Every AI vendor pitch follows the same script: “Our tool saves your team 40% of their time on X task.”

The demo looks impressive. The return on investment (ROI) calculator backs it up, showing millions in labor cost savings. You get budget approval. You deploy.

Six months later, your CFO asks: “Where’s the 40% productivity gain in our revenue?”

You realize the saved time went to email and meetings, not strategic work that moves the business forward.

This is the AI measurement crisis playing out in enterprises right now.

According to Fortune’s December 2025 report, 61% of CEOs report increasing pressure to show returns on AI investments. Yet most organizations are measuring the wrong things.

There’s a problem with how we’ve been tracking AI’s value.

## Why ‘Time Saved’ Is A Vanity Metric

Time saved sounds compelling in a business case. It’s concrete, measurable, and easy to calculate.

But time saved doesn’t equal value created.

Anthropic’s November 2025 research analyzing 100,000 real AI conversations found that AI reduces task completion time by approximately 80%. Sounds transformative, right?

What that stat doesn’t capture is the **Jevons Paradox of AI**.

In economics, the Jevons Paradox occurs when technological progress increases the efficiency with which a resource is used, but the rate of consumption of that resource rises rather than falls.

In the corporate world, this is the **Reallocation Fallacy**. Just because AI completes a task faster doesn’t mean your team is producing more value. It means they’re producing the same output in less time, but then filling that saved time with lower-value work. Think more meetings, longer email threads, and administrative drift.

Google Cloud’s 2025 ROI of AI report, surveying 3,466 business leaders, found that 74% report seeing ROI within the first year, most commonly through productivity and efficiency gains rather than outcome improvements.

But when you dig into what they’re measuring, it’s primarily efficiency gains, and not outcome improvements.

CFOs understand this intuitively. That’s why “time saved” metrics don’t convince finance teams to increase AI budgets.

What does convince them is measuring what AI enables you to do that you couldn’t do before.

## The Three Types Of AI Value Nobody’s Measuring

Recent research from Anthropic, OpenAI, and Google reveals a pattern: The organizations seeing real AI ROI are measuring expansion.

Three types of value actually matter:

### Type 1: Quality Lift

AI can make work faster, and it makes good work better.

A marketing team using AI for email campaigns can send emails quicker. And they also have time to A/B test multiple subject lines, personalize content by segment, and analyze results to improve the next campaign.

The metric isn’t “time saved writing emails.” The metric is “15% higher email conversion rate.”

OpenAI’s State of Enterprise AI report, based on 9,000 workers across almost 100 enterprises, found that 85% of marketing and product users report faster campaign execution. But the real value shows up in campaign performance, not campaign speed.

**How to measure quality lift:**
- Conversion rate improvements (not just task completion speed).
- Customer satisfaction scores (not just response time).
- Error reduction rates (not just throughput).
- Revenue per campaign (not just campaigns launched).

One B2B SaaS company I talked to deployed AI for content creation.
- Their old metric was “blog posts published per month.”
- Their new metric became “organic traffic from AI-assisted content vs. human-only content.”

The AI-assisted content drove 23% more organic traffic because the team had time to optimize for search intent, not just word count.

That’s quality lift.

### Type 2: Scope Expansion (The Shadow IT Advantage)

This is the metric most organizations completely miss.

Anthropic’s research on how their own engineers use Claude found that 27% of AI-assisted work wouldn’t have been done otherwise.

More than a quarter of the value AI creates isn’t from doing existing work faster; it’s from doing work that was previously impossible within time and budget constraints.

What does scope expansion look like? It often looks like positive Shadow IT.

**The “papercuts” phenomenon:** Small bugs that never got prioritized finally get fixed. Technical debt gets addressed. Internal tools that were “someday” projects actually get built because a non-engineer could scaffold them with AI.

**The capability unlock:** Marketing teams doing data analysis they couldn’t do before. Sales teams creating custom materials for each prospect instead of using generic decks. Customer success teams proactively reaching out instead of waiting for problems.

Google Cloud’s data shows 70% of leaders report productivity gains, with 39% seeing ROI specifically from AI enabling work that wasn’t part of the original scope.

**How to measure scope expansion:**
- Track projects completed that weren’t in the original roadmap.
- Ratio of backlog features cleared by non-engineers.
- Measure customer requests fulfilled that would have been declined due to resource constraints.
- Document internal tools built that were previously “someday” projects.

One enterprise software company used this metric to justify its AI investment. It tracked:
- 47 customer feature requests implemented that would have been declined.
- 12 internal process improvements that had been on the backlog for over a year.
- 8 competitive vulnerabilities addressed that were previously “known issues.”

None of that shows up in “time saved” calculations. But it showed up clearly in customer retention rates and competitive win rates.

### Type 3: Capability Unlock (The Full-Stack Employee)

We used to hire for deep specialization. AI is ushering in the era of the “Generalist-Specialist.”

Anthropic’s internal research found that security teams are building data visualizations. Alignment researchers are shipping frontend code. Engineers are creating marketing materials.

AI lowers the barrier to entry for hard skills.

A marketing manager doesn’t need to know SQL to query a database anymore; she just needs to know what question to ask the AI. This goes well beyond speed or time saved to removing the dependency bottleneck.

When a marketer can run their own analysis without waiting three weeks for the Data Science team, the velocity of the entire organization accelerates. The marketing generalist is now a front-end developer, a data analyst, and a copywriter all at once.

OpenAI’s enterprise data shows 75% of users report being able to complete new tasks they previously couldn’t perform. Coding-related messages increased 36% for workers outside of technical functions.

**How to measure capability unlock:**
- Skills accessed (not skills owned).
- Cross-functional work completed without handoffs.
- Speed to execute on ideas that would have required hiring or outsourcing.
- Projects launched without expanding headcount.

A marketing leader at a mid-market B2B company told me her team can now handle routine reporting and standard analyses with AI support, work that previously required weeks on the analytics team’s queue.

Their campaign optimization cycle accelerated 4x, leading to 31% higher campaign performance.

The “time saved” metric would say: “AI saves two hours per analysis.”

The capability unlock metric says: “We can now run 4x more tests per quarter, and our analytics team tackles deeper strategic work.”

## Building A Finance-Friendly AI ROI Framework

CFOs care about three questions:
- Is this increasing revenue? (Not just reducing cost.)
- Is this creating competitive advantage? (Not just matching competitors.)
- Is this sustainable? (Not just a short-term productivity bump.)

**How to build an AI measurement framework that actually answers those questions:**

### Step 1: Baseline Your “Before AI” State

Don’t skip this step, or else it will be impossible to prove AI impact later. Before deploying AI, document current throughput, quality metrics, and scope limitations.

### Step 2: Define Leading Vs. Lagging Indicators

You need to track both efficiency and expansion, but you need to frame them correctly to Finance.
- **Leading Indicator (Efficiency):** Time saved on existing tasks. This predicts potential capacity.
- **Lagging Indicator (Expansion):** New work enabled and revenue impact. This proves the value was realized.

### Step 3: Track AI Impact On Revenue, Not Just Cost

Connect AI metrics directly to business outcomes:
- If AI helps customer success teams → Track retention rate changes.
- If AI helps sales teams → Track win rate and deal velocity changes.
- If AI helps marketing teams → Track pipeline contribution and conversion rate changes.
- If AI helps product teams → Track feature adoption and customer satisfaction changes.

### Step 4: Measure The “Frontier” Gap

OpenAI’s enterprise research revealed a widening gap between “frontier” workers and median workers. Frontier firms send 2x more messages per seat.

This means identifying the teams extracting real value versus the teams just experimenting.

### Step 5: Build The Measurement Infrastructure First

PwC’s 2026 AI predictions warn that measuring iterations instead of outcomes falls short when AI handles complex workflows.

As PwC notes: “If an outcome that once took five days and two iterations now takes fifteen iterations but only two days, you’re ahead.”

The infrastructure you need before you deploy AI involves baseline metrics, clear attribution models, and executive sponsorship to act on insights.

## The Measurement Paradox

The organizations best positioned to measure AI ROI are the ones who already had good measurement infrastructure.

According to Kyndryl’s 2025 Readiness Report, most firms aren’t positioned to prove AI ROI because they lack the foundational data discipline.

Sound familiar? This connects directly to the data hygiene challenge I’ve written about previously. You can’t measure AI’s impact if your data is messy, conflicting, or siloed.

## The Bottom Line

The AI productivity revolution is well underway. According to Anthropic’s research, current-generation AI could increase U.S. labor productivity growth by 1.8% annually over the next decade, roughly doubling recent rates.

But capturing that value requires measuring the right things.

Forget asking: “How much time does this save?”

Instead, focus on:
- “What quality improvements are we seeing in output?”
- “What work is now possible that wasn’t before?”
- “What capabilities can we access without expanding headcount?”

These are the metrics that convince CFOs to increase AI budgets. These are the metrics that reveal whether AI is actually transforming your business or just making you busy faster.

Time saved is a vanity metric. Expansion enabled is the real ROI.

Measure accordingly.

How to replace vanity productivity metrics with a finance-ready AI measurement model tied to growth, advantage, and scale.

Beyond Time Saved: The 3 AI Metrics That Actually Convince CFOs to Increase Budgets

If your Gmail inbox feels particularly chaotic this weekend, you aren't the only one dealing with the mess. A glitch seems to be breaking the filters that usually keep marketing fluff out of your important emails.

## The Floodgates Have Opened

It looks like Google's sorting algorithm has taken a break. According to several reports online, a significant number of Gmail users are noticing that the **"Promotions" tab is failing to do its job**. Instead of tucking away newsletters, sale alerts, and general marketing blasts into their designated folder, Gmail is dumping them right into the **"Primary" inbox**.

This issue seems to have started popping up earlier today (January 24), with users flocking to online forums and support pages to ask if they were the only ones. We have seen threads on Reddit where confused users are wondering why their main feed is suddenly cluttered with coupons. It seems the system that automatically detects and segregates these mass emails is currently ignoring its programming.

## Why This Mess Matters to Your Sanity

Most of us rely on Gmail's tabbed inbox feature to maintain a semblance of digital peace. The **"Primary" tab is supposed to be a sanctuary for emails from actual humans, important bills, or work emails**. When the **"Promotions" filter breaks**, that sanctuary gets overrun by retail noise.

However, this is likely a temporary situation. Google has yet to acknowledge the bug, and the reports continue to flood Reddit and Google's own community forums. We also don't know how widespread this may be. All we can do at this point is wait until Google responds.

## Advice for Right Now

I checked my phone this morning and noticed a few errant emails that definitely did not belong in my primary inbox. It is definitely annoying, but I wouldn't panic just yet.

These server-side glitches usually get ironed out by Google engineers pretty quickly once they notice the spike in complaints. So, for now, I wouldn't try to manually move or delete these emails until Google addresses the situation. Our best bet is likely to just sit tight and wait to get additional information on what is actually happening. We will keep an eye on it and let you know when it's safe to look at your inbox again.

**Update from January 24th, 2026:**
Google has shared that the issue has now been resolved.

An apparent bug is making a mess of our email organization.

Gmail's Marketing Email Filter Is Broken: Your Inbox Is Flooded With Promotions

## The New Normal: Juggling Multiple Jobs

When 30-year-old Kim finishes her full-time marketing job at 6 p.m., her day is only half over. Three evenings a week, often including weekends, she rushes across Seoul to tutor middle and high school students in English.

“I’ve been tutoring for seven years,” she said. “With the 3 million won ($2,074) I earn from my main job, I feel like I’ll never be able to buy a house or start a family. **Working one job just doesn’t seem enough for the future anymore.**”

For 32-year-old Lee, a salesperson at a major conglomerate, nights are spent on his laptop, uploading and registering Korean beauty products on Amazon. The work is tedious and the platform’s standards demanding, often leaving him stressed. Still, he says he has little choice.

“After rent, groceries and the occasional meal out, there’s barely anything left to save,” he said. “This isn’t about ambition. **It’s a necessity.**”

Kim and Lee are far from outliers. Side jobs, once associated with freelancers or those between jobs, have quietly become a defining feature of young adulthood in South Korea.

Financial motivations, lack of trust in the traditional office structure, and even the desire to reinvent themselves or fulfill one's personal dream are propelling the growing trend of **“N-jobbers”** — referring to those holding down more than one job.

Nearly half of Korean workers now report having a side hustle, according to a recent survey by job portal Incruit, with participation highest among those in their 20s (55.2 percent) and 30s (57 percent).

## Survival Strategies in a Tough Economy

Data backs the growing reliance on additional income. According to microdata from the Ministry of Data and Statistics, the number of workers with secondary employment, including both regular and temporary employees, reached 404,409 as of October 2025.

A survey of 728 adults conducted in December by short-term job search platform NewWorker also showed that 49.5 percent of respondents were engaged in some form of side work, nearly matching the 50.5 percent who said they were not. Among full-time office workers specifically, 48.4 percent reported having additional work beyond their main job.

Experts say the numbers likely underestimate the real scale, as many workers are hesitant to disclose secondary income sources to employers.

As the number of young Koreans taking on side jobs increases, so has the diversity in the side job market. Opportunities are tailored to digital skills or personal interests and are available online and offline.

Side jobs range from one-off paid appearances as wedding guests and private academic coaching to smartphone-based earnings, where an individual can earn a small amount of money by watching ads, browsing and physically walking.

With the widespread use of artificial intelligence, many are also seeking YouTube content production, blogging or running online stores to secure supplemental income.

“This diversification has been accelerated by social media, which functions as both a marketplace and a learning platform. Workers share tips on app-based earnings, digital sales strategies or content-creation know-how, encouraging more people to try low-barrier forms of additional income,” said a 34-year-old Lee Ji-won, who is earning an extra 1 million won by posting blogs.

“On Instagram, there are floods of posts about how to make money on the platform. Many who succeed publish books and become famous within the community,” Lee said.

![An Instagram post showing diverse platforms where additional income can be earned. (Instagram)](https://wimg.heraldcorp.com/news/cms/2026/01/25/news-p.v1.20260125.e7ebf78b35a34911a1f744b848cffae5_P1.png)

So what's behind the surge?

Experts point to a disconnect between official inflation and lived reality. While consumer prices rose 2.1 percent last year — the lowest in five years — workers say daily expenses feel far higher.

Kim Sung-hee, director of the Institute for Industrial and Labor Policy, explained that growing expenses and stagnating income are driving even stable salaried employees into supplemental work.

“The pace of wage growth is not keeping up with the rise in living costs,” he said. “So more workers are adopting the **‘main job plus side job’ model as their default**,” he added, predicting that the practice could lead to a long-term transformation in the labor landscape.

“At the same time, there has been a persistent increase in precarious employment. Society must rethink whether workers are being compensated fairly for their labor,” said Kim.

In fact, 82.5 percent cite the need for additional income, whether to cover daily expenses, save for emergencies or prepare for unexpected costs.

## Lost Faith in Traditional Career Ladders

Experts say the trend also reflects a deeper shift in how young Koreans view work and careers. High inflation, stagnant wages and volatile employment conditions have eroded confidence in traditional career paths.

Surveys show young professionals increasingly reject the idea that climbing the corporate ladder is the only path to security.

According to last year’s survey by local think-tank 20s Lab on 850 office workers in their 20s and 30s, 36.7 percent of respondents said they do not wish to be promoted to a managerial position. Many cited the stress, workload and performance pressure associated with a promotion as reasons for their reluctance.

The apparent lack of desire for more authority at work was found in a 2023 survey of young workers by job-search platform Job Korea. Of the respondents, 54.8 percent said they do not want to be promoted to an executive position.

“Unlike past generations, young workers now know they can earn income outside the office through social media or e-commerce,” said Kim. “**Taking on more responsibility at work is no longer seen as the best or only way to build a stable future.**”

## Seeking Fulfillment Beyond the 9-to-5

For some, the motivation behind side jobs goes beyond financial survival. A growing group of N-jobbers sees multiple jobs as a pathway to self-improvement, personal branding or long-term dreams.

“I realized the company isn’t everything and I needed to invest in myself,” said a 27-year-old professional in Seoul who runs a YouTube channel of some 27,000 subscribers. “My main job alone isn’t enough to prepare for the future. Through my side work, I’m building financial stability and gaining new experiences.”

But the rise of second and third jobs comes at a cost. Young N-jobbers now work an average of 58.7 hours per week, with some clocking nearly 97 hours, according to a report by the Korea Institute of Labor Safety and Health.

Experts warn this could worsen Korea’s already chronic burnout, deteriorate health and weaken family and social bonds.

“Trying to maximize income through multiple jobs reflects anxiety about falling behind in a society where economic power is paramount,” said sociology professor Heo Chang-deok of Yeungnam University.

“Yet long working hours are reducing productivity and straining relationships. We need to examine whether workers’ wages adequately reflect the value of their labor.”

When 30-year-old Kim wraps up her full-time marketing job at 6 p.m., her day is only half finished. Three evenings a week, often including weekends, she rushes

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