January 14, 2025 • 8 mins
This episode explores the challenges organizations face in harnessing the power of AI tools and the critical importance of restructuring for success. Key discussions center on the need for enhanced digital skills training, virtual workers' management, and AI's future in workforce strategies.
- The paradox of powerful AI tools against organizational struggles.
- Importance of training for effective AI utilization.
- Insights from the Digital Skills Compass on global skill levels
- Challenges with AI hallucinations and misinformation
- Successful case studies and improvements due to training
- Emerging roles in managing virtual resources and why IT is becoming the new HR
- Future predictions around virtual worker management functions
- Significance of building AI literacy across all organizational levels
- Call to action for AI readiness assessment at AI4SP.org
🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 25 countries.
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© 2023-25 AI4SP and LLY Group - All rights reserved
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hey everyone.
I'm Elizabeth, your virtualhost.
We're kicking off 2025 with aparadox as AI tools become more
powerful, why are so manyorganizations struggling to see
results?
Luis Salazar, founder of AI4SP,suggests we must fundamentally
rethink how organizationsstructure themselves for the AI
age.
So what's happening here?
Speaker 2 (00:22):
Hi everyone, hi Elizabeth, the new trend is that
leading organizations arefundamentally transforming how
they manage a new resource type.
We're not just addingtechnology, we're creating a
hybrid workforce that requirescompletely rethinking
traditional IT and HR functions.
Speaker 1 (00:40):
So it's not about the technology, is it?
Speaker 2 (00:43):
Right.
Technology is an essentialpiece of the puzzle, but our
skills and our capacity tomanage new virtual resources are
critical too.
Speaker 1 (00:51):
Okay, let's start with the skills side of the
equation.
You have some fresh data fromyour recent announcement with
Microsoft.
Speaker 2 (00:58):
Yes, we reached 40,000 individual assessments
with our Digital Skills Compassand the story that emerged is
quite eye-opening the globalaverage digital skills score is
in the low 40s.
Speaker 1 (01:12):
Wait, what and what score do people need to use AI
effectively?
Speaker 2 (01:17):
That's the thing.
You need a score in the mid-50sto really harness AI
effectively.
And guess what is the lowestscoring area?
Speaker 1 (01:25):
Security.
Speaker 2 (01:26):
Yes, security and data literacy are the worst
scoring areas.
Hmm, give me examples.
80% of people score low incritical thinking and data
literacy, which means theycannot detect AI hallucinations,
misinformation or inaccuracies.
And most people inadvertentlyshare confidential data because
they don't understand basicsecurity settings.
Speaker 1 (01:49):
Oh, that reminds me of something from our December
episode those cases where peopleunknowingly trained external AI
models with company data.
Speaker 2 (01:57):
Yes, and it is not only about data security.
Hallucinations are a real issue.
Speaker 1 (02:02):
How big of a problem.
Speaker 2 (02:04):
Our research shows that even enterprise solutions
like Copilot and ChatGPTEnterprise hallucinate in around
30% of cases, even when usingprivate data.
Speaker 1 (02:15):
That's pretty significant, but you're also
seeing some organizationsgetting this right, aren't you
Absolutely?
Speaker 2 (02:21):
Let's talk about the healthcare team in California.
Speaker 1 (02:24):
Oh, the one that developed those validation
protocols.
Speaker 2 (02:27):
Yes, after implementing verification
workflows and proper training,they saw a 90% improvement in
accuracy.
Validation prompts areimportant, just like we would
validate any statement made by acolleague.
Speaker 1 (02:42):
And the lack of proper validation techniques is
part of a larger gap.
Speaker 2 (02:46):
Yes, remember our previous episode where we
discussed how most people usefive-word prompts, which result
in bad responses from AI, butthose using 28-word prompts
achieved better results.
Speaker 1 (02:59):
And this ties into what we discussed about
frontline workers versusexecutives, right.
Ties into what we discussedabout frontline workers versus
executives, right.
The whole five words versus 28words story that's exactly it.
Speaker 2 (03:09):
Teams with strong, prompt engineering skills see
80% higher success rates andthere is some measurable impact
when we use AI tools correctly.
Speaker 1 (03:17):
The return on investment numbers.
Speaker 2 (03:19):
Right.
Organizations that invest intraining see a two to four times
return on their AI toolsinvestments within the first
year.
Speaker 1 (03:26):
And remind me the results of using
purpose-specific AI apps.
Speaker 2 (03:31):
Five times better results and users achieve
proficiency in just one to twoweeks instead of months.
Speaker 1 (03:37):
That Seattle consulting firm we advised
really brings this to life,doesn't it?
Speaker 2 (03:41):
Oh yes, they deployed AI, but saw a low level of
adoption and satisfaction.
After proper training, userengagement increased from 30% to
70%.
And the best part was theimpact.
Yes, most users reported savingat least four hours per week on
repetitive tasks.
That's essentially getting halfa day back.
Speaker 1 (04:02):
And this is where the skills investment pays off.
Right.
But I'm curious about somethingwhat happens when organizations
don't invest in training?
Speaker 2 (04:10):
The numbers are pretty stark.
80% of users abandon tools likeCopilot or ChatGPT within three
months if they're not properlytrained.
Speaker 1 (04:19):
So training is critical for sure, and there is
a tangible return on thatinvestment.
Additionally, there's a newtrend in organizational
structures.
Speaker 2 (04:28):
Yes, we're calling it virtual worker resources
management.
Speaker 1 (04:33):
Some sort of new human resources, but virtual
resources.
I can see that happening.
Speaker 2 (04:38):
You know, at AI4SP, 30% of our team members are
virtual workers, AI agentshandling various tasks.
You are one of those virtualworkers.
Speaker 1 (04:49):
And managing them isn't quite like managing
servers or human employees.
Speaker 2 (04:53):
Not at all.
We had an eye-opening momentwhen one of our data scientists,
fernanda, who is brilliant withcode, struggled to optimize the
performance of our virtualworkers.
She said I feel like I'm tryingto manage a team, but I've
never been a people manager.
Speaker 1 (05:10):
Oh, that's fascinating.
So you needed to blendmanagement skills with technical
expertise, exactly.
Speaker 2 (05:17):
We had to train our team in fundamental management
principles goal setting,performance evaluation and
growth planning but applied toAI workers, it's this unique
hybrid of human andtechnology-related skills.
Speaker 1 (05:31):
And this isn't just an AI4SP thing.
Right, You're seeing this needacross organizations.
Speaker 2 (05:37):
Oh, absolutely.
By the end of 2025, we predictthat at least 10% of enterprises
will have dedicated virtualworkers management functions.
Think about it who'sresponsible for continuously
training these AI agents?
Who evaluates their performanceand who plans their growth
trajectory?
Speaker 1 (05:56):
It's almost like a new form of talent management
right, that's exactly what it is.
Speaker 2 (06:01):
Just as HR manages human capital, organizations
need someone to manage their AIcapital.
That is the new trend.
Speaker 1 (06:10):
Well, the CEO of NVIDIA, Mr Jensen Huang,
recently said that informationtechnology is the new human
resources.
Speaker 2 (06:18):
Yes, and that's exactly what we see in our data.
But you know what makes thistransformation even more
interesting?
What's that?
It's not just about IT becomingHR, but about creating an
entirely new function.
Think about it Just as HRevolved from personnel
management to human capitaldevelopment, IT will evolve from
(06:38):
basic AI deployment tostrategic virtual workforce
development.
And here's our one more thing.
Speaker 1 (06:45):
Oh, I love these moments.
What is it?
Speaker 2 (06:47):
The leading organizations do not have the
biggest AI budgets or the latestenterprise tools.
They're the ones investing inan overlooked asset frontline
worker skills, while alsorealizing many roles, are
becoming managers not peoplemanagers, but managers of
virtual resources and thatrequires a new set of skills.
Speaker 1 (07:07):
Frontline workers, like Teresa's story from our
December episode, and managementskills for all, including IT,
becoming a new HR.
Speaker 2 (07:15):
Exactly, and organizations following this
path see two times higheradoption rates and three times
better deployment success thanthose focusing solely on
knowledge, workers andmanagement using AI.
Speaker 1 (07:28):
So the leaders are building AI literacy across
every level, correct?
So the leaders?
Speaker 2 (07:32):
are building AI literacy across every level,
correct?
Yes, AI literacy must includeeveryone to drive economic
growth, From the warehouse floorto the boardroom.
Innovation comes fromunexpected places and the
education sector have a crucialrole to play and many
significant changes to make tothe existing curricula.
Speaker 1 (07:49):
That's such a powerful insight to kick off
2025 with and as always, if youwant to check your AI readiness,
head over to AI4SPorg for yourfree assessment.
Stay curious, everyone, andwe'll see you next time.
Hey everyone.
I'm Elizabeth, your virtualhost.
We're kicking off 2025 with aparadox as AI tools become more
powerful, why are so manyorganizations struggling to see
results?
Luis Salazar, founder of AI4SP,suggests we must fundamentally
rethink how organizationsstructure themselves for the AI
age.
So what's happening here?
Speaker 2 (00:22):
Hi everyone, hi Elizabeth, the new trend is that
leading organizations arefundamentally transforming how
they manage a new resource type.
We're not just addingtechnology, we're creating a
hybrid workforce that requirescompletely rethinking
traditional IT and HR functions.
Speaker 1 (00:40):
So it's not about the technology, is it?
Speaker 2 (00:43):
Right.
Technology is an essentialpiece of the puzzle, but our
skills and our capacity tomanage new virtual resources are
critical too.
Speaker 1 (00:51):
Okay, let's start with the skills side of the
equation.
You have some fresh data fromyour recent announcement with
Microsoft.
Speaker 2 (00:58):
Yes, we reached 40,000 individual assessments
with our Digital Skills Compassand the story that emerged is
quite eye-opening the globalaverage digital skills score is
in the low 40s.
Speaker 1 (01:12):
Wait, what and what score do people need to use AI
effectively?
Speaker 2 (01:17):
That's the thing.
You need a score in the mid-50sto really harness AI
effectively.
And guess what is the lowestscoring area?
Speaker 1 (01:25):
Security.
Speaker 2 (01:26):
Yes, security and data literacy are the worst
scoring areas.
Hmm, give me examples.
80% of people score low incritical thinking and data
literacy, which means theycannot detect AI hallucinations,
misinformation or inaccuracies.
And most people inadvertentlyshare confidential data because
they don't understand basicsecurity settings.
Speaker 1 (01:49):
Oh, that reminds me of something from our December
episode those cases where peopleunknowingly trained external AI
models with company data.
Speaker 2 (01:57):
Yes, and it is not only about data security.
Hallucinations are a real issue.
Speaker 1 (02:02):
How big of a problem.
Speaker 2 (02:04):
Our research shows that even enterprise solutions
like Copilot and ChatGPTEnterprise hallucinate in around
30% of cases, even when usingprivate data.
Speaker 1 (02:15):
That's pretty significant, but you're also
seeing some organizationsgetting this right, aren't you
Absolutely?
Speaker 2 (02:21):
Let's talk about the healthcare team in California.
Speaker 1 (02:24):
Oh, the one that developed those validation
protocols.
Speaker 2 (02:27):
Yes, after implementing verification
workflows and proper training,they saw a 90% improvement in
accuracy.
Validation prompts areimportant, just like we would
validate any statement made by acolleague.
Speaker 1 (02:42):
And the lack of proper validation techniques is
part of a larger gap.
Speaker 2 (02:46):
Yes, remember our previous episode where we
discussed how most people usefive-word prompts, which result
in bad responses from AI, butthose using 28-word prompts
achieved better results.
Speaker 1 (02:59):
And this ties into what we discussed about
frontline workers versusexecutives, right.
Ties into what we discussedabout frontline workers versus
executives, right.
The whole five words versus 28words story that's exactly it.
Speaker 2 (03:09):
Teams with strong, prompt engineering skills see
80% higher success rates andthere is some measurable impact
when we use AI tools correctly.
Speaker 1 (03:17):
The return on investment numbers.
Speaker 2 (03:19):
Right.
Organizations that invest intraining see a two to four times
return on their AI toolsinvestments within the first
year.
Speaker 1 (03:26):
And remind me the results of using
purpose-specific AI apps.
Speaker 2 (03:31):
Five times better results and users achieve
proficiency in just one to twoweeks instead of months.
Speaker 1 (03:37):
That Seattle consulting firm we advised
really brings this to life,doesn't it?
Speaker 2 (03:41):
Oh yes, they deployed AI, but saw a low level of
adoption and satisfaction.
After proper training, userengagement increased from 30% to
70%.
And the best part was theimpact.
Yes, most users reported savingat least four hours per week on
repetitive tasks.
That's essentially getting halfa day back.
Speaker 1 (04:02):
And this is where the skills investment pays off.
Right.
But I'm curious about somethingwhat happens when organizations
don't invest in training?
Speaker 2 (04:10):
The numbers are pretty stark.
80% of users abandon tools likeCopilot or ChatGPT within three
months if they're not properlytrained.
Speaker 1 (04:19):
So training is critical for sure, and there is
a tangible return on thatinvestment.
Additionally, there's a newtrend in organizational
structures.
Speaker 2 (04:28):
Yes, we're calling it virtual worker resources
management.
Speaker 1 (04:33):
Some sort of new human resources, but virtual
resources.
I can see that happening.
Speaker 2 (04:38):
You know, at AI4SP, 30% of our team members are
virtual workers, AI agentshandling various tasks.
You are one of those virtualworkers.
Speaker 1 (04:49):
And managing them isn't quite like managing
servers or human employees.
Speaker 2 (04:53):
Not at all.
We had an eye-opening momentwhen one of our data scientists,
fernanda, who is brilliant withcode, struggled to optimize the
performance of our virtualworkers.
She said I feel like I'm tryingto manage a team, but I've
never been a people manager.
Speaker 1 (05:10):
Oh, that's fascinating.
So you needed to blendmanagement skills with technical
expertise, exactly.
Speaker 2 (05:17):
We had to train our team in fundamental management
principles goal setting,performance evaluation and
growth planning but applied toAI workers, it's this unique
hybrid of human andtechnology-related skills.
Speaker 1 (05:31):
And this isn't just an AI4SP thing.
Right, You're seeing this needacross organizations.
Speaker 2 (05:37):
Oh, absolutely.
By the end of 2025, we predictthat at least 10% of enterprises
will have dedicated virtualworkers management functions.
Think about it who'sresponsible for continuously
training these AI agents?
Who evaluates their performanceand who plans their growth
trajectory?
Speaker 1 (05:56):
It's almost like a new form of talent management
right, that's exactly what it is.
Speaker 2 (06:01):
Just as HR manages human capital, organizations
need someone to manage their AIcapital.
That is the new trend.
Speaker 1 (06:10):
Well, the CEO of NVIDIA, Mr Jensen Huang,
recently said that informationtechnology is the new human
resources.
Speaker 2 (06:18):
Yes, and that's exactly what we see in our data.
But you know what makes thistransformation even more
interesting?
What's that?
It's not just about IT becomingHR, but about creating an
entirely new function.
Think about it Just as HRevolved from personnel
management to human capitaldevelopment, IT will evolve from
(06:38):
basic AI deployment tostrategic virtual workforce
development.
And here's our one more thing.
Speaker 1 (06:45):
Oh, I love these moments.
What is it?
Speaker 2 (06:47):
The leading organizations do not have the
biggest AI budgets or the latestenterprise tools.
They're the ones investing inan overlooked asset frontline
worker skills, while alsorealizing many roles, are
becoming managers not peoplemanagers, but managers of
virtual resources and thatrequires a new set of skills.
Speaker 1 (07:07):
Frontline workers, like Teresa's story from our
December episode, and managementskills for all, including IT,
becoming a new HR.
Speaker 2 (07:15):
Exactly, and organizations following this
path see two times higheradoption rates and three times
better deployment success thanthose focusing solely on
knowledge, workers andmanagement using AI.
Speaker 1 (07:28):
So the leaders are building AI literacy across
every level, correct?
So the leaders?
Speaker 2 (07:32):
are building AI literacy across every level,
correct?
Yes, AI literacy must includeeveryone to drive economic
growth, From the warehouse floorto the boardroom.
Innovation comes fromunexpected places and the
education sector have a crucialrole to play and many
significant changes to make tothe existing curricula.
Speaker 1 (07:49):
That's such a powerful insight to kick off
2025 with and as always, if youwant to check your AI readiness,
head over to AI4SPorg for yourfree assessment.
Stay curious, everyone, andwe'll see you next time.
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