Welcome to the APM podcast. APM is the chartered body for
the project profession. My name is Emma De Vita and I'm
the editor of Project at OPM's Quarterly Journal.
And your Host and this podcast. I'm speaking to three project
professionals with a deep interest in artificial
intelligence to consider what impact this technology is having
right now on projects, what it might hold for the future, and
what project managers should be doing to adapt to this brave new
world. I'm delighted to have with me
today Professor Antonio Nieto Rodriguez, Founder of the
Strategy Implementation Institute and author of the
Harvard Business Review Project Management Handbook, James
Garner, Global Head of Data and Intelligence at Gleed and Chair
of the Project Data Analytics Task Force and Martin Paver, CEO
of Consultancy Projecting Success.
The Autumn 2023 issue of APM's Project Journal also covers this
topic, so please do make sure you grab a copy.
Welcome everyone. I just wanted to thank you for
joining me today. I'm really looking forward to
our discussion on AI and its impacts on the world of
projects. I think a good place to start
would be for each of you to just tell us a little bit about
yourself and what fuels your interest in AI, or even better,
what gets you excited about it. So, Sherrie, begin with you,
Antonio. Well, myself, I'm, I'm, I'm
coming more from the PMI world. I was the chairman of PMI a few
years ago I launched the Brightline initiative.
My my goal is always to close the gap between the senior
leaders, the business, the strategies and projects and
project management. So I'm a practitioner as well.
I'm I'm part of a big sustainability transformation in
a corporate in the pharma sector, but also an academic.
I like to research. I publish.
I published several books, one of them with Harvard Business
Review, which has been my my goal because that's the way to
switch the people mindset around projects and project management
to appreciate it. And what drives me on a I what
makes me excited is something that is in my mind, it's around
delivering more value. I think there's very few
professions that are challenged about their success rates.
If you look any research around project management, 60 to 70% of
the project fails and and you can challenge that but that's
not acceptable. So we're we're wasting value
money impact and I think AI is a unique opportunity to close that
gap to say OK, out of 10 projects we deliver 8
successfully and we are here like a.
Some some that we we can bring value fast for, for
organisation. So that's for me the biggest,
biggest driver on ICE, increased success rate of this profession
that we love so much. OK.
Thank you and Martin. So in terms of me personally,
I've been a project professional for about 30 years, so I'm a
fellow of the APM and back in about 2014, fifteen I started to
look into things like lessons learned.
I pulled together about 20,000 lessons learned and from that I
realised that we're not learning from those lessons, we're just
repeating the same things time and time again.
So what I try to do is to apply advanced data analytics to that
and I realised that it's the wrong journey.
So we're not collecting the right evidence at the moment.
So we can start to use those techniques and really start to
drive it. So back in 2017 and then set up
the project data analytics community that's grown to over
10,000 people and I start to run hackathons, et cetera.
So for me personally, I see this is the way of leveraging that
vast experience that we've got as professionals that it's all
codified in data. So back to Antonio's part about,
you know, we're not doing good enough at the moment as a
profession. We could do a lot better.
It's for me, data is right at the heart of that.
So I don't see this as a tweak. I see it as a transformation.
It's a completely different way of thinking.
How about you, James? Where does your interest in AI
stem from? Eastern I've been interested in
from the very beginning of my my journey Even back at university
I was looking at sort of digitization in the construction
industry back in sort of 2000 or even before then with this
overwhelming kind of needs to to understand that there must be a
better way of doing things. That's really where it comes
from. Comparing ourselves to other
industries and thinking, you know, the way we do these things
just inherently seems so inefficient and a lot of that
was because of the very nature of the industry.
But the as Antonio races, we have this unique opportunity
right now in that the the technology has kind of finally
caught up with our aspirations in terms of what we can do.
And we we need to grasp it So we'll talk about it I'm sure
later in the podcast this kind of balance between the
opportunities and the risks and and we've got this very very
small window of opportunity to make this a I work for the
profession rather than for for other interested parties.
I guess my other kind of inspiration is other people have
inspired me and you know Martin was one of the people who really
put me on this journey and really inspired me to to follow
this follow my passion. I I I come from a QS background.
You know, there's so many people in this field who are really
passionate about this that there's there's great hope for
the future. We can all sort of come.
Given to to make it work for the better of the profession,
there's been a lot of hype around AI should really be
listening to the people are saying this is the end of
humanity and no one's gonna have a job or should we be feeling
excited about it. Probably like to put that to you
too, Antonio first. The question of whether it's a
hype or not, I don't think so. It's a reality and people like
Martin has been working on this space way before many people
started to even think about it. So I think it's not a hype, it's
a reality. It's happening.
And I think in the profession we have not embraced very quickly
new disruptions. We kind of always very cautious.
We we talk about change, but we're not quick at adapting to
change. And this is an opportunity where
we can drive, we can embrace these changes.
The fact that there will be parts of our work that are
automated, it's a blessing for I think for anyone that wants to
develop. More executive kind of career.
If you want to stick to your spreadsheets and your dashboards
and and just chasing people. Yeah, your job is at stake for
sure because you are not adding very much value.
I don't know. I've been working in PMO's
project management for 25 years. I can't wait to automate all the
the the 50% of our work that we do and PMO it's 80%.
So bring it tomorrow and and let's embrace it, right and and
let's start focusing on on where we can bring more value, which
is that alignment, stakeholder engagement, team kind of
engagement and commitment where I think that's what in the end
what Martin? Was saying we know why projects
fail. I hate when people ask me what
you need to do for a project to be successful.
We know that it's everybody knows that people even that
don't know projects know why projects fail.
So we have an opportunity to use technology and AI to get those
things out of the way and focus on those important matters which
I cannot solve, which is the cultural aspect, the
organisational aspects, the leadership aspects.
So there will be change definitely in the skills that we
need to build up, but I see it as a huge opportunity, exciting
time for for our profession. Is there anything that concerns
you that needs to be thought about and dealt with and planned
for right now? I think there's concerns of
course, but they're really far off.
I think the project management profession, these are there's
something bad around, yeah, we cannot influence this.
I think what concerns me is that we don't take action.
And when I see chaps, GDP and some other of these AI early
developments, I questioned the role of the project manager.
I could see self-driving projects if we don't step up.
So I think it's more the concerns is more that the
profession and the can be extremely disrupted that
somebody else can start doing our job because they've embraced
AI. So that is the immediate.
Is that how can we move fast so that we take that spot, which is
the integration of product managers, agile project
management, change management, which if we don't step up,
somebody else will do very quickly.
And that's what worries me. The bigger picture of course,
but I just don't know these fears.
I'm very far off. Entirely agree.
I mean, and the question about hype, I mean the Garden, the
height cycle refers to where we are, this peak of inflated
expectations right now, thinking it's going to, you know, change
everything. And then you go through what's
called the through of disillusionment and that there
will be this kind of period coming up where ohh OK, it
didn't totally change the world, but that doesn't mean the hype
is not there. And actually we will go on this
journey towards what's called a jive.
It's artificial general intelligence and some people
think it's 30 years away, some people think it's 100 years
away, but we will get there eventually.
So we're on the journey. Towards that reality.
So it's not hyper in that sense, but sometimes I think maybe
people think where the technology is right now and they
get disappointed when it can't do these incredible things at
this moment in time that some people predicting that there
shouldn't lose faith. You know that it's only a matter
of time it keeps improving the the improvement is huge.
But I agree with what Antonio says in terms of and this goes
back to what we said at the introduction, You know, we have
this opportunity and if we don't carve this technology for
ourselves and make it work. Of ourselves and control the
data, then we risk giving it away or given away control of
our industry to other people and other third parties who may not
have the best interests of the industry at heart.
And that's why we're, I think three of us are pushing so hard
to say, look, this isn't something to be afraid of.
Yes, the hype is something that is going to change your
workflows. It's going to change the way you
do think. But embrace it, because the
other option is we start giving away control slowly but surely
to third parties. Which third parties are you
talking about? It effectively third party
vendors or software companies. So it it it could be small
startups, it could be the big giants, you know the Googles,
the Amazons, the Autodesk. In this world, you know you can
see a future very clearly if we don't intervene and and protect
our industry where we we slowly but surely have that kind of
Netflix moment. I suppose is the best way of
describing it where, you know before we know it clients are
paying subscription something and not using project
professionals. OK, Thanks Martin.
What are your thoughts? Love to hear what you think
about all of this. So it's back to that point
really about, you know, is this an an apocalypse, You know is it
going to be the end of the world?
And I think we've got separate out, you know, what's the impact
of this on future wars and all that sort of stuff.
Like that's an issue for the state.
It's not something I can control as a project professional.
So I bring it back to project delivery.
Is this an existential threat to our profession?
And personally I think it is. If we don't respond to this,
others will. And these data people start to
come into our jobs and start to automate a lot of it.
So it's a case of moving ourselves up the value chain,
and it's not just. Artificial intelligence.
So something I like to say is if you can describe something in
logic, you can probably code it. So if you can code it using
Python And various other tools, then you can do that fairly
simplistically and fairly cheaply.
A lot of that is available today that just put it into Microsoft
XLS well. So you can now code in Python as
part of Excel. If it's more intuition based
than what you need to do is to grow the data set so you can
look at the patterns in the data so you can extract some of that
intuition. And that's when it starts to get
a bit magical, right? And that's when we start to get
some really cool insights coming out of it.
If we layer on top of that, things like the large language
models, so it's not just ChatGPT, there's larger and
various other ones out there. So what we can do now we can
take a model that's being, say, trained on English and then
teach it to speak with a Yorkshire accent.
But it's that sort of approach. So what we're doing at the
moment. So I've got a call tomorrow with
Adrian Dooley who created the practise framework.
So instead of having a body of knowledge or a book, it's now
online. So Adrian's taking it all
online, There's templates and there's various collateral on
there if we can now train a model on all of that.
And then train it on all of the National Audit Office reports,
the GAO reports in the US etcetera, We start to get a
large language model that is trained on project delivery.
So it becomes very project delivery.
Nuance, we're going to have that in about two or three weeks
time. So that's going to be available
and it's all going to be open source.
We can open source it for people.
So just imagine if we push that further and further and further,
if you can now start to train it on data, on schedules of risks,
on compensation events, on technical queries.
That's when it becomes even better.
It's starting to predict where we're going to end up, right?
So it's not just about forecasting envelopes.
It's now starting to say to me, what is my call to action?
And people who don't understand this stuff will get replaced by
the people who do understand this stuff.
So if you've got a choice of two project professionals, one
person who really understands this and can leverage it and can
make the most out of it and get better at making decisions and
somebody who doesn't, which person would you choose?
Which? Which person's going to get
promoted? I think that's the issue for the
profession. How do we share knowledge?
How do we share this experience? How do how do we learn from the
first movers if we're not one ourselves?
And also, I'll be really pleased if any of you want to just talk
about a couple of practical examples of how AI is being used
in the world of projects today so that we can move away from
the kind of theory and the hype. So, Antonio.
Yeah, I think the sharing is great, but somehow we say I to
me it feels that there's a bit more strategic advantage.
So why should I share something where I'm using an AI tool with
my competitions, they can adapt it and do better.
So yeah, I was talking earlier with the podcast in Australia
and we were talking about the PPM market as well.
We which we know and we collaborate with some of these
big players that have been there for. 20 years, But discussing
that, you can see that they're they're struggling to adopt AI
and there's one big big player which is Microsoft whose open AI
and has charged BT who might just take everything away in
some niche players around. But for me the the sharing of
AI, there's still the issue of IP and whether they can use all
the information for free or not, but that's a bigger kind of
discussion. We don't know where it's going,
but for me using AI. Can be a strategic tool.
It's not like we're using Excel or we're using Microsoft
Project. No, no, there's much more
intelligence that you can use it to to do your projects better,
faster more successfully. So I don't have an answer it's
just thinking in my head of can you share or should keep it bit
more confidential to make it a competitive edge right.
So that is in the the point I wanted to to share in terms of.
Some parts, I think in my article with Ricardo Vargas, we
talk about Walmart using AI for managing their supply chains and
data analytics to manage the demand and the streamlining.
Another example, I think we talk about Siemens that they've
implemented system to streamline manufacturing process.
This is already well known general electrics applications
on AI and project management in the energy sector.
So there are already. Companies that are using pieces
of Asia to some extent. So I I would not replicate what
is in the in the article which you published in the APM
magazine. So, but yeah, I think there is
more and more and I recommend people to just follow some of
these newsletters around and I because it's just amazing how
quickly it changes. Martin, any practical examples
you want to talk about or how we can learn from each other?
I personally see we've got choices to make here.
So we can either compete around this artificial intelligence or
can work together and to accelerate.
If we work together, we started to pool our data.
We start to sort of open source some of these solutions.
Now in terms of the solutions, a lot of them aren't actually
intellectual property. It's more about configuration of
Python libraries or it's a configuration of Microsoft tool
or a low code app or something like that.
So what we've been doing, so this is for the past five years
or so. So we've been running these
hackathons, so the last one in Manchester City Football Stadium
and we had about 230 people come along to it.
So we Co create solutions to shared problems.
So we're then open source and James can tell you about some of
the solutions because he's been pulling them through into gleeds
as well. It's now part of his product
portfolio. So those are all the scenes of
ideas that people can now fork and take in a different
direction. So if we do that, we're learning
on the fly, we're learning from each other.
We're starting to accelerate. So I'll give you an example.
Instead of 100 people all working on a health and safety
app, because every company wants a health and safety app, if we
just develop one or two of these health and safety apps and then
share them, it means we can do the other 98 things individually
as well. So we go 100 times quicker.
And I think that's the difference is that we shouldn't
be competing. On some of these low value sort
of aspects of data-driven project delivery, which should
be worth together, get us to the data volumes, get us the data
quality as well. And that's one of the biggest
issues at the moment. So artificial intelligence needs
lots of data, needs good quality data.
We'll never get to that point unless we work together on
things like the data model, the ontology about how this data all
fits together and it's not flat data.
You can't just look at things like cost data by itself, the
cost data and the work package and the.
Now is it a Greenfield or brownfield site?
All these other things, they become the features in this
artificial intelligence model and then we can look at the
correlation between those features and that drives the
artificial intelligence engine basically.
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projects succeed, society benefits James.
Any practical examples of AI that you've that have inspired
you or you would like to share with listeners?
Before I talk about some examples, I think Antonio picked
a really important point around this.
Some people think that AI or data more generally some kind of
competitive advantage. And I think what I'm trying to
do is challenge that to say that actually we're not in
competition with each other as consultants or or contractors or
whatever we are. We're actually in competition,
like I said with the big tech company.
So we we got to change our thinking and innovate ourselves
above that. There's enough to go around,
there's enough projects to go around and if we can use AI.
As a way of improving project delivery, it will clients
effectively less reason to start looking for moving, moving to
vendors. The other bit before I go into
some practical examples is is around the messaging and how we
get this out there. Now I think all three of us
probably say that's probably the hardest bit, because you can,
you could, you could have every single project professional in a
room and you could tell them about this, but it would still
sometimes not necessarily go over people's heads because
people are people intelligent. To understand it, I think
there's a there's a fear people have different motivations for
not wanting to pick up AI. Some of it is fear, some of it
is ohh, it's, you know, it's not gonna affect my profession, it's
not gonna affect what I'm doing. My bit is somehow unique from
everything else, so it's not going to affect that.
That's where I think the skills need to come in and sort of
upskilling people. And Martin does a lot of that
with his various data academies. We also do training to upskill
people and we've been working with the APM on the positive
dramatics deals guide document. So you know some of the examples
of things we've done is like training our own large language
models. So for years, one of the things
that we do in Leeds is published market reports about what's
happening in the project world and those have been issued as
traditional reports. We've actually trained a large
language model, ChatGPT basically of our market report
so that clients don't have to interact and read reports, they
can literally just talk to these reports.
That's a very simple example. We've been also using it to sort
of track material prices and what's happening in the market,
how kind of micro level almost in a daily so we can see what
trends are happening, you know even within a week or so prices,
steel or prices of labour in a certain region.
And that all of that is just giving people the tools so they
can become more efficient. Antonio, in the article you
wrote for us you you covered off some of the challenges and how
to overcome them when it comes to AI and and projects.
One might want to pick up on is the lack of skilled personnel.
So if you're speaking to individuals right now, what
advice would you give to them about adapting themselves to
this new reality? Yeah, that's something.
Again, one of these topics where there's no black or white
answer, I say things are moving really fast.
It's more like a mindset of continuous learning and trying.
I think you learn technology by trying, not by just listening.
And I think this is something that maybe we don't dedicate
enough time. But for me, it's about getting
involved in some of the work that both James and Martin are
doing, and and others and and and get connected with the
people who are in that. Breach of of this AI and and and
project management but also trying.
I think first of all everybody should have used already ChatGPT
or or bar to see what we have. What are the risks in in
projects like mine any like knowledge management you go to
chat and you can ask what kind of projects that in this sector
we've seen in the past and what are the key learnings you get
that immediately So that curiosity to experiment with the
tools I think it's. Is more important than saying
you need to develop the kind of design thinking or critical
thinking which is a bit more abstract.
We are not going to be developers for sure, but I think
that kind of constant checking and trying and new tools and see
how can make me better. How can I see that this
technology will help me to get to deliver value better.
I think that's where I I would put my focus.
That's what I'm doing. Of course, going through AI
courses. And and learning.
And I think one point. I did a survey with Ricardo
about this. Area is great, but don't forget
that AI is an enabler. So don't forget about if you're
working on sustainability, diversity, growth that should be
connected to. So don't just one thing, but see
how this connects to other bigger topics that are priority
in organisations that will make you even more special and
unique. So connecting AI with all these
other topics, I think something that I would recommend to do as
well, but the most important is try.
Don't be afraid just you said turn you'll get mistakes, you'd
struggle. But this is the best way to
embrace new technologies and and most of the softwares you have
the most uh that you can just watch and think about how do
they could benefit your your projects.
But I cannot give you one specific skill.
I think there's so many skills that we need to develop.
Thinking more strategically about one's career, should you
be thinking about the very human side of work?
So when it comes to decision making, So if all the AI
eventually is going to give you all the information you need and
flag up the risk areas of a project or suggest ways that
seems to be become better, what does that leave the project
manager needing to do? So if you're thinking five years
ahead of or 10 years ahead, what is it about the project
manager's role that will change from now until?
Kind of short term future, what should you be cultivating or
developing in within yourself to ensure that you?
Still going to be necessary and needed in a five years time.
In the skills, for me it's it's what we talk about is soft
skills, but in on a higher level is that alignment between
different groups of priorities and projects and critical
thinking of strategic thinking. These are things that a I will
for sure not do very soon. So engaging on stakeholders,
talking about the value of your projects, learning to speak the
language of the organisation, connecting with the right
people. I think this is where we should
have done that before anyway, because these are essential
skills. But now AI is going to make that
more obvious that if you want to have a job in this space in five
years, you need to develop that really acceleration there.
Because it's about also following empower, feeling the
confident, feeling confident to talk to our CEO of your company.
This kind of mindset we've never heard and it's the moment to
step up. And I always say it's more of a
mindset. Issue then the skills and the
mindset says you're in power to do these things to deliver your
project benefits and this is something that is built based on
confidence on on looking another examples and and trying this
kind of new new approaches to to delivering projects.
I think if there's something I would recommend it's the
mindset. Feel empowered to drive your
project. You're the owner.
You should be able to say let's stop it.
You should be able to go to the CEO, say I need.
Resources or this is not going to happen unless that in that.
So that's something that I always push in in conferences
and workshops. Martin, what are your thoughts
around this? So how project professionals
should be thinking about upskilling themselves or any
advice you'd pass on? So basically we saw this back in
2017 and the first point was about just awareness.
So that's why we set up the project data into its community
and that's why we start the meet ups.
We ran monthly meet ups and then pre COVID we were going to
Birmingham and we're going to Bristol and Manchester up to
Aberdeen as well and start to spread the word and share these
experiences as well. So we get guest speakers in.
So a chat came and talked about the Tour de France and he played
it back through a lens, which was brilliant, right, Really,
really brilliant. So what we then start to do is
to run these hackathons. Because it gave people some
practical experience and it took away some of the barriers.
It's not as scary if someone sat next to you and showing you what
to do and showing in two days what can be done.
So we run that and then people said to us that's not enough.
We need some practical experience.
You know, we need to be shown how to do it.
So we then started training, so we run the Project Data
Analytics Academy, So that's funded through the government's
Apprenticeship training levy. So it's basically free for most
organisations and that enables people to get up skills in data.
Even project delivery for nothing and a byproduct of that
process is each person has to do three or four projects as part
of the course. So there's no exams anymore.
It's all about your portfolio that that you develop.
If we do that, we start to develop this collateral then.
So we start to develop these little modules of capability,
these Lego bricks that we can all start to piece together.
And just imagine if you had 1000 people with three or four
projects seats, that's 4000 Lego pieces of capability.
If we start to pull along that like won't put it on cause some
of it will be commercially sensitive and et cetera.
But if we could pull half of it, we will transform the industry.
So that training is available now, so finders on
projectingsuccess.co.uk and look at the training page as well.
So it's all in there and it's funded by government.
So government is trying to help you to get these skills so you
can remain. At competitive and we start to
drive up UK PLC productivity. So back to one children's point,
you know what will project managers do in the future.
And for me there is a phase shift that's coming, a massive
phase shift as in spite of as spending loads of time, you know
looking backwards through reporting, doing assurance
etcetera, a load of that it's just going to be automated.
That doesn't need artificial intelligence, it just need needs
code and some of these sort of modules of capability that we
can develop through things like Power Automate and and Power BI
and that sort of stuff, right. So that's fairly easy to do, and
it's all accessible today. Well, this is 10 years away.
It's all available today. So what we then start to do as
project managers or project professionals, we start to say
where do I need to focus my laser beam so I can deliver
these projects more cost effectively and with greater
delivery confidence. So if you look at HS2 at the
moment, is it the politicians fault that it may get turned off
from Birmingham up to Manchester?
So is that a political decision or is it a case that IT cost
growth is so extreme is it's no longer investable?
So is that a project delivery issue?
Right. I think the jury is out on that
argument. But if projects are becoming an
investable once they get to a certain size, then that's a
massive issue for society and we can help to solve that through
advanced data analytics. So we start to understand which
parts of a project are predictable and which ones
aren't and why and what we need to do to sense that and and to
understand it. So the role of a project
delivery professional is going to evolve at pace.
So it's all about the superpowers.
Of individuals. So if you can see what's in the
future, you can predict where something's going to go wrong,
you will outperform your peers. And if you really, really good
at it and you're going to get paid a lot of money because you
can save the country and absolute fortune, you can save
your employees of fortune. The problem with this is, so
I've been posting a lot of things on LinkedIn at the moment
and people have said we need to take everybody on this journey
with us. So let's not scare the horses.
And let's not put out there that you know there's going to be
various people losing their jobs and plugged into this as I see a
lot of the time about all of this sort of efficiency
improvement and productivity improvement through project
delivery and some organisations will just cash that productivity
improvement in. So it will be heads, it'll be
headcount loss. It's the more visionary
organisations will transfer those people and start to move
them up the value chain. So they've got these superpowers
and they can deliver projects a lot more cost effectively.
So for me it's not necessarily about taking everyone with us
because they'll always be sceptics, It's about taking the
five or 10% who's really going to start to accelerate this,
this journey. We're going to pull a load of
other people along with them in their wake because we'll start
to develop the evidence and we'll start to demonstrate this.
That pace. Any last thoughts before we
finish? We run out of time already and I
could talk to you for another two hours.
Yeah, I think we cover a great questions and I think nothing to
what I think it's a great opportunity for the profession.
Let's step up, let's take this opportunity, follow Martin James
all the work that you are doing in PMG to focus on on a I and
and I think the future it's very right for for us in this
profession finally. So now I'm very excited and
looking forward to connecting with with everyone who's
listening. I think the big point for me,
it's about vision and leadership.
So with project professionals, we're all busy people.
We're stuck in the knife fight over the here and now we're
trying to deliver a project. It's probably going pear shaped,
you know, in most cases. Ohh, that's what the start
filling us. So we don't have the headspace
for this, we just don't have the head space.
And that's what I'm finding from speaking to organisations is
this is a job for tomorrow, it's not for a job for today and I've
been facing that for the past six years, so it's always a job
for tomorrow. So it needs client leadership,
it needs professional leadership, it needs all of us
to pull together to start to drive that.
I don't think that's where we need to be.
We need to be showing people the path.
And showing them the way to take this forward.
So some of the work we've done work with James as well and and
the project data on it, it's task force.
So James is the chair of the project date on it.
It's task force. So it's worth reaching out to
James if you're interested in some of this is the visions for
2025. So we said let's start to
reimagine things like risk management, let's start to
reimagine benefits management. Could that look like in about 18
months from now? All right.
If we can start to imagine it and break it down into some sort
of modules of capability to get us there, it becomes deliverable
and we can all do that if we unite around it.
And and James will probably share with you some of the pain
to try and motivate the community to line up around
those visions. And it's normally because it's
getting access to those thought leaders and those visionaries
and the people who's got the ambition to make this happen.
And I think that is changing in places now.
I think we are starting to see it in ChatGPT has brought this
into the imagination, right? It's made it a lot more
accessible for people. So I do sense that changing.
And I think people like Adam Bonnesen and we've got Andy
Murray as well from the major projects association.
Then I really started to understand this and get all over
it and start as well. So I do think we'll see a major
change probably this year. And James, any any last thoughts
from you? Yeah, so Martin mentioned the
Project Data Analytics Task Force.
So Martin set that up how to how many years ago probably four or
five years ago and he's passed the championship on to me.
We've got our first meeting this week actually.
And you know, I I think what out of the objectives, if I could
think of 1 objective that would move the goalpost most rapidly
is all the institutions started to work together.
And if I see that as my role as helping create this kind of
overlay. So you've got you know what you
guys do which is brilliant. You know these podcasts and
stuff and in in the journals is brilliant.
PMI is doing some of the things. Ohh ICS are doing things.
But you know if we rather than all we're doing little bits
ourselves if we can bring it under one umbrella.
And that's what I hope the project they genetics task force
can become a kind of a way of putting all of this information
like an overlay on top of it all so that people can see there's a
very clear direction that the profession is, is moving in and
then all the institutions and government these are doing their
bit to drive towards that vision.
So I am optimistic there is that there is with all these kind of
things, there's dangers and there's, there's risks and we
have to control that and who's better than to do that, than
project professionals, you know that's part of our part of our
role. All right.
Just leaves me to say thank you to everyone.
Thank you for your time and your thoughts.
Could talk another two hours about this, but we just can't do
that, I'm afraid. But thank you so much.
It's brilliant. Thanks again to Antonio, Martin
and James for joining us, and to you for listening to the APM
podcast. Don't forget to look out for
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