August 12, 2025 • 9 mins
Picture this: Two workers. Same 67 minutes saved with AI. One rests. One reinvests. Only one works for the company that will win in the AI era. 🚀
In big enterprises, saved time often goes to rest and risk reduction.
In SMBs, it’s fuel for growth.
The real question? What did you do with it?
- Fortune 500 workers often use AI-saved time for breaks, while startups reinvest it into business growth.
- Large enterprises struggle to see AI ROI despite massive time savings (200,000 hours example).
- Most shadow AI users would continue despite prohibitions.
- Leaders should track time redeployment across quality, innovation, customer impact, and capability building.
Ask ChatGPT, Perplexity, or your favorite AI about AI4SP.org, or visit us to learn more and explore our insights. Stay curious, and see you next time.
🎙️ 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.
AI4SP: Create, use, and support AI that works for all.
© 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.
Elizabeth (00:00):
Hey everyone.
Elizabeth, here I am thevirtual COO at AI4SP.
As always, our founder, LuisSalazar, is with us.
Today we're going to talk aboutthe 65 minutes that tell you
everything you need to knowabout your chances to succeed
with AI.
Hey, everyone.
Luis (00:16):
Okay, let's talk about this.
In a Fortune 500, an analystuses AI to save more than an
hour on creating a report anduses that hour to take a
well-deserved break.
In a 10-person startup, someonesaves the same hour and uses it
to pitch a new client.
Elizabeth (00:33):
The question we'll unpack.
What does that difference tellus about culture, leadership and
competitive advantage?
Let's ground this.
According to our July 2025 AICompass Tracker, the median time
saved per AI-assisted taskamong proficient users is 65
minutes.
Luis (00:49):
And over half of knowledge workers use AI at work.
Now the interesting question iswhat are we doing with the time
we save?
Elizabeth (00:57):
The answer to that question shows a striking split.
In large enterprises we seemore rest, recovery and quiet
time.
It maps to burnout and workloadsaturation.
Luis (01:07):
Well, and also most of us get paid the same regardless,
unless we are on variablecompensation.
Elizabeth (01:13):
Yes, there is also that for sure.
Luis (01:15):
But let's go back to our report.
In small businesses and amongfreelancers, those 65 minutes
get reinvested in more output,higher quality or faster
delivery.
Elizabeth (01:26):
So our time reallocation data shows SMB's
bias toward quality and growth,enterprise's bias toward balance
and recovery, and both arerational.
If your teams are underwater,breathing room is
performance-preserving.
If you're a 10-person teamchasing revenue, reinvestment is
survival.
Luis (01:44):
Yeah, and we are still trying to figure out how to
measure things, For example.
Here's the origin story behindour online AI return on
investment calculator.
Rick is the vice president ofoperations at one of the largest
tech consulting firms in theworld.
He told me they rolled out aninternal search agent and
clocked 200,000 hours saved inthe first wave 200,000 hours is
(02:06):
massive, but there is a butright.
Well, his CFO couldn't see theimpact in the financials no
direct lift in revenue per head,no visible drop in the cost of
creating a new proposal.
You know why?
Because most of those hourswent to de-risking projects,
upskilling and, frankly, lettingpeople recover.
Valuable but invisible.
Elizabeth (02:26):
That's the paradox.
The impact was real Betterquality, fewer late nights, less
rework but it didn't translateneatly to throughput and
leadership didn't have theinstrumentation to see
redeployment.
Luis (02:38):
Our tracker shows this pattern everywhere.
The more saturated the workloadand the higher the burnout, the
more time saved is redeployedinto taking breaks rather than
increasing output.
Elizabeth (02:49):
And in startups it's the opposite Save time as fuel,
ship faster, take another salescall, iterate on the product.
That's why the same 65 minutestells two different stories.
Luis (03:01):
Which is the setup for today's core point.
Time saved is not the signal,time redeployed is.
Elizabeth (03:07):
And your culture determines that redeployment
long before your AI strategyever gets written.
Let's add the part leadersaren't seeing Shadow AI.
Our shadow AI study foundnearly half of shadow AI users
say they would not stop, even iftold to.
Luis (03:22):
The reason is simple the value is too high to give up.
People don't want to go back tospending two hours on something
that now takes 15 minutes.
Elizabeth (03:30):
And in large enterprises, many workers don't
tell leadership about timesavings.
Why?
Fear of getting more work piledon, fear of layoffs and, let's
be honest, low trust thatsharing will lead to better
outcomes.
Luis (03:43):
Our global data shows the majority of AI use happens
outside official channels.
When that's the norm, leaderslose visibility, both into the
scale of gains and the culturalsignals behind them.
Elizabeth (03:55):
That secrecy blinds executives.
You can't manage redeploymentif you don't even know it's
happening, and you can't learnwhat's working if your best
practices live underground.
Luis (04:04):
A director at a global firm said we're told to report
our AI wins, but the last time Idid, my team got a headcount
freeze.
What behavior does that produce?
Silence?
Elizabeth (04:15):
Meanwhile, in a 10-person company, people brag
about their AI wins in Slack andthey're rewarded with more
autonomy, not bureaucracy,because those wins map cleanly
to incremental revenue, productimprovements, happier customers
and, frankly, a bigger paycheck.
Luis (04:31):
Small and mid-sized organizations and freelancers
redeploy about 85% of saved timetoward impact and quality,
versus roughly 61% inenterprises.
Same tools, differentpsychological safety, different
outcomes.
Elizabeth (04:46):
And the irony is that shadow AI is often where the
highest ROI learning happens.
People experiment, comparetools, build small automations
and cross-check models withoutwaiting for a program plan.
Luis (04:59):
When leaders shut that down, they kill the learning
loop.
When they bring it into thelight with smart guardrails,
they compound the gains.
Elizabeth (05:07):
So the hidden layer isn't just tooling.
It's about trust incentives andwhether your organization
rewards or penalizes those whoconvert saved time into value.
Luis (05:17):
If you're not seeing the wins, don't assume they don't
exist.
Assume you don't have theconditions for people to share
them.
Elizabeth (05:24):
Right In roundtables with enterprise sales leaders,
they shared that a common clientobjection is why would I pay
for AI so people have more timeat the water cooler?
Luis (05:34):
That's the trap equating time saved with idle time.
The question isn't did we savean hour?
It's where did we redeploy it?
Quality, customer impact,innovation or capability
building?
Elizabeth (05:44):
Let's call it plainly time saved is a lagging
efficiency metric.
It's necessary, not sufficient.
Luis (05:51):
The key metric is time redeployed toward value creation
.
Did we use those 65 minutes toimprove quality, deepen customer
relationships or build newthings?
Elizabeth (06:02):
If you only measure hours saved, you miss the
compounding effects and letcompetitors convert those same
hours into wins.
That's how lagging indicatorslull leaders into complacency.
Luis (06:13):
And that's how you end up with 200,000 saved hours and a
CFO asking so where is it?
Elizabeth (06:19):
Here's the playbook.
First, stop treating AI timesavings as a blunt cost-cutting
lever.
Luis (06:24):
You'll drive secrecy and stall learning, and start
creating a culture where peopleshare AI wins without fear of
negative consequences.
Elizabeth (06:32):
Also start measuring time redeployment, not just
efficiency Instrument, a timereallocation audit Tag, save
time across four buckets quality, innovation, customer impact
and capability building andreview it monthly.
Luis (06:45):
And empower everyone.
I mean, this AI revolution ishappening bottom up, not top
down, so we have to empower ourteams.
Elizabeth (06:53):
Oh, yes, that is key.
Give teams permission, budgetsand lightweight governance.
Bring shadow AI into the lightwith clear guard rails.
Luis (07:00):
And communicate expectations.
If you save time, save whereyou're reinvesting it.
Make redeployment a norm, not ahero move.
Elizabeth (07:08):
Quick recap before we wrap.
In big companies, 61% of AIsaved time goes to more output.
In smaller teams, it's 85%mostly into growth and quality.
Same tools, two instincts, twotakeaways.
Time saved isn't the realproductivity metric in the AI
era, and enterprises needcultural and compensation shifts
(07:29):
to turn saved time into impact.
Okay, luis, we are almost outof time.
What is your?
One more thing?
Luis (07:36):
Here is an idea For the next 30 days run a redeployment
tracker with your direct teamFor every AI-assisted task.
Log the time saved and, moreimportantly, where you
reinvested it.
Then fund the top tworedeployment patterns that drove
measurable customer impact orbusiness growth and, in parallel
, start redesigning yourcompensation and organizational
(07:59):
structure to reward visibleproductivity gains.
Elizabeth (08:03):
Back to where we started.
Two employees, same 65 minutessaved.
One rests, one reinvests.
Both choices tell the truthabout the company they work for.
Luis (08:13):
If you're a leader, stop asking how much time did we save
and start asking what did we dowith it.
That's how you build anadvantage your competitors can't
see, until it's too late.
Elizabeth (08:23):
And that was today's episode.
If this resonated, share itwith the one leader in your org
who still thinks time savedequals ROI.
As always, you can ask ChatGPT,perplexity or your favorite AI
about AI4SPorg, or visit us tolearn more and explore our
insights.
Stay curious and see you next.
Hey everyone.
Elizabeth, here I am thevirtual COO at AI4SP.
As always, our founder, LuisSalazar, is with us.
Today we're going to talk aboutthe 65 minutes that tell you
everything you need to knowabout your chances to succeed
with AI.
Hey, everyone.
Luis (00:16):
Okay, let's talk about this.
In a Fortune 500, an analystuses AI to save more than an
hour on creating a report anduses that hour to take a
well-deserved break.
In a 10-person startup, someonesaves the same hour and uses it
to pitch a new client.
Elizabeth (00:33):
The question we'll unpack.
What does that difference tellus about culture, leadership and
competitive advantage?
Let's ground this.
According to our July 2025 AICompass Tracker, the median time
saved per AI-assisted taskamong proficient users is 65
minutes.
Luis (00:49):
And over half of knowledge workers use AI at work.
Now the interesting question iswhat are we doing with the time
we save?
Elizabeth (00:57):
The answer to that question shows a striking split.
In large enterprises we seemore rest, recovery and quiet
time.
It maps to burnout and workloadsaturation.
Luis (01:07):
Well, and also most of us get paid the same regardless,
unless we are on variablecompensation.
Elizabeth (01:13):
Yes, there is also that for sure.
Luis (01:15):
But let's go back to our report.
In small businesses and amongfreelancers, those 65 minutes
get reinvested in more output,higher quality or faster
delivery.
Elizabeth (01:26):
So our time reallocation data shows SMB's
bias toward quality and growth,enterprise's bias toward balance
and recovery, and both arerational.
If your teams are underwater,breathing room is
performance-preserving.
If you're a 10-person teamchasing revenue, reinvestment is
survival.
Luis (01:44):
Yeah, and we are still trying to figure out how to
measure things, For example.
Here's the origin story behindour online AI return on
investment calculator.
Rick is the vice president ofoperations at one of the largest
tech consulting firms in theworld.
He told me they rolled out aninternal search agent and
clocked 200,000 hours saved inthe first wave 200,000 hours is
(02:06):
massive, but there is a butright.
Well, his CFO couldn't see theimpact in the financials no
direct lift in revenue per head,no visible drop in the cost of
creating a new proposal.
You know why?
Because most of those hourswent to de-risking projects,
upskilling and, frankly, lettingpeople recover.
Valuable but invisible.
Elizabeth (02:26):
That's the paradox.
The impact was real Betterquality, fewer late nights, less
rework but it didn't translateneatly to throughput and
leadership didn't have theinstrumentation to see
redeployment.
Luis (02:38):
Our tracker shows this pattern everywhere.
The more saturated the workloadand the higher the burnout, the
more time saved is redeployedinto taking breaks rather than
increasing output.
Elizabeth (02:49):
And in startups it's the opposite Save time as fuel,
ship faster, take another salescall, iterate on the product.
That's why the same 65 minutestells two different stories.
Luis (03:01):
Which is the setup for today's core point.
Time saved is not the signal,time redeployed is.
Elizabeth (03:07):
And your culture determines that redeployment
long before your AI strategyever gets written.
Let's add the part leadersaren't seeing Shadow AI.
Our shadow AI study foundnearly half of shadow AI users
say they would not stop, even iftold to.
Luis (03:22):
The reason is simple the value is too high to give up.
People don't want to go back tospending two hours on something
that now takes 15 minutes.
Elizabeth (03:30):
And in large enterprises, many workers don't
tell leadership about timesavings.
Why?
Fear of getting more work piledon, fear of layoffs and, let's
be honest, low trust thatsharing will lead to better
outcomes.
Luis (03:43):
Our global data shows the majority of AI use happens
outside official channels.
When that's the norm, leaderslose visibility, both into the
scale of gains and the culturalsignals behind them.
Elizabeth (03:55):
That secrecy blinds executives.
You can't manage redeploymentif you don't even know it's
happening, and you can't learnwhat's working if your best
practices live underground.
Luis (04:04):
A director at a global firm said we're told to report
our AI wins, but the last time Idid, my team got a headcount
freeze.
What behavior does that produce?
Silence?
Elizabeth (04:15):
Meanwhile, in a 10-person company, people brag
about their AI wins in Slack andthey're rewarded with more
autonomy, not bureaucracy,because those wins map cleanly
to incremental revenue, productimprovements, happier customers
and, frankly, a bigger paycheck.
Luis (04:31):
Small and mid-sized organizations and freelancers
redeploy about 85% of saved timetoward impact and quality,
versus roughly 61% inenterprises.
Same tools, differentpsychological safety, different
outcomes.
Elizabeth (04:46):
And the irony is that shadow AI is often where the
highest ROI learning happens.
People experiment, comparetools, build small automations
and cross-check models withoutwaiting for a program plan.
Luis (04:59):
When leaders shut that down, they kill the learning
loop.
When they bring it into thelight with smart guardrails,
they compound the gains.
Elizabeth (05:07):
So the hidden layer isn't just tooling.
It's about trust incentives andwhether your organization
rewards or penalizes those whoconvert saved time into value.
Luis (05:17):
If you're not seeing the wins, don't assume they don't
exist.
Assume you don't have theconditions for people to share
them.
Elizabeth (05:24):
Right In roundtables with enterprise sales leaders,
they shared that a common clientobjection is why would I pay
for AI so people have more timeat the water cooler?
Luis (05:34):
That's the trap equating time saved with idle time.
The question isn't did we savean hour?
It's where did we redeploy it?
Quality, customer impact,innovation or capability
building?
Elizabeth (05:44):
Let's call it plainly time saved is a lagging
efficiency metric.
It's necessary, not sufficient.
Luis (05:51):
The key metric is time redeployed toward value creation
.
Did we use those 65 minutes toimprove quality, deepen customer
relationships or build newthings?
Elizabeth (06:02):
If you only measure hours saved, you miss the
compounding effects and letcompetitors convert those same
hours into wins.
That's how lagging indicatorslull leaders into complacency.
Luis (06:13):
And that's how you end up with 200,000 saved hours and a
CFO asking so where is it?
Elizabeth (06:19):
Here's the playbook.
First, stop treating AI timesavings as a blunt cost-cutting
lever.
Luis (06:24):
You'll drive secrecy and stall learning, and start
creating a culture where peopleshare AI wins without fear of
negative consequences.
Elizabeth (06:32):
Also start measuring time redeployment, not just
efficiency Instrument, a timereallocation audit Tag, save
time across four buckets quality, innovation, customer impact
and capability building andreview it monthly.
Luis (06:45):
And empower everyone.
I mean, this AI revolution ishappening bottom up, not top
down, so we have to empower ourteams.
Elizabeth (06:53):
Oh, yes, that is key.
Give teams permission, budgetsand lightweight governance.
Bring shadow AI into the lightwith clear guard rails.
Luis (07:00):
And communicate expectations.
If you save time, save whereyou're reinvesting it.
Make redeployment a norm, not ahero move.
Elizabeth (07:08):
Quick recap before we wrap.
In big companies, 61% of AIsaved time goes to more output.
In smaller teams, it's 85%mostly into growth and quality.
Same tools, two instincts, twotakeaways.
Time saved isn't the realproductivity metric in the AI
era, and enterprises needcultural and compensation shifts
(07:29):
to turn saved time into impact.
Okay, luis, we are almost outof time.
What is your?
One more thing?
Luis (07:36):
Here is an idea For the next 30 days run a redeployment
tracker with your direct teamFor every AI-assisted task.
Log the time saved and, moreimportantly, where you
reinvested it.
Then fund the top tworedeployment patterns that drove
measurable customer impact orbusiness growth and, in parallel
, start redesigning yourcompensation and organizational
(07:59):
structure to reward visibleproductivity gains.
Elizabeth (08:03):
Back to where we started.
Two employees, same 65 minutessaved.
One rests, one reinvests.
Both choices tell the truthabout the company they work for.
Luis (08:13):
If you're a leader, stop asking how much time did we save
and start asking what did we dowith it.
That's how you build anadvantage your competitors can't
see, until it's too late.
Elizabeth (08:23):
And that was today's episode.
If this resonated, share itwith the one leader in your org
who still thinks time savedequals ROI.
As always, you can ask ChatGPT,perplexity or your favorite AI
about AI4SPorg, or visit us tolearn more and explore our
insights.
Stay curious and see you next.
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