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“Zoom Got It Done” is the tagline for the company’s new Zoom Ahead campaign, with the focus being how Zoom’s AI-first capabilities take conversations to completion. This one features Kate McKinnon and builds on their “I Use Zoom!” spot with Bowen Yang that kicked off this consumer-friendly campaign late last year.

For the record, I’m not a fan of their comedic approach here, but the ads hold your attention, and it’s great seeing SNL favorites playing over-the-top corporate tropes. Am just not so sure the messaging gets it done.

Wearing my Marketing hat, I’ll note that B2C marketing campaigns from tech companies are really hard to do well, especially when the audience is not the economic buyer. The Zoom ads are aimed at workers – end users – while the buyers – IT and CEOs – are caricatured as the worker’s worst nightmare.

This is a topic I’d love to explore further, but I need to stay on script and tie their Got It Done tagline to the main topic, namely my review of the recent Zoomtopia event. While the event is mainly for customers and partners, I was part of the small cohort of analysts who attended as well.

Since Zoomtopia caters primarily to those economic buyers, it wasn’t surprising that the Got It Done message was the opening theme for the event, capped by a local choir that went full gospel to celebrate the uplifting power of AI to get work done and relieve us of so many tedious tasks that undermine our productivity. Am not sure if everyday workers get that euphoria when using Zoom, but that’s the aspiration – nothing wrong with that, amen.

Choir singing the praises of ‘Got It Done’

Jon Arnold

More importantly, I think Zoom is trying to communicate how AI is transforming their platform into something bigger than video calls and meetings. On that count, I think Zoomtopia succeeded, perhaps in ways that most people don’t realize. In that context (pun intended), I’ve distilled my takeaways into three big ideas.

1. Unified Context Layer

This was the big story at the event, so let’s start there.

I’m never the first analyst to post about industry events, but I’m going with flow here, as this was the lede most of my peers went with for their write-ups. What I haven’t seen so far, though, is connecting the dots to the last time most of our group was at a Zoom event. That would be Perspectives, their analyst-only event, and back in April we got the deep dive on their go-to-market vision, “from conversation to completion”.

The overall reception was positive, and it marked a new chapter in Zoom’s evolution to align more closely with AI’s transformative potential and get beyond being a meetings platform. Building on the premise that all interactions start with some form of conversation, AI does all the hard work of taking those conversational inputs, identifying next-best actions and closing with intelligent task completion.

At Zoomtopia 2026, the big story was Unified Context Layer, which takes that vision one step further. The missing piece was context, where AI is now better able to understand intent, sentiment, urgency, etc., and connect all that to memory across the entire lifecycle of an interaction. Humans simply cannot do this at scale and in real time, so this is where the AI story becomes next level.

On a more basic level, this is no longer about human-to-human communication, the foundation upon which all UCaaS platforms are built. Communication remains the cornerstone for how work gets done, but now it’s just as much about P2P as it is about P2A, A2P, A2A and B2B. Translation – people need to communicate among themselves, but increasingly it’s also agent-to-agent, bot-to-bot and everything in between. Getting context right is more challenging when AI agents are involved, and that point will tie into my second big theme.

Zoom’s new Unified Context Layer

Zoom

To make all this work, the vision needs to be broader, so now it’s “conversation to context to completion”, and that’s what the Unified Context Layer brings to the Zoom platform. You can read more about it here, and I’ll just add some key points to show why the context piece is so important.

• This new layer takes conversations to completion “by linking conversation history with relevant documents and data”. Nothing really new here – other vendors are doing similar things in an effort to become the central hub through which all workflows go. What is new is how these capabilities are framed to support both actual workers – humans – and AI agents. Not only are these agents doing work and completing tasks on behalf of human workers, but as they become more “agentic”, they’ll be doing these things independently. Definitely not something the founding fathers of UCaaS had in mind.
• To become an enterprise-wide “system of action”, this new layer works across all of Zoom as well as third-party applications. This is necessary for agents to pull context from everywhere and every interaction – humans cannot do this on their own, and when all the integrations are in place, data no longer stays in siloes. Their update notes that with MCP connectors and APIs, Zoom can search across over 40 third-party applications, such as ServiceNow, Workday and MSFT OneDrive. Drawing from such a wide range of sources, workers and the workplace become more productive, and makes Zoom Got It Done more than a marketing slogan.
• It’s worth noting how Zoom identifies two forms of data to understand context at a deeper level – dynamic and static. Dynamic would be human-based, real-time interactions in the workplace – calls, chats, meetings, etc. Since all of these are in digital form now, AI can process them as conversational intelligence inputs to drive task completion. Static data represents what’s on record and documented – also in digital form, so it can easily be mined by AI. Together, this presents a more complete picture for automating workflows.
• The emphasis on AI is hard to overstate, as agentic search capabilities serve to get more complete information – and context – to surface answers faster, so tasks can be completed in less time. For example, one of the new features, My Notes, turns meetings into workflows automatically – something that human workers would have spent a lot of time doing manually. Not only that, but Zoom now has prebuilt templates for specific functions, namely sales, marketing and IT. These workflows can now be created directly in My Notes, without human effort to do this with a workflow builder.
• Another sign of where this is going is the distinction between general and specialized AI agents. Why stop at each worker having one AI agent? Never mind the workers – ZoomMate’s AI Agent Teams now can have a general AI agent manage teams of specialized AI agents, further accelerating the time to task completion. Each agent can be assigned a specific task, so you can now have subagents working in parallel to support the overall task. Humans may think they can multitask effectively – it’s a myth – but this approach is next-level. AI magic aside, it’s important to note that all of this task automation is subject to human review, so it’s too early to think about using this to replace human workers. Sidebar – this is exactly what Kate McKinnon was getting so worked up about in the ad – let’s just call it misplaced Zoom Rage, where Zoom gets it done in ways her workers simply cannot do.

Zoom Ahead campaign featuring actress and comedian Kate McKinnon.

Zoom

2. AI update – aka, the Anthropic effect

I may be going out on a limb here, but Anthropic was barely mentioned at Zoomtopia, and it seems to me this is driving a lot of Zoom’s evolution, perhaps more than we realize.

If you don’t know, Zoom took a small stake in the company in 2025, and has since added to its position. Financially, it’s been a huge windfall for Zoom, but that’s really beside the point. Zoom and all the other cloud players in their orbit cannot afford to not be close to all the AI players in Anthropic’s orbit – that’s just how Big Tech works.

For Zoom in particular, this is about helping transform the company into an AI-first platform, and what better way to do that than by leveraging their small stake with one of the top three players creating the AI economy? In that context – there’s that word again – their “system of action” vision makes more sense. Yes, human workers will use these tools to take conversations to completion, but longer term, this system will be about AI taking the action.

I’ll call this the “Anthropic Effect” because Claude is now deeply embedded in everything Zoom touches – collaboration and meetings with UCaaS, customer interactions with CCaaS and more recently, ZRA for sales automation – Zoom Revenue Accelerator. All of these data flows cross Zoom’s platform, and this is where AI agents need to be to tap into the data that takes conversations to completion.

Memories can be short, but AI Companion was a cornerstone for how workers engaged with the Zoom platform. Yes, all platforms evolve, and AI Companion was quietly retired, replaced – augmented, really – by ZoomMate. AI Companion hasn’t really gone away; it’s just been subsumed by something bigger and more agentic. Perhaps to make room for Claude, or at least get hooks into what their system of action is trying to do.

On a technology level, this is perfectly reasonable. Zoom has actually been at the forefront of innovation in our space, and they have succeeded at just about everything they’ve taken on internally. However, I think it’s fair to say that even Zoom cannot replicate what Anthropic, OpenAI, Meta, et al have been doing with AI.

Depending on how you look at things, I think the business rationale for riding with Anthropic is even stronger. Consider the chart below, from App Economy Insights. They publish a newsletter that breaks down how tech companies make money, and Anthropic’s revenues are up 45-fold over the last six quarters.

Of greater interest, as their newsletter reports, Anthropic has almost 12,000 enterprise customers spending $100k+ annually – exactly the kind of customers Zoom covets. To whatever extent these customers rely on Claude, this sure dovetails nicely with Zoom’s value proposition. Going from conversation to context to completion at scale requires a lot of AI horsepower, and the more tightly Claude integrates with ZoomMate, the more successful both companies will be.

Of course, Claude could fall out of favor, and all of this will be moot, and every other cloud platform player is partnering with Anthropic, so nothing is for sure. That aside, though, this looks like a good way for Zoom to build a moat they can defend, especially as AI gains trust and is used to automate more workflows and tasks. That makes for a good growth story to become an AI-first system of action that truly takes them out of the UCaaS milieu that is going sideways at best.

Anthropic’s revenue growth

App Economy Insights

3. New management controls for AI

Finally, I wanted to note this focus, as it says a lot about how Zoom wants to be positioned, and how they want to be perceived by enterprise IT leaders.

This is a core piece of the story in terms of Zoom becoming an AI-first platform and truly evolving beyond video calls, meetings and UCaaS. Their new management controls are coming soon, but this signals where and how Zoom intends to play.

With Anthropic now in their DNA, these are the capabilities Zoom will need to become a centralized system of action for enterprises. Not siloed for workplace productivity or in the contact center, but to be the hub for all communications flows.

Again, this is no longer a UCaaS story – one could argue that Teams holds court there, along with other leading UCaaS players – and Zoom is looking beyond this and wants to be positioned on a higher, more strategic plane.

In this – yes, context – the Zoomtopia updates were about the things that IT really cares about when managing these do-it-all platforms. This is about enterprise-wide policy and governance, not updating permissions to edit transcripts, configuring new endpoints for meeting rooms or updating CRM integrations.

These are the bigger picture controls that IT needs to be comfortable and confident that Zoom can really be this system of action for the entire organization. To illustrate, here are three examples for how Zoom intends to earn their trust.

• AI guardrails. Allows IT to customize account-level rules for what AI agents can use or generate. These rules can be highly specific for a team, job function, line of business, etc., but always subject to human review (HITL) to keep AI in check.
• Deepfake risk detection. Not a new idea, but as agentic AI proliferates, and as personal AI agents start clogging your digital channels, the threats become very real. When synthetic data is paired with bad actors, deepfakes can find their way into workflows and customer interactions, making this an enterprise-wide challenge to address, and not just limited to the contact center.
• Compliance Manager. With AI-driven outputs turning up everywhere, there’s a need for centralized visibility to remain compliant. Different platforms track communications in different ways, and when it comes to archiving, data retention, search, retrieval, etc., Zoom will soon be adding more compliance tools to support IT at an organizational level.

Conclusion

Zoom executive Q&A with analysts

Jon Arnold

During the executive Q&A with analysts, Eric Yuan was asked where Zoom would like to be in the future, and I think his three-word response sums up everything I’ve been trying say here. He envisions Zoom as a “work operating system”. Not a UCaaS platform, not a meetings app, but something bigger, and more of a hub that enterprises can organize workflows around.

Conversations to context to completion is the path for getting there, but this puts them up against hyperscalers who are all-in with AI, and not terribly interested in the communications layer that got Zoom this far in relatively little time.

Is Zoom ready for this? Will their customers be ready to view Zoom this way? With much of this data residing with third-party apps, who will ultimately control all the data needed to be a work operating system? What role will the hyperscalers and AI majors play? How will their working relationship with Anthropic evolve to support this vision?

These are just a few leading questions to consider following Zoomtopia. Prediction markets aside, I’m more inclined to bet on Zoom than against Zoom, as their track record for making moves has been pretty good.

The management team has both vision and confidence – they know what they have, where they’ve been and where they need to be going – and I’ll try to answer those what’s-next questions as things progress. As with everything AI, they will progress, and Zoom just might get it done; in which case Kate McKinnon’s Zoom Rage will turn up to 11. Can’t wait to see that!

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It’s early days for AI-assisted work, and sentiments are mixed about its benefits: Does AI actually bring value and save employees time, or does it bog them down and add unnecessary activities?

Data from ActivTrak seems to vacillate between those two potential realities: The latest research from the productivity tracking software company says employees who use AI most heavily are working up to 90 minutes longer each day, yet its previous research, published earlier this year, found that they are actually working less.

The discrepancy may be due in part to the timespan and sample sizes of the data collection for the two reports, but it indicates that enterprises should still be wary of vendor claims about AI-related productivity gains. Measuring them remains incredibly difficult.

AI use compared

ActivTrak’s current findings are based on behavioral work data gathered from 9,140 knowledge workers across 467 enterprises over a five month period (April 1 to September 25, 2026). This sample is much smaller than that of its previous report based on 443 million hours of work performed by 163,638 employees across 1,111 organizations over a three year period (January 1, 2023 through December 31, 2025).

According to the latest findings, heavy AI users are working between 8.42 and 9.08 hours per day, compared to 7.58 hours for those not using AI. This contradicts ActivTrak’s previous finding that average workdays had decreased by roughly 9 minutes (a 2% decline) thanks to AI.

On the productivity front, heavy AI users have 22% shorter focus sessions than light users (37.8 minutes versus 48.2), suggesting their work is more fragmented due to AI use; further, they switch apps 15% more frequently.

“Over time, those interruptions add friction to high-value work that requires concentration, critical thinking, and sustained attention,” Sarah Altemus, manager of the ActivTrak Productivity Lab, said in a blog post describing the latest findings.

ActivTrak’s previous report had found that over the period of the earlier study, focus efficiency, the percentage of work time spent in focused, uninterrupted activity, fell to a three year low of 60% with AI use, and average focused session time in 2025 declined by 9% from 2023. However, that same report found that daily productive time increased by 19 minutes, or 5%, to 6 hours and 36 minutes, with AI in the workplace. Furthermore, productive sessions grew by 13%.

The company’s latest report also tracked the productivity differences between users of tools with embedded AI and users of web-based AI tools. Those using embedded AI switched apps 0.6 times an hour, while those using AI on the web switched between 1.7 and 4.2 times per hour. That’s up to 4x more switching than by employees who don’t make use of AI at all, which creates what ActivTrak describes as a “swivel-chair tax” — the additional effort spent by employees due to the movement between apps.

Similarly, in its previous report, ActivTrak had found that this multitasking rose 12%, or 10-plus minutes, with AI.

Interestingly, according to the latest research, light users spend more active work time in core job-specific apps (81.4% compared to 78%).  “In other words, more frequent AI engagement doesn’t necessarily translate into more focused work,” Altemus pointed out.

The larger issue is the way organizations manage the additional capacity that AI may create, Altemus noted. “When employees complete tasks faster, managers may assume they have room for more responsibilities,” she said. Without clear workload boundaries, time savings may be redirected into additional work that can be taxing.

The numbers often don’t tell the full story

ActivTrak has a useful view of how work moves across applications, noted Sanchit Vir Gogia, chief analyst at Greyhound Research, but he also pointed out that it sells the capability that produces these measurements.

Recorded use depends on what the instrumentation can detect, he observed. For example, an employee can use AI at work and still appear in the non-user group, and work on an unmanaged personal device sits outside the measured estate. In addition, an API or a background agent can finish work without producing a desktop session, and passive screen time, an offline meeting captured through a calendar, and paid hours are also different measures. Furthermore, switching apps is easier to observe than switching attention within an application.

Ultimately, he noted, those judging the value of AI need to establish what happened after the first task became faster. “An improvement per paid hour can conceal effort left off the timesheet,” said Gogia. “The [enterprise] board should be able to say whose day improved and whose work made that improvement possible.”

This article originally appeared on CIO.com.

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Microsoft ended mainstream Windows 10 support a year ago, but PC upgrades to Windows 11 have ground to a halt, analysts said.

Relief may not come until 2028 or even 2029, as high CPU prices, which analysts call “chipflation,” and high memory prices, widely known as the “RAMpocalypse” or “RAMageddon,” keep PC prices up.

PC prices were already high, and recent steps like Intel raising CPU prices are increasing the base cost of PCs, said Dean McCarron, principal analyst at Mercury Research.

“When prices are higher, demand goes down. It causes a deferred upgrade cycle,” McCarron said.

Microsoft’s Windows revenue from PC makers fell 27% in its latest quarter, missing expectations, the company’s chief financial officer Amy Hood said on the company’s earnings call last week.

Last year’s rush to upgrade from Windows 10 boosted PC demand, but sales have since slowed, Hood said. PC makers, which pay Microsoft for a Windows license on each PC sold, are also still sitting on unsold stock, Hood said.

StatCounter numbers also show a steady number of PC users hanging on to Windows 10 throughout most of 2026. In September, Windows 10 was still running on 27.7% of Windows PCs worldwide, slightly up from 26.45% in February. That coincided with the PC market crash due to high RAM prices, uncertainty around tariffs, and the Iran war.

Windows 11’s share of Windows PCs jumped from about half in October 2025 to 72.57% in February after mainstream Windows 10 support ended, then dipped to 71.5% in September. (Windows 10 extended security updates are available for both businesses — for a hefty fee — and consumers.)

For enterprises, upgrades are more complicated than making decisions based on price alone, said Neil Shah, vice president of research at Counterpoint Research. Companies in a Windows 10 end-of-support replacement cycle face a conundrum: whether to invest in expensive AI PCs, Shah said.

“All these trends are deflating the demand slowing down the replacement cycle,” Shah said.

Buyers are being prudent about what to buy and when, waiting for better deals and lower prices, which won’t happen anytime soon, Shah said.

A rush to buy PCs ahead of memory-driven price increases boosted PC shipments by 3.2% in the first quarter of 2026, according to Counterpoint. But PC shipments declined 4% in the second quarter and 21% in the third quarter.

Commercial PC replacements and Windows migrations provided some stability to the market, but “was insufficient to offset the broader market contraction,” Shah said. “We…expect a 27% YoY decline in Q4 2026, highlighting the tough market.”

Analysts were split on when PC prices will stabilize, but they agreed it won’t be 2027. Memory prices will remain inflated as long as most of the supply is directed to data centers feeding the AI boom, Mercury’s McCarron said.

Intel in its recent earnings call telegraphed that its PC chip business will remain soft through the rest of 2026 and into 2027. Its lowest-cost PC chip, Wildcat Lake, is sold out.

Supply constraints for memory and PC parts may last through 2029, said Steven Dickens, principal analyst at Hyperframe Research.

“PC vendors are combating this through restricted configurations and bundles,” Dickens said.

AI isn’t yet driving PC upgrades, which are mostly following a typical cycle, Dickens said. But high-end machines capable of running LLMs on-device are starting to shift the market.

“We are seeing power user devices for local LLM deployment becoming a material part of the mix and changing the unit price average as a result,” Dickens said.

At some point, enterprises will have to upgrade PCs, and the market will also turn around, McCarron said. If a soft PC market goes on for too long, “it will turn into a larger boom perhaps a year later,” McCarron said.

“It’ll result in a larger PC upgrade cycle down the road,” McCarron said. “It’s like compressing a spring. The longer you hold it down, the harder it snaps back.”