28 Best AI Tools for Marketing With Examples 2025
If your marketing team downloads and uses AI software, you'll need to be sure you comply with privacy laws, such as GDPR. If you're going to use AI to generate content without having a human edit it, you may see a drop in the quality. The success of AI is reliant on high-quality data that is accurate and timely. AI can also identify customers at risk of churn and put them in an automated marketing campaign to get them to re-engage with your company. This saves your marketing team time and money, allowing them to work more efficiently and increase profits. While AI has a lot of great benefits, it‘s still an emerging technology and has some drawbacks.
Artificial intelligence Machine Learning, Robotics, Algorithms
The roots of AI trace back to the ancient idea of creating machines that can replicate human abilities. However, the formalization of AI as a field of study began in the mid-20th century. Alan Turing, one of the pioneers of computer science, played a critical role in laying the foundation for modern AI with his development of the Turing Test in 1950.
Top 10 Most Used AI Tools in The World 2025: The Definitive Global Usage Report
It also handles domain-specific terms through custom models, which improve its utility in specialized fields. Google Translate is one of the most used translation tools on the internet. It’s important to note that Google Translate's strength lies in its extensive language support, as it provides translations for over 100 languages.
Machine Learning
For example, a financial-services company could customize a foundation model they have for languages just for sentiment analysis. The second experiment was considerably larger, and hints at a future where generative AI systems, built on analog chips, could be used in place of digital ones. It aimed to implement a large, complex model, using five of the team’s chips stitched together, and simulated off-chip digital computations to showcase the scalability of analog AI.
Snap ML pushes AutoAI to deliver 4x-faster automated machine learning on IBM Cloud
This eliminates the need to move the weights between memory and compute regions of a chip, or across chips. The analog chips can also carry out many MAC operations in parallel, which saves time and energy. The artificial neurons in a deep learning model are inspired by neurons in the brain, but they’re nowhere near as efficient.
Difference between online and on line English Language Learners Stack Exchange
There is one useful difference in meaning between them, though. If you want to emphasise that you did buy a new cell phone, or contradict someone who thinks you didn't, you would definitely choose "I have bought a new cell phone." Which one you are likely to say is probably more about regional differences than anything else, especially when you add "I've bought a new cell phone" to the list. For some speakers, there's almost no practical difference in how they pronounce "I've" and "I" if they aren't speaking carefully. Grammatically, as I'm sure you know, the difference is that the first example is simple past, and the second is present perfect.
Bought vs Have bought
It is an old-fashioned term and native speakers of English do not use it. It is used in neither British English nor American English. Discussion is one of those words which can be a mass noun or a count noun. As a mass noun it means the act of discussing in general, as a count noun it means a single event of discussing. So for useful discussions implies that there were several separate times at which you discussed.
Best AI Solutions for Business: Top 12 Tools
They are super efficient at detecting anomalies that could pose potential threats. These systems can analyze vast amounts of data from multiple sources simultaneously, allowing for the quick identification of issues that humans may otherwise miss. Ensure every AI business application supports key business priorities—whether it’s customer experience, operational efficiency, or revenue growth.
Get Started With ChatGPT: A Beginner's Guide to Using the Super Popular AI Chatbot
The newest version of OpenAI’s image generator, DALL-E, was made available to ChatGPT Plus and Enterprise users. Hallucinations can become a huge issue if ChatGPT is being used to, say, write a news article, or ask questions about historical events, or get healthcare advice. Or, in the case of one New York lawyer, use ChatGPT for a brief in a client’s personal injury case (where it inadvertently cited six non-existent court decisions). ChatGPT is one of many AI content generators tackling the art of the written word — whether that be a news article, press release, college essay or sales email. ChatGPT is quite practical, particularly in business applications. And it has affected how everyday people experience the internet in “profound ways,” according to Raghu Ravinutala, the co-founder and CEO of customer experience startup Yellow.ai.
ChatGPT Gov
It can also critique the user’s writing, summarize long documents and translate text from one language to another. The paid version of ChatGPT also offers features like image and voice inputs and integrations with other more info OpenAI services like the image generator DALL-E. In May 2024, OpenAI released the latest version of its large language model -- GPT-4o -- which it has integrated into ChatGPT. In addition to bringing search results up to date, this LLM is designed to foster more natural interactions.
What Is Machine Learning? Definition, Types, and Examples
It’s how AlphaGo learned to defeat human champions at Go, and how robots learn to walk and run. Put AI to work in your business with IBM’s industry-leading AI expertise and portfolio of solutions at your side. Access our full catalog of over 100 online courses by purchasing an individual or multi-user subscription today, enabling you to expand your skills across a range of our products at a low price. Learn how organizations are shifting from launching AI in disparate pilots to using it to drive transformation at the core. Join IBM for a webinar where we demonstrate how to find real ROI through agentic AI initiatives, with examples across industries, use cases, and even IBM’s own stories of success.
What is artificial intelligence (AI)?
If AI is the broader concept of machines mimicking human intelligence, then ML is the application that allows systems to automatically learn and improve from experience. AI and ML are beneficial to a vast array of companies in many industries. Additionally, ML can predict many natural disasters, like hurricanes, earthquakes, and flash floods, as well as any human-made disasters, including oil spills.
Top 15 AI Business Use Cases in 2025 + Examples
Integrates deepfake technology into film production, enabling realistic digital character creation and storytelling enhancements. AI-driven systems can recognize new malware strains, defend against distributed denial-of-service (DDoS) attacks, and alert companies to vulnerabilities. They act faster than human analysts ever could, learning from each attack to strengthen defenses.
Property maintenance scheduling
ML models analyse various risk factors, such as geopolitical events or natural disasters, to identify potential disruptions and implement proactive mitigation strategies. ML models predict estimated time of arrivals (ETAs) for shipments based on historical data and real-time factors like weather and traffic conditions. Implements AI-based systems to detect and prevent financial crimes such as fraud and money laundering by analysing transactional data and identifying suspicious patterns. AI assists in workforce planning by predicting future staffing needs and optimizing resource allocation.
Graph-based AI model maps the future of innovation Massachusetts Institute of Technology
The table gives researchers a toolkit to design new algorithms without the need to rediscover ideas from prior approaches, says Shaden Alshammari, an MIT graduate student and lead author of a paper on this new framework. The electricity demands of data centers are one major factor contributing to the environmental impacts of generative AI, since data centers are used to train and run the deep learning models behind popular tools like ChatGPT and DALL-E. Diffusion models were introduced a year later by researchers at Stanford University and the University of California at Berkeley. By iteratively refining their output, these models learn to generate new data samples that resemble samples in a training dataset, and have been used to create realistic-looking images. A diffusion model is at the heart of the text-to-image generation system Stable Diffusion. Then, they screened the library using machine-learning models that Collins’ lab has previously trained to predict antibacterial activity against N.
Can large language models figure out the real world?
Next, the researchers set out to train the model to make predictions about LNPs that would work best in different types of cells, including a type of cell called Caco-2, which is derived from colorectal cancer cells. Again, the model was able to predict LNPs that would efficiently deliver mRNA to these cells. “From the perspective of the two main approaches, that means data from the other 98 tasks was not necessary or that training on all 100 tasks is confusing to the algorithm, so the performance ends up worse than ours,” Wu says.
5 Benefits of AI to Know in 2025 + 3 Risks to Watch Out For
General Electric's Predix platform, for example, monitors turbines in power plants. Analyzing data from sensors predicts potential failures up to two months in advance. This system has helped GE's clients achieve a 5% increase in production and a 25% reduction in maintenance costs. AI-driven predictive maintenance systems analyze sensor data, historical performance, and environmental factors to forecast equipment failures before they occur. This predictive approach saves maintenance costs and prevents unexpected breakdowns. Unilever, for instance, uses HireVue's AI-powered video interviewing platform to assess candidates.
Can AI really code? Study maps the roadblocks to autonomous software engineering Massachusetts Institute of Technology
Its user-friendly interface and AI-powered design suggestions make creating visually appealing social media content easy without needing advanced graphic design skills. Users highly acclaim Buffer’s user-friendly approach to generating content in seconds. Using AI tools for social media, you can supercharge your efforts across various aspects of content creation. Regularly monitor the generative AI content created to ensure that it meets your standards and objectives. Maybe one piece fits your goals after editing, but it’s not creating a holistic narrative with the rest of your content.
What is the Best Social Media AI Tool for Content Creators?
In this context, papers that unify and connect existing algorithms are of great importance, yet they are extremely rare. In 2017, researchers at Google introduced the transformer architecture, which has been used to develop large language models, like those that power ChatGPT. In natural language processing, a transformer encodes each word in a corpus of text as a token and then generates an attention map, which captures each token’s relationships with all other tokens. This attention map helps the transformer understand context when it generates new text. The work uses graphs developed using methods inspired by category theory as a central mechanism to teach the model to understand symbolic relationships in science.
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The AI continues your writing with one click while keeping your voice and style intact. Simple commands let you rewrite, shorten, or expand text right away. Whether you’re looking for a new AI assistant or want to get your own tool discovered, Agenthunter is one of the best places to start.