Google has created some of the most successful consumer AI tools in the last two years. NotebookLM, Gemini, Google Opaland a handful of others are on the list of products that advance what consumer-facing AI can do for research, learning and creative work. Each solves a fundamental problem that competing tools don’t, or rather, solve less elegantly.
The problem is that Google has no clear vision or direction for these very useful tools. NotebookLM now has millions of users globallybut spent years in obscurity before becoming mainstream. On the other hand, Gemini Omni, the latest and perhaps most powerful consumer video creation model, is marketed to make TikTokers look like Disney characters on social media. Google Opal launched with such a vague positioning that a significant portion of its target market is unaware of its existence. It’s unfortunate, especially given the transformative potential these tools have in the right workflow, and I’ve had the chance to experience this firsthand in my experiences.
But Google thinks it’s better suited for making TikToks and reels
Gemini Omni has long been the most capable free video creation platform that consumers have ever had access to. Before its arrival, AI-generated video was anything but mainstream and limited to a set of YouTubers with an appetite for niche video creation. OpenAI’s now-defunct Sora attempted something similar, but its access was locked behind a paywall that discouraged casual users, and the quality ceiling never warranted paying a premium in the first place. Gemini Omni achieved two major milestones, first by making the entire category free, and second by making it immediately available to anyone with a Google account.
Simply because Omni inherits Gemini’s understanding of “world history, science and math” and builds on that breadth during the generation process makes it unlike any other consumer-facing video-generation platform on the market. Over the past few weeks, I’ve been using it to create cinematic product visualizations. clay-style explainers of complex concepts I bring static sketches that I’ve made into fully animated clips like Einstein’s theory of general relativity and even the work of a small production studio. Clearly, the use cases practically write themselves.
For marketers brainstorming ideas around advertising, educators trying to make learning more visually interactive, researchers communicating findings to lay audiences, or learning and development professionals creating training materials that won’t put you to sleep in the first ten minutes, Omni offers a starting point that didn’t exist a few months ago. However, none of these use cases appear anywhere in Google’s marketing materials. In fact, the closest Omni’s landing page comes to identifying them is a link to “creators,” which appears to be shorthand for the social media variety.
Google Opal brings smart automation to non-coders
And he wants nothing in return
Google Opal came out of Google Labs, the same group responsible for NotebookLM. That should tell you something about the design philosophy from the start. Where Opal most clearly succeeds is in its ability to visualize workflows, specifically allowing users to “describe” what they want the process to do in simple, natural language and watch it assemble into a coherent, editable workflow on screen. The interface then translates the instructions into a visual graph and provides the user with an automated workflow that makes every other automation tool feel obsolete by design.
The moment I used it, I immediately knew who it was intended for. Opal is designed for people who want to use automation without ever needing to write a PowerShell script. accept a local agentor use Claude to train agents and sub-agents. When using Opal, I think of university professors who want to organize their course materials and assessment criteria, accounting professionals who want to simplify their reports, data analysts who want to bring more structure to their analytics pipeline, and students who are simply working on literature reviews and dissertations.
The value proposition it offers to non-coders is incredible, and the fact that it’s simple and free to use multiplies that benefit tenfold. However, every time Opal coverage comes up, the overwhelming response from users points to discovery rather than recognition. This is a really disappointing product with its marketing, in fact, it doesn’t even exist.
Google continues to understand its products
Brilliant engineering, mind-boggling placement, every time
Google Opal is designed to be kind to those who can’t code, and in the process solves a very pressing problem: alienation. I say “expropriation” because existing tools have done exactly this by requiring a prerequisite skill that the user has neither the time nor the resources to acquire. The entry barrier is also not visible. With just five minutes and a few natural language prompts, I was able to build a narrative analysis tool, a thematic analysis engine, “communicate” the two, and create reports that would otherwise take my time.
Likewise, Gemini Omni has been instrumental in democratizing video production in a market where there are no other user-friendly (and dare I say, usable) alternatives for those without native AI expertise or hardware. Experiencing the Omni’s ability to quickly infer text, audio or images from a subject matter expert’s perspective, there’s a huge gulf between what the model can do in the right hands and what Google has shown the world to be big enough to classify it as a strategic failure.
While there are solutions, Google doesn’t know who needs them the most
Of course, there is an undeniable economic and accessibility incentive for lay communities to use these tools. Access to automation in institutions such as universities and schools, as well as public health, has always come at a large cost and with large lead times, as it requires capital expenditure primarily on contracts (provided such contracts are negotiated in the first place) and then their integration and delivery. Because this scale of automation requires expert teams to build and deliver, most organizations tend to take advantage of tools long after the paradigm has advanced, and sometimes not at all. Despite having the tools to change the paradigm and make progress in these communities, Google seems to have a rather narrow view of what its tools can deliver.
