issues.
And this is this is why we really need
an approach for digital transformation.
Because things are moving
so quickly, we're going to be left behind,
or even worse, we're going to degrade,
substantially.
Right.
And we're that's
why we're seeing small startups that are
being able to take down some mid-size
and even large companies
that normally have some large barriers
to entry into those markets.
We're seeing small companies
being agile and moving
because they can adopt
these new technologies quickly,
because they're building from scratch,
they're building new,
and they don't have any of that
inertia organization.
Warner. So that they have to overcome.
So moving
forward, this is a really exciting time.
We're going to find, you know, through
these lectures which happen every week.
Check them out weekly on Digital
transformation Architect,
where we're going to explore
some of the techniques that we can use
to look at digital transformation
holistically
across five domains of the open
digital transformation architecture.
Coming out of the open group.
Now, the five domains are strategic,
organizational process,
digital and physical domains.
And we're going to
look at how we can, leverage
and use those five domains
coordinated together
into a developing a holistic enterprise
architecture solution,
and build out
those digital transformation roadmaps
so I can move an organization
into the future.
You've been listening
to Digital Transformation Architect.
If today's discussion helped
you see your challenges more clearly,
the next step is to apply architecture,
not just technology.
For deeper conversations
with leaders and practitioners
for real change, listen to Embracing
Digital Transformation.
Or check out our website
embracing digital.org.
Until next time,
architect the future with intent.