AI's deployment landscape is littered with good intentions, crushed projects and unintended consequences due to misaligned business goals, mistrust in AI and weak management. Continue Reading
AI watermarking is being used to identify deepfakes, enhance transparency and build trust in AI-generated content, but reliability issues and false positives present challenges. Continue Reading
With the rise of generative AI, prompt engineering has emerged as a new profession. Desired skills include refining prompts, analyzing AI output and ensuring alignment with business goals. Continue Reading
Transparency, explainability and trust are critical for enterprise AI. Learn how organizations can embed these principles to build accountable, ethical and reliable systems. Continue Reading
When justifying their investments in AI deployments, business leaders know keeping up with the Joneses isn't enough without uncovering a positive ROI. Here's where to find it. Continue Reading
As we welcome 2026, AI continues to lead the charge in business innovation. Expect to see more about governance, physical AI and integration with emerging technologies. Continue Reading
Ethical AI governance is now a boardroom priority, enabling organizations to curb bias, ensure accountability and build trust as a strategic advantage. Continue Reading
Five years can seem like an eternity in a world where AI's technological advancements occur almost daily, but best to be prepared now and avoid "future shocks." Continue Reading
With AI now poised to be a capable teammate rather than a mere tool, businesses are struggling to identify where and to what extent human-AI collaboration makes sense. Continue Reading
In the care and feeding of AI models and chatbot interfaces, prompting alone can be a fool's errand in strategic business planning without the proper context to interpret prompts. Continue Reading
Calculating ROI of an AI project to prove business value requires a complicated mix of costs, including data prep, infrastructure, integration, staffing, training and power needs. Continue Reading
Regression in machine learning helps organizations forecast and make better decisions by revealing the relationships between variables. Learn how it's applied across industries. Continue Reading
Technology never stands still, and 2026 could see it go full sprint. See our picks for emerging and developing technologies and tell us what tech your organization is watching. Continue Reading
As generative AI accelerates concepting and production, creative teams are evolving, requiring new skills, governance models and stronger human insight to guide meaningful work. Continue Reading
GenAI's outlook focuses on ROI expectations, power demands, data quality, agentic orchestration, plug-and-play LLMs, ethical practices, stepped-up security and human oversight. Continue Reading
Numerous local, regional and national AI regulations can help businesses govern AI, foster innovation and mitigate potential risks -- as long as their differences are understood. Continue Reading
As the project management field increasingly embraces AI-powered software, the benefits can help organizations thrive -- but only if the risks are properly considered too. Continue Reading
AI companies are the major winners with Trump's new AI executive order. But what does it mean for end users and enterprises? Continue Reading
Leading AI experts sound off on some of the top areas where AI deployments can positively impact business operations and services. Continue Reading
Building a machine learning model is a multistep process involving data collection and preparation, training, evaluation and ongoing iteration. Follow these steps to get started. Continue Reading
AI is helping make 5G networks more resilient, integrated and easy to implement. That makes private 5G networks for enterprises a clearly superior alternative to Wi-Fi. Continue Reading
Machine learning bias can distort predictions and harm trust. This guide explains types of bias, real-world cases and seven effective strategies to ensure fairness in ML models. Continue Reading
AI is reshaping virtually every aspect of business operations. Stay ahead of the curve by exploring these 10 emerging AI trends for 2026. Continue Reading
Are our humble AI agents turning into valuable AI associates? Learn about the growth of AI agents from experts at this year's EmTech MIT conference. Continue Reading
Can AI technology foster trust and serve the common good, or will algorithms shape humanity's future for the worse? Experts at EmTech MIT wrestled with the nuances. Continue Reading
From crop monitoring to autonomous machinery, AI is changing the agriculture industry. Hear from farm owners and domain experts on what use cases are having an effect in 2025. Continue Reading
In a race to adopt innovative technology, organizations across the globe made mistakes in enterprise AI deployment. What lessons can you learn from this year's AI horror stories? Continue Reading
A recent Yale study finds AI is reshaping jobs, automating tasks and boosting demand for analytical and collaborative skills, with overall employment remaining stable. Continue Reading
Beyond the risks associated with traditional AI, agentic AI poses specific ethical concerns, including diminished human oversight, privacy erosion and misaligned outcomes. Continue Reading
AI that doesn't just follow instructions but figures out how to get things done -- that's the promise of agentic AI, an emerging approach that's already changing some sectors. Continue Reading
Navigate the agentic AI tool landscape and accelerate successful deployment with this comparison of AI agent frameworks, platforms and capabilities. Continue Reading
Agentic AI's autonomous nature and its ability to access multiple data layers bring heightened risk. Learn how to ensure its deployment meets compliance standards. Continue Reading
Choosing which AI hardware option makes more sense for an AI or machine learning project depends on multiple factors, including speed, memory and cost. Continue Reading
Agentic AI changes workflows, boosts productivity and introduces new security risks. Learn what agentic AI can do and how to make this intelligent automation system secure. Continue Reading
The need for ever more AI expertise and performance has spawned vertical AI agents -- a new breed of autonomous agents purpose-built for specific industries. Learn how they work. Continue Reading
With concerns like limited reasoning and hallucination risk, will AI developers turn away from the GPT model and toward alternative model types? Continue Reading
Model makers disrupted AI, pushing Google to innovate and boosting Microsoft. Yet four years later, enterprises remain loyal to cloud providers, leaving the survival of the startups uncertain. Continue Reading
Compare Anthropic's Claude vs. OpenAI's ChatGPT in terms of features, model options, costs, performance and privacy to decide which generative AI tool better suits your needs. Continue Reading
AI agent use is ramping up, with development environments leading the charge. Governance and agent building are also on the rise. Continue Reading
Learn how one professional author uses QuillBot AI for writing tasks -- and how it stacks up to other popular options like Grammarly. Continue Reading
AI is virtually expanding, reshaping and personalizing telehealth practices in triaging, image analysis, patient diagnoses, treatment planning, monitoring and mental health. Continue Reading
The big healthcare product company's dental software division turned to AI automation startup Pipefy to transform a paper-based system into a digital one. Continue Reading
At MIT's Sloan CIO Symposium, experts emphasized that AI upskilling starts with what humans do best, pairing hands-on learning with inclusive, contextualized strategies. Continue Reading
Generative AI is already changing classrooms and student behavior. At Harvard, that's prompting faculty to reexamine how they teach and how they assess real learning. Continue Reading
At EmTech AI, generative AI's value was top of mind. But real ROI depends on business fundamentals like change management and clear success metrics. Continue Reading
At MIT's EmTech AI conference, tech leaders emphasized the value of purpose-built systems designed to support real business workflows. Continue Reading
Although the terms ChatGPT and GPT are both used to talk about generative pre-trained transformers, there are significant technical differences to consider. Continue Reading
What should enterprises make of the recent warnings about AI's threat to humanity? AI experts and ethicists offer opinions and practical advice for managing AI risk. Continue Reading
Multimodal generative AI can integrate and interpret multiple data types within a single model, offering enterprises a new way to improve everyday business processes. Continue Reading
Building a useful, reliable AI system requires trustworthy, well-managed data. Here's how to find and fix data issues that can drag down AI projects. Continue Reading
The use of generative AI is taking off across industries. Two popular approaches are GANs, which are used to generate multimedia, and VAEs, used more for signal analysis. Continue Reading
AI engineers and data scientists both shape AI projects, but their roles aren't the same. Learn how their jobs differ and why it matters. Continue Reading
Convolutional neural networks and generative adversarial networks are both deep learning models but differ in how they work and are used. Learn the ins and outs of CNNs and GANs. Continue Reading
Examine the standards, tools and techniques available to help navigate the nuances and complexities in establishing a generative AI ethics framework that supports responsible AI. Continue Reading
OpenAI's GPT-4o promises improved multimodal capabilities and increased efficiency. Explore the differences between GPT-4o and its predecessor, GPT-4. Continue Reading
Reported federal AI use cases jumped from 710 in 2023 to 2,133 in 2024. The staggering growth rate could continue to rise under the Trump administration. Continue Reading
Generative AI is predicted to add up to $16 trillion to the global economy by 2030. Learn how 20 industries, from finance and legal to healthcare and manufacturing, are using it. Continue Reading
Generative AI helps security teams defend against threats, but it also lets bad actors infiltrate organizations. Learn about how each side is tapping into GenAI to gain an edge. Continue Reading
Organizations are using generative AI to reimagine processes. Discover 10 ways the technology is transforming employees' jobs and their interactions with customers. Continue Reading
From personalized marketing and prototyping to business workflows and planning, generative AI can augment creativity as a new collaboration tool for humans in enterprise settings. Continue Reading
The travel industry is using AI to increase efficiency and personalize experiences, but challenges include data privacy, legacy integration and the need for a human touch. Continue Reading
2025 could bring more agentic AI developments. Enterprises could embed agents in their workflows. It could also lead to an orchestration infrastructure and better reasoning models. Continue Reading
Last year, expectations for generative AI for the coming year centered on regulation, open source and multimodality. While some predictions were accurate, others were wrong. Continue Reading
As the new year approaches, the pace of AI development shows no signs of letting up. Get up to speed for 2025 by catching up on TechTarget Editorial's top AI news stories from 2024. Continue Reading
AI technologies enable doctors to improve diagnostic accuracy, personalize treatment plans and streamline clinical workflows. However, they also pose challenges worth considering. Continue Reading
When gauging the success of generative AI initiatives, metrics should be agreed upon upfront and focus on the performance of the model and the value it delivers. Continue Reading
AI- or human-generated? To test their reliability, six popular generative AI detectors were asked to judge three pieces of content. The one they got wrong may surprise you. Continue Reading
Hyperparameters play a key role in shaping how machine learning models learn from data. Learn how adjusting these settings can improve model accuracy and performance. Continue Reading
Microsoft's Recall feature promises AI-powered convenience, but it raises significant security and privacy concerns that the company must address before a public release. Continue Reading
In lieu of federal regulation, U.S. states are proposing and enacting AI laws of their own. This up-to-date breakdown by state can help the C-suite keep tabs on developments. Continue Reading
To get the most out of generative AI models, developers and other users rely on prompt engineering techniques to achieve their desired output. Explore nine tools that can help. Continue Reading
Nearly a third of organizations are now using generative AI in production. But data quality, the AI skills gap and an evolving regulatory landscape continue to present hurdles. Continue Reading
Enterprise AI tools are transforming how work is done, but companies must overcome various challenges to derive value from this powerful and rapidly evolving technology. Continue Reading
Understanding how AI models make decisions is challenging, but two concepts -- interpretability and explainability -- can shed light on model outputs. Continue Reading
In addition to generating personalized advertising content, marketing professionals are using large language models as new personas to shape brand perception and strategy. Continue Reading
Ethical AI establishes principles for AI development and use, while responsible AI ensures they're implemented in practice. Learn how the two differ and complement each other. Continue Reading
Financial technology can benefit greatly from AI tools and strategies. But financial services companies looking to adopt AI need to understand the risks too. Continue Reading
AI compliance expert Arnoud Engelfriet shares key takeaways from his book 'AI and Algorithms,' describing the EU AI Act's effects on innovation, risk management and ethical AI. Continue Reading
What happens when you expand the use of AI beyond a circle of experts? To prevent business challenges, leaders must make smart investments in AI tools and training for workers. Continue Reading
As businesses in the construction industry integrate AI and machine learning into their processes, the sector's approach to design, safety and project management is changing. Continue Reading
Unlock the power of AI in data analytics with expert guidance. Learn how to implement AI tools that drive strategic success and future-proof your business. Continue Reading
These risks associated with implementing AI systems must be acknowledged by organizations that want to use the technology ethically and with as little liability as possible. Continue Reading
The growth of generative AI has led to more audio cloning technology. This could affect the U.S. election. Recent incidents show that existing safeguards are not effective. Continue Reading
Training data quality and availability aren't always a given in machine learning projects. When data is limited, costly or nonexistent, few-shot learning can help. Continue Reading
Convolutional and recurrent neural networks have distinct but complementary capabilities and use cases. Compare each model architecture's strengths and weaknesses in this primer. Continue Reading
Regularization in machine learning refers to a set of techniques used by data scientists to prevent overfitting. Learn how it improves ML models and prevents costly errors. Continue Reading
Boosting is a technique used in machine learning that trains an ensemble of so-called weak learners to produce an accurate model, or strong learner. Learn how it works. Continue Reading
Machine learning is changing how we write code, diagnose illnesses and create content, but implementation requires careful consideration to maximize benefits and mitigate risks. Continue Reading
Data science and machine learning both play crucial roles in AI, but they have some key differences. Compare the two disciplines' goals, required skills and job responsibilities. Continue Reading
What's the difference between open vs. closed AI, and why are these approaches sparking heated debate? Here's a look at their respective benefits and limitations. Continue Reading
Although AI can enhance cybersecurity practices like threat detection and vulnerability management, the technology's limitations ensure a continued need for human security pros. Continue Reading
AI tools and systems are becoming an asset for many real estate endeavors. Explore seven top use cases for AI in the real estate industry and challenges to adoption. Continue Reading
Learn the characteristics of supervised learning, unsupervised learning and semisupervised learning and how they're applied in machine learning projects. Continue Reading
New features for job applicants, recruiters and businesses include personalized writing suggestions, more advanced search capabilities and AI conversations within LinkedIn Learning. Continue Reading
As AI technology advances, U.S. and international copyright laws are struggling to keep pace, raising legal and ethical questions about ownership and AI-generated content. Continue Reading
Machine learning applications are increasing the efficiency and improving the accuracy of business functions ranging from decision-making to maintenance to service delivery. Continue Reading
Hype around GenAI will inevitably be followed by generative AI disillusionment. Experts ruminate on how to shorten the trough and prepare for the future. Continue Reading
AI is transforming the insurance industry by automating processes and improving risk assessment, but it also poses challenges in data transparency and algorithmic decision-making. Continue Reading
Businesses using AI digital humans in sales and marketing can cut costs through efficiency. However, experts warn of the legal risks and public distrust of the technology. Continue Reading
At the MIT Sloan CIO Symposium, enterprise leaders grappled with AI's benefits and risks, emphasizing the need for cross-team collaboration, security controls and responsible AI. Continue Reading
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