This week, YouTube unveiled a powerful lineup of AI tools designed to help creators and marketers transform raw recordings and content ideas into polished Shorts, globally accessible clips and optimized campaigns. 

Over half of global marketers now depend on YouTube 

With over 2.5 billion users logging in each month, YouTube has become a central hub for online search, content discovery and powerful marketing impact. For businesses, that means unmatched visibility and flexibility: whether you’re chasing viral reach with Shorts or telling a deeper story through long-form podcasts, YouTube gives you direct access to a global audience at a scale few channels can rival.

This January, a Statista survey revealed that 60% of marketers indicated they were planning to ramp up their organic use of YouTube this year. According to Think With Google, more than 90% of people globally discover brands or products through the platform, and many go on to make rapid, decisive purchases influenced by the videos they watch and discover. 

YouTube Shorts outperform TikTok and Instagram Reels in engagement and retention

Among short-form formats, Shorts has proven especially explosive, offering brands and marketers a way to connect with new and distinct audiences beyond the reach of TikTok, Instagram and similar channels. Marketers are increasingly betting on Shorts because the numbers suggest they can deliver both reach and retention at scale. 

Since its worldwide launch, YouTube Shorts accumulated more than 5 trillion views by May 2025, drawing 2 billion active monthly users. Boasting an engagement rate of 5.91%, it stands as the highest engaging media for short videos according to Resourcera, edging out TikTok (5.75%) and Instagram Reels (5.53%). Just as important, Shorts in the 50- to 60-second range achieve completion rates as high as 76% when the content resonates. 

YouTube has introduced a suite of AI-powered tools designed to make creating short-form videos faster and more efficient. Unveiled at its Made on YouTube 2025 event, the centerpiece is Veo 3 Fast: a streamlined version of Google’s generative video model that can transform simple text prompts into ready-to-publish Shorts in just seconds. With Veo, creators can style their videos in creative ways and insert objects, characters or props just by describing them in text.

YouTube is also introducing an “Edit with AI” draft editor, capable of assembling clips from raw footage, suggesting transitions and even adding narration. A new speech-to-song feature converts dialogue into musical soundtracks, while stylization filters and motion transfer tools let creators animate still images or change the look of entire clips. 

One of the biggest wins here is that marketers no longer need full editing teams or expensive software to turn raw assets into polished clips. With AI handling the first draft, even small teams can get Shorts out the door quickly, which means more testing, more content and more reach without ballooning budgets. 

To maintain transparency, Shorts generated with these tools will carry both a visible label and an invisible SynthID watermark from Google DeepMind. The rollout will begin in the U.S., U.K., Canada, Australia and New Zealand before expanding worldwide.

Discover trending content ideas fast with Google’s new Inspiration tab

It’s not just Shorts getting smarter. YouTube is making it easier for creators and marketers to plan, scale and monetize across the platform. Creator Collabs enables seamless cross-promotion by allowing partners to copublish videos and share analytics, helping brands and influencers coordinate campaigns, maximize visibility and increase revenue opportunities. 

YouTube’s Inspiration tab, introduced last year, is also getting an upgrade to help creators brainstorm smarter. Now, for every AI prompt, creators receive nine tailored suggestions and a curated list of topic ideas specific to their channel. The tool highlights why each topic could perform well, based on audience insights, and allows creators to combine suggestions or add their own.

Meanwhile, the platform’s long-awaited auto-dubbing tool is also rolling out globally, instantly translating and voicing videos in multiple languages with synchronized lip movements. 

Ask Studio: Use YouTube’s AI assistant to understand your audience better

YouTube’s Ask Studio is a new AI-powered assistant designed to give creators a clearer picture of their audience and content performance. By analyzing metrics, comments and retention data, it delivers actionable insights that help creators understand what works, what doesn’t and how to improve future videos. Whether you’re looking to optimize engagement, test new formats or fine-tune your content strategy, Ask Studio acts like a personal channel strategist, providing guidance so every upload reaches its full potential.

For instance, you might ask, “Which clips from my last video kept viewers watching the longest?” or “What are my subscribers saying about the topics I cover?” and Ask Studio’s analysis of the data can give you clear insights. Ask Studio can also suggest improvements for upcoming uploads. For example, you can query, “How can I make my next tutorial more engaging?” or “Which keywords are trending in my niche right now?” The tool can provide data-driven recommendations on content structure, titles, descriptions and posting times, helping you optimize every video for maximum reach.

For creators, this means less time sifting through analytics dashboards and more time focused on creating high-quality content. With Ask Studio, you have a personal analytics assistant who can deliver actionable guidance, helping you refine your strategy, experiment with new formats and ensure each upload resonates with your audience. 

For professionals looking to stand out online, YouTube’s new upgrades provide a blueprint for smarter marketing. Repurpose long-form content into Shorts, brainstorm winning ideas with AI and use Ask Studio to understand your audience like never before. Use these AI powers, and every clip becomes a doorway to a larger audience and bigger influence.

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Staying on top of industry insights is a critical part of being a leader. From competitor news to salacious exposés, a daily read or watch of the latest headlines is a staple for many CEOs and senior leaders. 

But it can be overwhelming to go through endless sites and check competitor press pages every day. ChatGPT can make this process a lot easier. The “Tasks” feature in the popular AI tool allows for recurring activities and reminders to be scheduled through the platform, including searching the web for the latest headlines.

This was the first recurring task I set up as soon as the feature was launched in February. Having ChatGPT comb through the websites I trust has made it easier to keep up with the news I needed to know. It’s simple to set up and highly rewarding. Here’s how to do it:

Step 1: Enable the o4-mini model of ChatGPT

The recurring tasks feature is only available on the o3 and o4-mini models, but I find o4 to be more accurate. It’s capable of fast advanced reasoning and consistently delivers correctly.

Step 2: Start a new chat for your recurring task

Start a new chat for each task and let ChatGPT know you want to set up a recurring task. Give the task the frequency—daily—and the time for ChatGPT to scour the news.

Step 3: Redirect the model towards a web search

By default, the tasks feature will ask what the user wants a reminder for, as if the user is the one who will carry out the task. Let ChatGPT know it will be doing a daily web search instead.

Step 4: Give it clear instructions

This is the most important step in the process, because ChatGPT needs clear criteria of what it should be searching for. Use the prompt below as a model:

I’m a [position title] in [industry]. Every day, I need you to search these websites to pull up relevant news headlines: [all the publications and niche blogs and competitor press rooms regularly consulted]. Please restrict yourself to headlines only from the last 24 hours as I will use these headlines to help guide my decision making, using explicit date filters (for example after:2025-05-15) or a freshness=daily parameter. Hyperlink the websites in the titles of each article.

Split the results into three sections:

1. Priorities
   My current priorities are [enter your key priorities]. Check for any articles tying into those priorities. For each, provide a four-line summary, two sentences on how it should influence my immediate priorities and a letter grade for its priority impact. If there’s nothing relevant, say so.
2. Competitors
   Keep a special watch for any news in the last 24 hours on [competitor names]. If there’s news, give a two-line summary for each item. If there’s no news, note that.
3. Industry & Function News

Find relevant headlines from the last 24 hours in [industry, function, key area of interest]. Provide a three-line summary for each and order them by priority. 

Use the prompt as a baseline and modify it according to specific objectives.

Step 5: Troubleshoot and provide feedback

It may take a few days to get the prompt exactly right. Give additional instructions on the quality of the articles, the timeframe, the ranking based on industry. This helps the task better understand specific needs and goals. 
As with all AI use, filter the results through a careful lens. It’s important to do a due diligence check twice a week, but this prompt can save significant time pouring through the front page of publications to find relevant headlines every day.

Photo courtesy of Ju Jae-young/Shutterstock

When you’re running a business, every photo you put out into the world is part of your brand story. Whether it’s a product image on your website, a team photo for LinkedIn, or a behind-the-scenes Instagram shot, visual quality matters—and it can mean the difference between “just scrolling” and “click to buy.”

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During his time at Uber, Magos spent much of his time on hiring and saw firsthand the way the process can become subjective and fragmented due to a lack of clear data, even at high-growth Fortune 500 companies.

“To us, hiring at that time meant interviewing. It meant spending time with other human beings to sort of understand who they are. And there was this particular hiring loop that I was a part of where, when we turned up at the debrief…you just saw this massive delta between the folks that really knew how to run these and what to look for in great candidates and the people that didn’t,” he told Fortune.

“Some people were just so data-driven in the facets they were sharing about the candidate, and other people were just completely going by gut,” he said.

“It made me realize that even these amazing companies are still fundamentally relying on shards of memories that people have of these human-to-human interactions and if you’re ever going to significantly up-level hiring—you’re going to have to harness this conversational data.”

This is what led to the inspiration for the company’s flagship product, an AI-notetaker that records and structures interview notes so hiring managers don’t have to. Now, the company is planning to build a full suite of AI tools aimed at the recruiting and hiring process.

$35 million for an AI recruiting revolution

The pair’s history with and knowledge of corporate recruiting workflows drew in Vidu Shanmugarajah, a partner at Google Ventures. He sees this as an area “where digitalization skipped a step.” Recruiting, which is heavy on admin, is ripe for disruption when it comes to developing AI tools.

“Pre AI, it was quite basic what you could do in and around hiring. It was sort of like software 1.0…you weren’t able to go anywhere near as deep as you can go as you can now with LLMs, but to be able to do that, you need to spend a lot of time in and around hiring workflows,” Shanmugarajah told Fortune.

“They’ve been building for hiring and in recruitment,” Shanmugarajah said of Magos and Shahriar Tajbakhsh. “You need to spend a lot of time in and around hiring workflows, which they’ve done in their prior roles at Uber and Palantir, and you also need to be able to build with a real understanding of who the users are and how their hiring workflows have been developed over time.”

Metaview’s latest round also includes continued backing from existing investors, including Plural, Vertex Ventures, Seedcamp, Coelius Capital, True Equity, as well as Victor Riparbelli and Barney Hussey-Yeo, and builds off its previous $7 million Series A in March last year.

The company plans to use the funds to build out its full suite of AI tools, hire more staff at its London headquarters, and expand its presence in San Francisco.

“The focus for us now is to really build out the rest of the platform,” Magos said. “So our big thesis for the company, since the start..is obviously AI is going to change how we work.”

Automate the hiring process

Metaview’s full suite of AI tools aims to streamline and enhance every stage of the hiring process.

The company’s flagship product is an AI note-taking app for recruiters and hiring managers that records, analyzes, and summarizes job interviews, but it’s also working on: AI Reports, a customizable reporting engine for optimizing the hiring funnel; AI Answers, an always-on assistant that delivers instant information about any candidate, job, or hiring detail; and AI Job Posts, which generates and maintains job descriptions so teams can launch new searches in seconds rather than days.

Metaview says its customers, which include Sony, Brex, ElevenLabs, and Deliveroo, save 30 minutes after every interview and up to two hours per job post.

While other companies offer similar note-taking services, Magos sees Metaview as protected from threats from general-purpose tools like Microsoft Copilot through its specialization in recruitment workflows.

Metaview integrates directly with recruiting tools such as applicant tracking systems and is designed to understand the specific context of recruiting conversations.

Magos says specialized data and domain-specific post-training, allowing Metaview’s AI tools to generate far more accurate and relevant summaries.

Limits of AI hiring

There are concerns about how much AI should be used in the recruiting process, especially if decisions are being influenced or made by AI agents.

Under the EU AI Act, HR-related applications of artificial intelligence—including recruitment—are classified as ‘high risk’, due to concerns around transparency, fairness, and ethical implications in their use.

Magos says the company is not trying to automate the hiring decisions, but rather the admin that comes with writing a job post, searching for candidates, and making interview notes.

He says Metaview’s software never offers advice about who to actually hire: “Where we draw the line at the moment is that we leave the human-to-human interaction to humans. But some of the work associated with spending a ton of time sort of scrolling through LinkedIn to find these candidates is something we’re working on.”

Magos also told Fortune the tech has the potential to take some of the subjectivity out of hiring and encourage more data-backed decisions.

However, AI tools often bring their own bias to the table, something that has worried HR professionals.

For example, three-quarters of employers in a recent ISE Student Recruitment Survey said they worried about the potential for bias and preferred a more human-centric approach to recruitment.

In response to some of these concerns, Magos argues that speech-to-text systems provided by LLMs are better than most human attempts at it.

When it comes to bias, Metaview’s biggest mitigation is ensuring that its AI assistants don’t become “a judgment tool” or “make recommendations about who to hire.”

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