The Killer App for Generative AI

Exactly two years ago, I published an article about The Importance of Killer Apps. At the time, a new platform technology had just emerged, spatial computing. Remember Apple Vision? That was the hottest tech right before OpenAI launched ChatGPT. I wrote then that no killer app had emerged for Vision, and without one, market success is unlikely.

Today, spatial computing is all but forgotten amid the generative AI gold rush. So, what’s the killer app for generative AI?

Yes, AI qualifies as a platform—it enables countless applications solving a wide range of business and personal problems. But a successful platform needs at least one killer app that drives the platform adoption across many audiences. The truly transformative platforms tend to have several killer apps. Think of the mobile phone: its killer apps include the camera, media players, messaging, and social media. The reason you're willing to spend $1,000 on an iPhone isn’t because of apps like Asana or Conga. It's because you no longer need a separate camera, music player, DVD player, or monthly supply of postage stamps.

So, what’s the killer app for generative AI?

Your first instinct might be to say, “There are thousands!” But if none of them clearly rises to the top, that could be a problem. It suggests that while the new technology is powerful, we're still unclear on why we truly need it or why we should pay for it. Some signs suggest that this might be the current state of the market. Many organizations are experimenting with generative AI out of fear of missing out (FOMO), yet very few compelling business use cases have emerged so far.

The leading contenders

Chatbots are an obvious candidate. Yet those powered by generative AI remain as frustrating to help-seeking customers as the pre-ChatGPT ones. Their primary function is still to deflect inquiries rather than to serve customers, which doesn’t really feel like a “killer app.”

AI-powered search and summarization is another strong area. These tools allow us to ask natural-language questions instead of typing keywords and can synthesize answers across sources. It’s one of my top use cases. Google should be worried. But is that “killer” enough? We’ve never paid for search - would we pay for AI search? I’m not sure.

Content creation also gets mentioned frequently, but that’s too broad to be considered an application. I’m also concerned about the rise of AI slop, mass-produced, low-quality images and videos generated from questionable training data that are flooding the web. The same applies to text content. Don’t get me wrong, I use gen AI for content creation and love it, but it’s becoming clear we’re being buried in AI-generated noise. I won’t get into the legal implications of implicit and explicit copyright violations, but those issues might soon face their judgment day.

Content generation alone isn’t specific enough to qualify as a killer app. Real apps solve specific business problems. I see a lot of promise in use cases like marketing content (blogs, email sequences, sales collateral), customer and prospect communication, memo drafting, business planning, and brainstorming. These are undeniably useful, especially when AI is used as a creative assistant, but the quality degrades quickly when left unsupervised. Creative assistant is a tool, not an application. People pay for tools, but tools don't become killer apps.

Naturally, I asked the AI what it thought could become the killer app. In addition to the areas above, it added a few more: code generation for software development, legal and compliance document summarization, and medical/clinical documentation and decision support.

I like these suggestions because they address real business needs. That’s what defines an app. You can’t be a killer app without being an actual app. These are industry-specific use cases, and I believe the future of AI will be shaped by domain-specific applications. Still, it’s a stretch to say that the legal or medical sectors are driving generative AI adoption, like killer apps would. Code generation might be the closest we’ve come to a killer app, but the millions of ChatGPT users who aren’t coding would probably disagree.

In summary, I don’t believe the killer app for generative AI has emerged yet. But I’m confident it will. Perhaps a new category will evolve, like "personal AI assistants" in the spirit of HAL 9000 or J.A.R.V.I.S. Of course, we’re nowhere near that level of capability. As long as prompt engineering is still a thing, we’re not getting close. Luke Skywalker doesn't have to think about the right prompt structure when he talks to C-3PO.

Until the killer app (or apps) emerges, generative AI will remain in the Trough of Disillusionment on the Gartner Hype Cycle. The Plateau of Productivity seems distant, but the technology evolves very rapidly.

What do you think will be the killer app for gen AI?

Gartner Hype Cycle for Generative AI 2024

Enterprise Content and AI Security

You can’t talk to a business customer today without AI coming up. While most people seem to have embraced the power of public generative AI tools like OpenAI’s ChatGPT or Google’s Gemini, there’s a lot of hesitation when it comes to using generative AI on enterprise content. The one concern that comes up again and again? 

Security.

Rightfully so. Public AI tools don’t have to worry about security. They’re gobbling up all the data on the public internet with the motto: “Train first, worry about intellectual property rights later.” Technically, nothing is stopping them from doing that, and their models are fed by scrapers and crawlers that grab everything they can find.

In an enterprise, however, that doesn’t work. Enterprise data is privileged, confidential, and subject to privacy laws. The data cannot be shared with everyone, and AI models must respect that. It means two users must receive different answers to the same question, depending on the data they’re authorized to access.

The problem is, if your content isn’t well secured and governed in the first place, AI will expose those holes quickly. You may have been able to hide some data behind cryptic file names, but that won’t stop the AI models. Having solid data governance with granular, clean permissions is imperative. Otherwise, it’s “bad security in, bad security out,” to paraphrase Fuechsel’s Law ("garbage in, garbage out").

It also means you need to bring AI tools to your content rather than trying to bring your content to the AI tools. It’s hard enough to secure your content in the first place, and the idea of copying a snapshot into a separate container for AI would obliterate any of that security.

Don’t expect public AI vendors like OpenAI, Google, Anthropic, Meta, or DeepSeek to solve this problem. Enterprise content is a different animal—one they neither understand nor care to understand. None of these vendors has any enterprise DNA. Security is not their concern, and their models aren’t built with the assumption that data access should vary by user.

To illustrate this point, let me remind you of what happened with enterprise search. Web search, which we all use many times a day, is based on an index created by crawlers that scour the internet to deliver the best content match for your keywords—the same results for everyone. That’s what Google does in simplest terms. But in the enterprise, that approach doesn’t work. Enter enterprise search.

About 20 years ago, Google—the heavyweight search champion—entered the enterprise search space with a bright yellow, rack-mounted Google Search Appliance, drawing a lot of attention with its promise that managing content wasn’t necessary: "Wherever it is, you can find it with Google". Or something like that.

It sounded great—except it didn’t work. Google eventually discontinued the product after a decade of trying. Interestingly, other major players in enterprise search met similar fates. There was FAST, which Microsoft acquired in 2008—only to discover a year later that FAST had been cooking the books. And then there was Autonomy, which HP acquired in 2011, only to eventually sue the CEO and CFO for—you guessed it—cooking the books. The Hollywood-worthy Autonomy saga ended with the CFO in jail and the CEO dying in a freak boating accident. (I described that story in more detail last year in “Mike Lynch, Autonomy, and Incredible Coincidences”.)

Today, search is provided by the companies that own the data. Enterprise search is hard, and usually, only the company that built the repository has a chance of doing it well. On the web, Google finds content that wants to be found—literally. Millions of companies spend billions of dollars each year on SEO to make their content easily discoverable. And there’s no security to worry about.

Enterprise content is different. It’s not optimized for search engines, and security is not optional. This is hard to get right. Eventually, the open-source Apache Lucene solved the problem well enough, and that’s what many enterprise applications use today. Still, you rarely hear anyone say, “Wow, this search is amazing”—because it doesn't match Google’s web search, which sets the expectations bar.

Now, let’s come back to AI. The vector databases at the heart of enterprise AI models must respect data security, just like search indexes do. That’s incredibly difficult for anyone other than the companies that hold the data. Only they understand the data structures, the users, and their permissions. For any external application, sure, it’s possible, but it's really hard to make that work. If you don’t believe me, think back to enterprise search.

AI in the context of enterprise data will be extremely valuable, with the potential to dramatically boost productivity—whether it’s through assistants, agents, or whatever comes next. But in an enterprise, the first rule will always be: respect the data’s security. 

And that makes it hard.

Ode to the Desktop

Blame Google. Actually, blame Microsoft. The idea sounded great, but the consequences? Unintended. They slow you down. They limit your skills. They force you into a world of mediocrity.

I’m talking about using applications in a browser.

Now, I don't mean any application. There are many types of applications that work well in a browser. For example, process and transactional applications like CRM, Spend Management, and Project Management work just fine in a browser.  In fact, having a browser UI eliminates the need for a client installation, which is a big part of what makes cloud applications appealing. 

Many other types of applications like monitoring, analytics, and reporting also work well in a browser. But the applications that don’t belong in a browser are authoring applications; the types of applications in which you are creating or editing content. Yet, they seem to be very popular.  

Google started it.

For decades, authoring was done in desktop applications like Word or Excel. Then Google introduced its application suite as browser apps in a frontal attack on Microsoft.  Google first launched Docs and Sheets back in 2006 after acquiring Writely and XL2Web. Google Slides was added in 2012. At the time, Microsoft was going through the rough patch of the Balmer era, being attacked on many fronts (and losing), including desktop OS, mobile OS, browser, ...and office suites. Seeing an opening and being flush with cash from its money-printing ad business and the 2004 IPO, Google succeeded where several companies failed a decade before, including Borland, WordPerfect, Lotus, and IBM.

And succeed Google did, especially after cleverly combining the browser applications with Google Drive in 2012. Google Apps, now called Google Workplace, quickly became a serious alternative to Microsoft Office which until then had a virtual monopoly on office applications. The pressure forced Microsoft to counter the way Microsoft always does – by doing the same and making it free. 

Microsoft joins the bandwagon

Microsoft introduced its Office Web Apps in 2010 and later renamed them Office Online, Office 365, and eventually Microsoft 365. The rest is history and browser-based authoring apps from Google and Microsoft are everywhere. Microsoft also introduced SkyDrive in 2007, eventually renamed to OneDrive, which is also integrated with MS365 just like Google Drive. The “free” strategy didn’t work that great against Google, which made Workspace free as well. According to Statista, Google supposedly owns 44% of the market share for office suites, while Microsoft 365 owns 30%.

Browser applications have many benefits. They require no installation and the installation with cloud drive makes working in the cloud easy. Kids use them in school for their projects and, consequently, Gen Z seems to prefer them over desktop apps. Google introduced real-time co-editing in 2006, which enabled new ways of team collaboration that weren’t possible in Microsoft’s suite until 2015. Other benefits are enjoyed by the IT departments such as low cost of administration, high scalability, and solid security.

However, browser applications have significant drawbacks. 

For one, they require a browser to operate. Browsers are designed for viewing web pages, not to run authoring applications. This has some repercussions. For one, a browser is designed to browse the Internet. But when there is no Internet, there are no applications to work with. Losing power is not that uncommon even in Silicon Valley and while your laptop might have plenty of battery charge left, you have no apps to work with.

Another issue is related to opening multiple documents at a time. As document sharing via a link is very easy in a browser, every time you receive a link, you click on it and leave it open to get back to it later. Before you know it, you have a hundred tabs open, each consuming 300 MB of memory. Your laptop gets slower and slower and eventually your browser might crash.

Most importantly, the browser apps only come with a subset of functionality compared to the desktop apps. Don’t believe for a second that browser-based Word or Photoshop are the same as their desktop counterparts. In MS365 alone, you will find many limitations in formatting, shortcuts, performance, data sizes, data modeling (Excel), embeddable objects, customizations, add-ons, macros, and more. 

Similarly, Adobe’s Photoshop for the Web is a highly simplified version of the desktop application. That's why many applications like Adobe Premiere Pro or Autodesk’s AutoCAD don’t even exist as a web version. These applications are built for complex authoring workloads that the users are unlikely to ever perform in their browser. 

The pros use desktop applications

That’s at the heart of the matter. Browser authoring is good enough for light workloads like writing a memo, updating an Excel table, or adjusting image contrast. But for more serious workloads that involve heavy formatting, large data sets, macros, or specialized add-ons, desktop applications are the only choice. The users get trained in using PowerPoint, Excel, Photoshop, or AutoCAD. In fact, they take great pride in how well they master these applications. There are entire industries built around making such professional users more proficient.

You might argue that 80% of all workloads are quite simple and the web applications are perfectly good for that. But I disagree. You don’t become a faster runner by running slow. Professionals go through training to learn their tools of trade. They become proficient in using shortcuts. They seek ways to learn better ways of using the apps. They explore the latest innovations and add-ons available for their applications. They challenge each other to push the limits of their tools. Pros want to run faster. 

And that’s only possible when using desktop applications.

My Take on the Zuora Acquisition

On October 17, 2024, Zuora announced its acquisition by Silver Lake, a private equity firm, for a total of $1.7 billion. The acquisition was not unexpected. My former employer had already announced on April 17 that it was “exploring strategic options, including a sale”. The buyer was also not a surprise, as Silver Lake had already invested $400 million in Zuora on May 9. Acquiring the remainder of the company cost them only $1.3 billion. 

What is surprising is the price. 

The offer of $10 per share represents a meager 6% increase above the previous day's closing price of $9.42. Yikes! As a shareholder who has been holding underwater shares from an ESPP purchase over 3 years ago, I find this quite disappointing. Sure, you might say that an ARR multiple of 3.7 is what PE companies pay (Zuora expects to make $455.5-461.5 million this year). But that doesn’t make it any better for the investors. The stock closed at $9.91 on Friday which signals that many other investors are unimpressed. 

How did Silver Lake manage to secure such a lucrative deal? 

Zuora pioneered subscription billing and remains the company to beat in this space. It boasts an impressive roster of customers, a highly knowledgeable team, and a broad range of capabilities that none of its competitors can match today. Yet, Zuora’s stock has remained stuck in single digits for almost three years, with no upward movement. 

This stagnation isn’t due to poor execution. The management team has lately consistently exceeded earnings expectations quarter after quarter. The issue wasn’t execution—it was strategy. 

A subscription billing platform operates between orders, payments, and the general ledger—in other words, between CRM, payment processors (PP), and ERP. These are Zuora’s strategic touchpoints; its inputs and outputs. When Zuora first started, it was the only game in town. However, today, all those vendors have added subscription billing capabilities, which puts pressure on the demand for Zuora. Salesforce (CRM), MS Dynamics (CRM), Stripe (PP), Gotransverse (PP), SAP (ERP), and NetSuite (ERP)—they all offer subscription billing today and they don’t need Zuora. 

When you’re being squeezed by all your strategic touchpoints, you must find a way out. One strategic option is to push back by adding capabilities that encroach on their turf. That’s what Zuora did by introducing solutions like CPQ, payment recovery, and revenue recognition. Unfortunately, this fragmented approach didn’t succeed, especially when facing much larger competitors like Salesforce, Stripe, SAP, and Oracle. In such situations, the next strategic move is either to find a new direction for expansion—which, arguably, wasn’t available—or to specialize. 

That’s exactly what Zuora did by deepening its focus on the manufacturing and media sectors. It even acquired a paywall vendor Zephr to strengthen its media solution. However, most manufacturing companies are not good at selling software or data subscriptions, and most media companies already know how to do subscription billing and deal with more existential problems. Focusing on verticals was the right move, but Zuora probably chose the wrong ones. It’s easy to critique in hindsight, but selecting other verticals like insurance, financial services, healthcare, or utilities might have been a better strategy for verticalization. Maybe. 

In the meantime, Zuora began missing out on many software market opportunities, while software is the largest market for subscription billing. Software companies need billing solutions from the early stages as tiny startups, but Zuora’s platform, designed to handle some of the most demanding enterprise billing scenarios, is too complex for startups. What these companies are looking for is a simple billing solution that can be integrated with just a small snippet of code, like the solutions from Stripe or Metronome.  

Zuora was also slow to respond to the rise of usage-based billing, which is a hot topic these days. Whether usage billing is the future remains to be seen, as most customers seem to hate it. However, its emergence created an opening for upstarts like Metronome, Orb, M3ter, and Tioga—the latter eventually acquired by Zuora. Unfortunately, that move came too late to make any significant impact. 

Moving down-market is nearly impossible for an enterprise software vendor; it’s difficult to simplify software built for large enterprises (the opposite is somewhat easier). Acquiring an SMB vendor to target the SMB market was likely not an option for a relatively small publicly traded company with not that much cash on hand. It seems like Zuora wasn’t left with many strategic alternatives here. However, failing to act quickly enough on usage-based billing was another key strategic misstep. 

Out of strategic options, Zuora publicly put itself up for sale. Silver Lake quickly seized the opportunity with an initial investment, and since no strategic buyers emerged, Silver Lake ended up acquiring the entire company a few months later. The modest 6% premium reflects the strategic predicament Zuora found itself in. Silver Lake got a good deal, and now Zuora will need to figure out its strategy under private equity ownership, which is not known for fostering growth through innovation investments. 

I wish Zuora well. It’s a great company that stands as a shining example of category creation, thought leadership, and solid execution. However, I’m unhappy about the stock price. 

Why I Joined Egnyte

Yes, after two years of working on my own as an independent consultant, it happened. One of my clients made me an offer to join their company, and I decided to take the leap. Why did I do that? 

"Lubor, I thought you were done with this space!" said Marko Sillanpaa from Gartner when I joined a recent briefing. Marko and I go way back to our Documentum days. 

Well, it’s true. After spending nearly 15 years in content management companies like Vignette, Documentum, and OpenText, I was starting to get bored. For years, I had been trying to convince customers to manage their content to avoid compliance, governance, and litigation risks. But, aside from companies in highly regulated or litigious industries, most didn’t care. 

Things became even clearer when the new upstarts began pushing Enterprise File Sync and Share (EFSS). In the spirit of "consumerization" and "enterprise 2.0", they claimed that IT was becoming irrelevant, and many companies decided to stop worrying about how their content was managed. Employees were indiscriminately sharing files straight from personal drives. It was madness, but I knew it would take time for people to realize that. 

So, I left the enterprise content management (ECM) world and ventured into business applications, to finally get the experience of marketing to business buyers. Funnily enough, the companies I worked for had a horrible way of sharing and managing content. Their content chaos was a massive productivity drain, and they didn’t even know about it. 

But, I kept an eye on the content platforms. 

For a while, it seemed like nothing would change. Most of the old vendors faded away, and EFSS 'boxes’ became just as boring once they started selling to enterprises. They kept talking about compliance on and on, but no one cared. Content was seen as more of a liability than an asset, with "secure collaboration" being the most exciting positioning they could muster. 

Then, generative AI arrived. 

It quickly became clear that while ChatGPT is awesome, for business use, it needs to work with a company’s private, often sensitive, content. That changed the game for content platforms since they own the content repositories. Even if a lot of content still lives in personal drives, content management suddenly matters again. The focus shifted from reducing risk to boosting productivity. Now that’s cool—AI used for something truly useful! I want to be part of that. 

When I started working with Egnyte as one of my clients, I found a company with leading-edge cloud technology, with all the bells and whistles you’d expect from a modern content platform. Unlike EFSS vendors, Egnyte has always focused on control and security, eliminating duplicates, data leaks, and privacy issues. This becomes crucial when applying generative AI to private company content. Random duplicates can lead to incorrect answers, which isn’t acceptable in business. Egnyte figured this out long ago. 

On top of that, Egnyte has powerful and unique capabilities for managing highly complex content with massive files like CAD files, BIM models, and Adobe creative projects. I saw a company with amazing technology, strong prospects, a great team, good culture, and solid financials. I knew I could make a difference here. So, I said yes.  

Yes, I’m running product marketing again, which is what I love. I’m diving deep into the technology, working closely with product teams, and using all my marketing craft to tell Egnyte’s story. There’s a lot of work ahead, but the opportunity is huge.

I’m excited to be back in the content management space. It’ll be fun reconnecting with industry analysts like Marko Sillanpaa, Cheryl McKinnon, Craig LeClair, Marci Maddox, Alan Pelz-Sharpe, Dan Lucarini, and others. I might check in with AIIM, where I served on the Board for five years, to see what they’re up to. And I’m really looking forward to meeting with customers in person. 

It’s great to be back. We’re just getting started!