Is $30/Month for Office 365 Copilot Too Much? When and Why

How much incremental value do subscription-based generative artificial intelligence models have to provide to be viewed as reasonable by business users? In other words, if an Office 365 subscription costs X, is an Office 365 Copilot subscription worth 2X, and if so, for what percentage of users at a firm?

In many cases, the value assessment will come in the form of estimated “time saved” metrics, which will vary based on job roles. One study conducted for the Federal Reserve Bank of St. Lous suggests that “among workers who used generative AI in the previous week (21.8 percent of all workers), between six percent  and 24.9 percent of all work hours were assisted by generative AI, for example. 

But usage varies by role. “Among all workers, including those who used it only in the previous month and non-generative AI users, we found that between 1.3 percent and 5.4 percent of total work hours were assisted by generative AI,” the study authors note.

Keep in mind those are end user estimates, with the imprecision that likely includes. But it might be reasonable to note that, at this time, perhaps only 20 percent of a firm’s entire workforce might actually be routinely using generative AI, for example. And those use cases might represent less than five percent of total work hours. 

There are some use cases where value is easier to grasp. Customer support agents might save 19.7 hours monthly with a 14 percent productivity boost, while programmers could save 44.8 hours with AI coding tools cutting time by 56 percent for half their tasks. The value added is calculated as time saved multiplied by the user's hourly rate (e.g., $20–$100/hour), according one McKinsey estimate. 

Much hinges on the assumed hourly labor rates. For example, we might assume $20 for customer support, $50 for general professionals, $100 for high-skilled roles. 

Perhaps the business case is easiest for roles including customer support and coding. It might not be so clear for many other roles. If “time saved” is usefully captured, customer service and coding use cases might justify significant per-user monthly subscription fees. 

Application/Use Case	Estimated Time Savings per Month (hours)	Assumed Hourly Rate ($/hour)	Value Added per Month ($)	Per-Seat Cost Range ($ per Month)
Customer Support	19.68	20	393.6	Up to 394
Programming	44.8	50	2,240	Up to 2,240
General Professional	9	50	450	Up to 450

Of course, you know the drill. As much as proponents and suppliers use such metrics, few customers actually believe the claims. 

 if a feature costs $30 per month and saves nine hours monthly for a user earning $50 per hour, the value added is $450, making the cost reasonable, with the unstated assumption that the saved time is put to some other productive use. If not, the “savings” might be questionable. 

It’s sort of the same exercise we might make when looking at work-from-home productivity. Assume WFH leads to a given worker’s ability to complete the standard “in office” work load in half the time. The firm gains if that time, or some of it, is redeployed for other outcome-producing activities. There actually is no firm gain if the employee simply uses the free time for non-work activities. 

A Thomson Reuters report suggests AI could save a professional four hours a week now, and perhaps up to to 12 hours per week within five years.  But it matters where those time savings are used. 

Consumer users might have a harder time justifying a subscription fee for AI-enabled apps. Few of us would claim language model features increasingly available to work with any existing major platform provide some value, some of the time, whether that is search, customer relationship management, e-commerce, communications, social media or productivity suites. 

For products based on advertising, transaction or pay-per-use models, perhaps the incremental value can be relatively low, so long as the incremental cost (time, attention, clutter or out-of-pocket fees) are low enough. 

That probably is not true for subscription revenue models, though. And that might be a growing issue for subscription-based products where the AI features are offered as an incremental “premium” price to existing subscription products. 

That might be a key issue for some products including Office 365 or other subscription-based products whenever the incremental value of the AI add-on effectively doubles the price “per seat” or per user, since many of us would not see the incremental value of the integrated AI as 2X. 

There is value, to be sure. It is often helpful to have the AI summarize and “take notes” of a videoconference; summarize key points of a document; draft email responses or generate graphics from a spreadsheet. Other functions, such as creating presentations, might yet leave much to be desired. 

But the point is the value-cost evaluation. How valuable are the capabilities; how often are they used and and how do those outcomes compare with the cost of having them, at this point in time? Which workers actually benefit most, and which benefit rarely? 

At least so far, reasonable people might agree that, generally speaking, the value of embedded AI features often is not 2X. But is the reasonable business case 0.2X or 0.1X or some other percentage in some cases, but 0.5X in some cases? 

And whatever value estimation we might make at this point, will perceptions change in the future if more-compelling capabilities are added?

Lower Home Broadband Speeds Correlate with Economic Growth; High Speeds Less So

Though the relationship between home broadband speed tends to be correlated with economic growth (the two tend to be found together), the relationship seems a bit non-linear. 

In other words, though the availability or non-availability of home broadband might be more correlated with economic growth, higher speeds seem less correlated. 

Title	Date	Publisher	Key Conclusions
Impact of broadband speed on economic outputs: An empirical study of OECD countries	2014	ideas.repec.org	The study found a positive contribution of broadband speed to economic outputs like GDP, but the effects were greater in lower-income OECD countries. It does not explicitly confirm linearity but suggests a positive relationship.
Is faster better? Quantifying the relationship between broadband speed and economic growth	2014	ScienceDirect	This study aimed to quantify the effect of higher broadband speeds (10 Mbps vs. 25 Mbps) on economic growth rates in U.S. counties. It found no significant economic payoff from the speed difference, suggesting that the relationship might not be linear or significant at higher speed thresholds.
The economic impact of mobile broadband speed	2014-2019 data	ScienceDirect	Using panel data from 116 countries, this study found that a 10% increase in mobile broadband speed was associated with a 0.2% increase in labor productivity with a one-year lag, but only in non-OECD and low-income countries. This indicates a potentially non-linear relationship, as effects were not robust across all countries.
Broadband Infrastructure and Economic Growth in Rural Areas	Not specified	ScienceDirect	The study suggested that the economic impact of broadband might be more significant at lower speeds (below 10 Mbps), with higher speeds showing small and statistically insignificant effects, implying a non-linear relationship.
Broadband׳s contribution to economic growth in rural areas: Moving towards a causal relationship	Not specified	ScienceDirect	Here, the focus was on adoption rather than speed per se, but it noted that economic benefits might plateau or show diminishing returns beyond a certain speed or adoption level, hinting at a non-linear relationship.
Socioeconomic benefits of high-speed broadband availability and service adoption: A survey	Not specified	ScienceDirect	The findings indicate that socioeconomic benefits might show diminishing returns as speed increases, suggesting the relationship between speed and economic outcomes is not strictly linear.

In fact, the correlation might be inverted as well: higher economic growth creates demand for home broadband. For that matter, there also are correlations between demand for home broadband and income; wealth and educational status. 

Study Title	Published	Publisher	Key Conclusions
"Exploring the Relationship between Broadband and Economic Growth"	2016	World Bank	Analyzed the bidirectional relationship between broadband and economic growth, suggesting that while broadband penetration can boost GDP, economic growth also increases demand for broadband services. documents.
"Broadband for all: charting a path to economic growth"	2014	Deloitte	Found a strong correlation between broadband availability and economic growth, indicating that as economies grow, there is an increased demand for higher broadband speeds and better infrastructure.
"The benefits and costs of broadband expansion"	2020	Brookings Institution	Discussed how economic growth leads to increased broadband adoption, as higher income levels and business expansion drive the need for improved digital connectivity.
"Mobile broadband drives economic development"	2019	Ericsson	Highlighted that economic development spurs demand for mobile broadband services, as growing economies require enhanced communication infrastructure to support business and consumer needs.
"Global Connectivity Index"	2023	Wikipedia	Indicated that nations with higher GDP per capita tend to have greater broadband penetration, suggesting that economic prosperity increases the demand for broadband services.

Home Broadband Capacity Might Not be the "Problem" We Sometimes Think

“How much bandwidth do you need?” is always a complicated and subjective matter. But some studies might suggest that consumers “need” far less than internet service providers often suggest. 

Some older studies suggested that having access at relatively moderate speeds (25 Mbps to 30 Mbps) does correlate with productivity. Over time, those minimums arguably have increased. 

It appears to be much harder to show correlations at higher speeds. 

And for consumers, “productivity” might not be the best metric. “Value,” as in the ability to enable video or audio streaming or gaming, might be the more-relevant measure. And even there, “speed” might be less important than data allowances. 

For businesses, higher speeds also might not correlate so directly with value. Productivity gains often depend on how the bandwidth is used. In other words, some entities seem to be better at wringing value out of the access because their business processes are more developed. 

Study	Context	Speed Threshold	Findings on Productivity Effects Beyond Threshold
Rohman & Bohlin (2012)	OECD countries	~10 Mbps	Doubling speed had a diminishing GDP impact (0.3% growth); higher speeds showed smaller, less consistent gains.
Whitacre et al. (2014)	U.S. counties	~25 Mbps	Speeds above 25 Mbps had inconsistent effects on employment/business growth, especially in rural areas.
Briglauer et al. (2021)	German counties	~50 Mbps	Beyond 50 Mbps, productivity effects were uncertain, varying by sector; no uniform gain across firms.
Lobo et al. (2020)	Rural Missouri, USA	~100 Mbps	No clear productivity boost in employment/education/health; benefits skewed to quality-of-life, not economic.
Akerman et al. (2015)	Norwegian firms	~10 Mbps	Speeds above 10 Mbps showed uneven productivity gains, limited by worker skills rather than bandwidth itself.

Does AI Make Us "Dumber?"

Does artificial intelligence make its users dumber or less capable of critical thinking? Does AI-assisted writing make us less-capable writers? 

 

Lots of observers already note the increase in volume of AI-assisted writing we encounter daily. That isn’t too surprising. Commercial speech (advertising, marketing, workgroup communications) obviously benefits from AI use. 

It is not entirely clear to me that this is a big concern. Who cares whether bots or humans are creating advertising copy, really? Perhaps we care more whether co-workers can express themselves clearly, but again, it might not be a big concern if AI helps them make their points faster, more succinctly, and more clearly. 

Likewise, it might not be so clear whether we worry too much about ways AI can clarify non-fiction and instructional text, since the pont there is to transfer information or knowledge. 

AI might be more of an issue in some other fields, such as fiction writing, or script writing or poetry and so forth. 

Sometimes (perhaps often), that trend also is said to imperil writing skills, and that remains open to debate. But we might miss some of the countervailing matters. 

I spent much of my career as a journalist or analyst required to do lots of writing. And while I would agree that AI might help me when producing analytical text, such as final reports to customers or market studies (saving me the time of writing), I actually disagree that AI provides the same level of help in a journalist role, for example. 

Many journalists write because they enjoy writing. Producing content one does not write does not provide satisfaction. So it makes no sense to stop writing and lte AI do it. It’s kind of analogous to a painter allowing AI to produce a picture. It isn’t the same subjective value.

If one enjoys playing music, then having AI produce music is fine for some purposes, but does not replicate the “joy of playing music.” 

To be sure, perhaps most of our music, visual arts and text creation is harnessed to commercial purposes, and there is a bigger argument to be made that AI offloads work in such contexts. 

But “creatrives” often enjoy the process of creation itself. AI is no threat to those activities. When the “purpose” of painting, singing, playing instruments, writing or other creative pursuits is the inherent joy of doing so, AI is not going to stop people from doing so.

Will Telcos Prove Better at AI Innovation?

Here we go again: telco leaders are talking about how they might use artificial intelligence to create new or bigger roles as solution providers for enterprise customers. Perhaps they should be applauded for trying to innovate. 

On the other hand, past efforts for decades have generally failed to get traction. The laundry list of reasons always includes inability to move fast enough; inability to scale, probably because the innovations are not a core telco competency. 

Oh, and let’s not forget that few enterprise customers seem to look to telcos for such solutions, as they rarely are “best of breed.”

Over the past couple of decades, for example, “telcos” have tried to gain traction in any number of areas, largely without success. 

Telco Initiative	Description	Reason for Lack of Success
Telco Cloud Services	Many telcos attempted to compete with AWS, Azure, and Google Cloud by offering cloud computing and hosting services.	Lacked scale, ecosystem, and expertise compared to hyperscalers; enterprises preferred established cloud providers.
IoT Platforms	Telcos tried to build and sell proprietary IoT platforms for enterprises.	Struggled against specialized IoT providers; monetization limited to connectivity.
Edge Computing Services	Aimed to offer low-latency computing solutions at network edges.	Market adoption slow; enterprises preferred cloud-based edge solutions from hyperscalers.
Mobile Payments (Telco Wallets)	Many telcos launched mobile payment and digital wallet solutions.	Banks, fintech firms, and tech giants like Apple and Google dominated the space.
Unified Communications as a Service (UCaaS)	Some telcos attempted to create UCaaS solutions for enterprise collaboration.	Slack, Microsoft Teams, and Zoom captured the market.
Enterprise Security Solutions	Telcos tried to offer managed security services beyond network security.	Cybersecurity specialists (Palo Alto, CrowdStrike, etc.) provided better solutions.
AI-Powered Customer Engagement Platforms	Efforts to develop AI-driven chatbots and automation for enterprises.	Enterprises preferred AI solutions from CRM providers like Salesforce and Zendesk.
Blockchain for Enterprise	Some telcos explored blockchain-based business solutions.	Failed to find compelling use cases beyond experimentation.
Industry-Specific 5G Solutions	Telcos promoted private 5G networks for industries like manufacturing and healthcare.	Adoption slow; enterprises hesitant due to costs and complexity, Wi-Fi 6 remains a strong alternative.

If you wanted to go back further, in the 1980s and 1990s, telcos also tried to enter many new “up the stack” businesses, without notable success. 

Telco Initiative	Era	Description	Reason for Lack of Success
Videotex & Interactive TV	1980s	Telcos attempted to provide interactive information services (news, shopping, banking) via phone lines.	Outcompeted by the internet and early web browsers; lacked compelling content and user adoption.
ISDN as a Business Communications Standard	1980s-1990s	Telcos pushed ISDN (Integrated Services Digital Network) as the future of business telephony and data.	Expensive, complex, and slow adoption; DSL and Ethernet-based broadband became dominant.
Telco-Run Online Services (e.g., France’s Minitel, BT’s Prestel, BellSouth’s Interchange)	1980s-1990s	Early telco-operated online platforms offering directory services, messaging, and commerce.	The rise of the open internet and web browsers (e.g., Netscape, AOL) made closed telco systems obsolete.
Telco-Owned PC & Business Computing Services	1980s-1990s	Some telcos (e.g., AT&T, BT) tried selling PCs and IT services directly to businesses.	Lacked expertise and faced competition from specialized IT firms (IBM, Microsoft, Dell, HP).
Telco Private Networks Competing with Enterprise LANs	1990s	Telcos promoted managed private networks as alternatives to on-premises LANs.	Ethernet and local networking equipment (Cisco, 3Com) became the preferred standard for enterprises.
ATM (Asynchronous Transfer Mode) for Business Networks	1990s	Telcos tried to make ATM a standard for enterprise networking and broadband.	Too costly and complex; Ethernet and IP-based networks dominated.
Telco-Controlled E-Commerce Marketplaces	1990s	Some telcos attempted to build proprietary online marketplaces for businesses.	Amazon, eBay, and other internet-based platforms grew faster and were more user-friendly.
Telecom-Managed Email and Messaging Services	1990s	Telcos tried offering enterprise email and messaging solutions.	Microsoft Exchange, Lotus Notes, and later, web-based email services (Hotmail, Yahoo) won out.
Early Telco Cloud & Data Hosting Services	1990s	Telcos experimented with hosting business applications and storage.	Poor execution, lack of scalability, and competition from early web hosting companies.

Perhaps it will be different this time. But history suggests just how difficult the task will prove.