Top AI Tools for Creators for 2025

Are you a content creator or marketer looking to improve your content? Wondering how AI can help you produce high-quality content? 

In this article, you'll discover the best AI tools for research, image generation, video creation, and audio production to enhance your content creation process.

Who Should Use Tools for AI-Generated Content

Not everyone needs to integrate AI-powered tools into their content creation. However, AI tools expert Matt Wolfe, says leveraging AI tools is no longer optional for businesses focused on content creation.

“If you're a business owner and content is your business, and you're looking for the most efficient way to get high-quality content out into the world, using AI is a must,” Wolfe explains. “There's really no more efficient way to create content than to leverage some of these tools out there that are really kind of a shortcut to creating really, really high-quality content.”

Wolfe's expertise comes from firsthand experience. Thanks to strategic AI implementation, he runs a successful YouTube channel, curates AI tools on his Future Tools website, and maintains a consistent presence across multiple social media platforms. He accomplishes what would typically require a team of 20 people with just two team members.

If you want to maximize your efficiency and content output quality similarly, Matt recommends adding the following paid and free AI content creation tools to your creative workflows. 

#1: AI-Powered Research Tools

Perplexity

Perplexity is a hybrid of ChatGPT and Google search, offering deeper insights than traditional search engines.

What sets Perplexity apart from ChatGPT's built-in search functionality is its depth of analysis. While ChatGPT's search feature provides surface-level results with summaries, Perplexity delivers comprehensive research by analyzing multiple sources and synthesizing the information into detailed summaries.

Wolfe notes that Perplexity's capabilities significantly exceed Google's AI-generated summaries, which have faced criticism for accuracy issues due to its inability to distinguish between genuine information and internet memes. In contrast, Perplexity's sophisticated filtering ensures more reliable and contextually appropriate information.

Perplexity offers a robust free tier that provides access to their core search and synthesis capabilities, though it includes advertisements. The free version allows users to conduct research and receive comprehensive summaries synthesized from multiple sources, going beyond simple search results to provide in-depth analysis. 

For users seeking enhanced capabilities, Perplexity's paid tier removes advertisements and allows users to select their preferred large language model (LLM), including options like Claude or GPT-4 instead of the default Llama model. 

The free tier provides sufficient functionality for many users' research needs, with the paid version primarily offering the benefits of ad removal and model selection rather than fundamental feature differences.

Google Gemini DeepResearch

Wolfe recommends Google's Gemini DeepResearch, available through their paid program (approximately $20 per month), for even more sophisticated research capabilities.

This tool takes research to another level, analyzing hundreds of websites simultaneously. 

Wolfe recently used the tool to learn about quantum computing. DeepResearch analyzed 247 different websites about quantum computing, producing a comprehensive 12-page document complete with sections covering benefits, challenges, current status, and future developments. 

The integration with Google Drive allows users to easily save and cite their research, making it particularly valuable for content creators developing in-depth educational or analytical content.

#2: Image Generation Tools

Leonardo

Wolfe identifies Leonardo as his primary tool for image generation due to its versatility and unique features. Leonardo incorporates multiple models, including Flux for photorealistic images and their proprietary Phoenix model, which Wolfe considers superior to Midjourney for creative, colorful, high-contrast images.

The platform excels at producing images that include text and offers features like AI upscaling capabilities, which can add additional details and textures to images.

One of Leonardo's most innovative features is its Flow State Mode. This unique capability allows users to begin with basic prompts and receive an infinite scroll of varied images. 

“Let's say you don't really know in your head what you want the image to look like,” Wolfe explains. “You can give it a rough idea and let it sort of flesh out a whole bunch of ideas and then dive deeper and deeper and deeper when you find an idea that you like.”

Then, the “More Like This” button generates variations based on the images you select, allowing you to refine your results progressively. You can also navigate backward through your exploration history if you want to pursue a different creative direction. Wolfe says this feature has become his primary method for creating YouTube thumbnails.

Leonardo operates on a credit-based system, offering approximately 100 free credits per day to users. Credit consumption varies based on several factors, with each image typically using between 4 and 8 credits, depending on the settings chosen. Higher-resolution images and simultaneously generating multiple images will consume more credits. At this rate, users can create roughly 20 images per day using their free allocation. 

While Wolfe is not a fan of the credit model due to its complexity in determining exact usage, he says the free tier provides substantial value for many users' daily needs.

Editor's Note: Matt Wolfe is an advisor to Leonardo.

Ideogram

Ideogram is helpful for projects requiring text integration in images. It delivers usable images with text eight out of ten times, compared to ChatGPT and other tools that will miss eight out of ten times, sometimes ten out of ten.

Ideogram's free tier gives users 10 credits per day.

Controlling Image Consistency: Seeds vs. LoRAs

There are two primary approaches for creators seeking to maintain visual consistency across multiple AI-generated images, but one significantly outperforms the other.

The first approach involves seeds, which are just starting points for image generation. “When you generate an image, it's basically creating a sort of blank canvas with a whole bunch of noise on it,” Wolfe explains. “That noise is based on the random seed that you give it, and then the noise is sort of diffused down to become the image that you were looking for.” However, seeds have significant limitations. While a seed defines the initial noise pattern, changing any prompt element will result in a completely different image, making seeds unreliable for maintaining consistency across a series of images with different poses, backgrounds, or scenarios.

The more effective approach utilizes Low Rank Adapters (LoRAs), significantly advancing AI image generation consistency. Rather than just providing a starting point, LoRAs allow users to train the AI model on specific styles, characteristics, or subjects. “You can train a LoRA by giving it about 10 pictures,” Wolfe explains. This training process creates a specialized trigger word that, when included in prompts, ensures the AI maintains consistent characteristics across multiple generations.

Wolfe provides several practical applications of LoRAs. For example, creators can train a LoRA on a specific artistic style using 10 screenshots from South Park to create a trigger word that will generate any new content in that distinctive style. Or, creators can train a LoRA on 10 images of a specific person or character, allowing them to generate new images of that character in different scenarios while maintaining consistent features.

This technology has become particularly valuable for AI influencer creation and brand consistency. “Whenever you see any of these AI influencers or things like that where every single image looks like the same character, but they're in a different scenario, they're most likely using a LoRA that they created on this character,” Wolfe explains.

The technology is currently available on several major platforms. Leonardo and Flux have integrated LoRA capabilities into their systems, and Midjourney has recently added similar functionality.

If you're developing a consistent brand or character presence, understanding and utilizing LoRAs is a game-changer because they provide a flexible way to maintain visual coherence across diverse content while allowing for creative variation in poses, settings, and actions.

#3: AI Video Content Generation Tools

Google's Veo2

Google's Veo2, currently in its early beta testing phase, has emerged as what Wolfe considers the best video generation tool presently available. 

The tool follows a distinctive generation pattern, creating four different variations of a video from a single prompt. Typically, two of the four look really good, and two won't.

The generation process for Veo2 is consistently around four minutes per request. However, the platform offers significant flexibility by allowing users to open approximately five instances simultaneously. This means creators can initiate multiple video generations in parallel, maximizing productivity during content creation sessions.

As of the interview, access to Veo2 currently requires joining a waitlist.

Sora by OpenAI

When OpenAI first unveiled Sora nearly a year ago, they showcased remarkable demonstrations, including highly realistic scenes such as a spacecraft on an alien planet with astronauts walking around. These initial demos set extremely high expectations for what AI video generation could achieve.

However, the reality of computational requirements led to significant adjustments in the public release. Wolfe explains, “When we finally got Sora, they actually gave us a model that uses a lot less compute, it uses a lot less computer power to generate that video.” This version, Sora Turbo, represents a practical compromise between capability and accessibility.

Cost considerations drove the decision to release a more computationally efficient version. “If they gave us that model, it would just be way too expensive to use,” Wolfe notes. “The cost to process those videos is just too high still.” This reveals a crucial challenge in the AI video generation field: the gap between what's technically possible and what's economically viable for public use.

While Sora Turbo may not match the visual fidelity of the original demonstrations, it still represents a significant advancement in accessible AI video generation technology. OpenAI has since increased its bandwidth and improved processing times. However, the tool remains a clear example of how current AI technology must balance capability with practical computational resources and cost considerations.

Luma Ray2

While Luma had previously released a video model called Dream Machine about nine months ago that Wolfe describes as “okay” and “decent,” their recent release of Luma Ray2 represents a significant advancement. Wolfe ranks Ray2's capabilities as not quite as good as Veo2 but better than Sora.

A key advantage of Ray2 is its accessibility – unlike Veo2, it's currently open and available to anyone.

The platform's effectiveness stems from its unique training approach. Much of its video generation capabilities are informed by real-world video and the extensive collection of 3D scans Luma has accumulated over five to six years. When users utilize Luma's scanning technology, they grant permission for their scans to be used in training, contributing to a vast database that helps inform the video generation process.

The State of AI-Generated Video

Wolfe emphasizes that while these tools excel at creating B-roll footage and short clips of 5-10 seconds, we're still far from AI generating complete, high-quality, long-form videos. The primary limitation remains computational power and associated costs. However, current capabilities are already proving valuable for content creators for typical B-roll needs, which rarely exceed 3-5 seconds in professional content.

#4: AI Audio Tools

NotebookLM by Google

NotebookLM, Wolfe's preferred tool for audio content creation, is a free Google tool that allows users to input content in multiple formats: PDF documents, URLs to websites, or direct text input. Once content is uploaded, users can interact with it in several ways.

The platform's standout feature is its ability to generate podcast-style conversations. It creates natural-sounding discussions between two AI hosts who talk about the information provided. Wolfe notes that the conversations sound surprisingly natural, like “two real people having a conversation.”

A recent feature addition allows you to interact with these generated discussions by pressing a button to interrupt the conversation, similar to calling into a radio show. When interrupted, the AI hosts will acknowledge you by name (e.g., “Hey Matt, what's up?”), listen to the question, and then continue their discussion addressing the new topic.

The generated content is downloadable, allowing you to save the podcasts for various purposes. 

Some creators have leveraged this capability to build successful podcast channels. Their workflow involves:

• Gathering information about a particular topic
• Uploading it to NotebookLM
• Having the system generate a podcast
• Downloading the content
• Publishing it through their RSS feed to platforms like iTunes and Spotify

Eleven Labs

ElevenLabs stands out for Wolfe as “the most realistic text to speech out there.”

The core functionality allows users to train their own voice into the system. This feature proves particularly useful for content creators who need to correct their videos. Wolfe shares a personal example of using ElevenLabs to fix a sponsorship ad read in which he had misspoken. Rather than re-recording the entire segment, he was able to type up a new sponsorship read and generate it in his voice, then overlay it into his video.

The platform includes a voice marketplace where users can access voices trained by other people who earn revenue when others use their voices through the platform.

ElevenLabs also features a sound effects generator so users can prompt the system to create specific sounds, such as a cat meowing, a door slamming, or an explosion happening in the distance. This feature eliminates the need to use stock sound effects websites.

The platform's GenFM feature functions similarly to NotebookLM, allowing users to upload articles and create podcasts. While Wolfe notes that NotebookLM currently does this better, GenFM remains a notable platform feature.

Looking ahead, ElevenLabs is planning to add music-generation capabilities to its platform.

Suno 

According to Wolfe, Suno is the best music generation tool available. The platform offers two primary approaches to creating music.

Users can input their own lyrics and have Suno generate a complete song, adding background music, drums, guitars, and other instrumental elements to accompany the provided lyrics. 

Alternatively, users can simply provide a prompt and let Suno create an entirely original song. Wolfe gives an example: “You can say, make a song about my dog Bowie and how he goes crazy running around in circles in my backyard,” and Suno will create a complete, fun song about that topic.

Suno includes a “no lyrics” option for content creators needing background music for videos. When this switch is activated, the platform will generate instrumental tracks that can serve as video sound beds. Wolfe frequently uses this feature instead of searching through stock video sites, simply telling Suno the tone he wants for his video and generating instrumental background music.

Other Notes From This Episode

• Connect with Michael Stelzner @Stelzner on Facebook and @Mike_Stelzner on X.
• Watch this interview and other exclusive content from Social Media Examiner on YouTube.

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