Category

Artificial intelligence

Learn how persistent application models help SDETs move beyond brittle scripts, reduce test maintenance, and understand failures faster.

The Test That Actually Knows Your App

Interconnected agent pipelines are making consequential decisions in sequence — but most enterprise agentic architectures have no quality layer. Here's what one looks like and why it can't be an afterthought.

The Agentic Enterprise Needs a Quality Layer

Intent-based testing replaces brittle scripts with outcome statements. Here's what that actually changes about how you write, debug, and maintain tests every day.

What ‘Intent-Based Testing’ Actually Means for How You Write Tests Day to Day

Bolt-on vs AI-native testing platforms explained. Learn the key differences engineering leaders must understand before choosing a modern test automation platform.

Bolt-On vs. AI-Native: What Engineering Leaders Need to Know Before Buying a Testing Platform

Unlock objective-driven QA. Perplexity's 'AI OS' frames the future: stop giving tests instructions, start giving Functionize objectives. Adapt, not just automate.

From Instructions to Objectives: What Perplexity's Personal Computer Reveals About the Future of AI in Software Quality

Enterprise testing volumes require trillions of tokens monthly. Discover why GPU-dependent AI testing solutions face impossible economics at scale.

The Economics of Impossible: Why GPU-Dependent Testing Will Never Scale

Discover how agentic AI empowers QA teams by automating repetitive work, enabling professionals to focus on strategy and innovation for superior quality outcomes.

Replace Work, Not Workers: How Agentic AI Empowers QA

Why frontier AI labs can't replicate Functionize's testing data advantage—and what it means for the future of enterprise QA automation.

Why Data is the Bedrock of AI Testing

Learn how agentic AI testing eliminates traditional trade-offs between speed, quality, and innovation, enabling enterprises to achieve all three simultaneously.

Speed, Quality, Innovation: Meeting the Modern Business Trifecta with Agentic QA

Discover why purpose-built AI models outperform generalized frontier models in QA testing, delivering superior accuracy and reduced maintenance overhead.

Why Purpose-Built AI Models Outperform Frontier Models in Testing

Discover how Agentic Labor and AI-powered QA are reshaping productivity, policy, and enterprise innovation in the U.S.

Agentic Labor and the New Golden Age of American Innovation

Discover how AI-powered tools like Functionize optimize test creation, maintenance, and diagnostics for faster, reliable enterprise QA at scale.

The Role of AI in Scaling Test Automation

The future of QA isn’t offshore—it’s no-shore. Discover how Functionize’s AI-powered Digital QA Workers redefine software testing, delivering unmatched speed, accuracy, and cost efficiency.

The story of digital workers

Discover 5 essential truths about AI in 2025 that cut through the hype. Learn how AI at the core, digital workers, and automation drive real business impact, faster results, and lower costs.

5 AI Truths for 2025- A New Year list

A modern tale of two QE developers, Sam and Andy, highlights the stark contrast between sticking to outdated frameworks and embracing AI-driven automation. This is the second part of their journey and choices impact their careers.

The Tale of Two QE Developers: Sam vs Andy - Part II

The future of software testing lies in AI’s ability to create, adapt, and optimize and as solutions engineers, we have the unique opportunity to guide businesses into this new era of smarter, more intelligent software testing.

New Frontier of AI Driven Software: A Solutions Engineering Perspective

A modern tale of two QE developers, Sam and Andy, highlights the stark contrast between sticking to outdated frameworks and embracing AI-driven automation. Discover how their choices impact their careers and learn how tools like Functionize can transform QA into a strategic advantage.

The Tale of Two QE Developers: Sam vs Andy - Part I

Delegating AI evaluation to individual contributors risks inaccurate ROI assessments and delayed adoption, making it crucial for leadership to actively guide the process to ensure strategic alignment and competitive advantage.

Why Delegating AI Evaluation is Risky

Using AI and technical strategies can vastly improve QA test coverage. Learn how AI-enabled autonomous test case creation, along with code coverage analysis, mutation testing, model-based testing, behavior-driven development (BDD), and integrating tests into CI/CD pipelines, can further enhance testing coverage

How to Use AI and Technical Strategies to Improve QA Test Coverage

Learn about the roles of tokens and parameters in machine learning AI-based testing, detailing how they enhance test accuracy and efficiency by interpreting complex scenarios and learning from past data.

Understanding Tokens and Parameters in Model Training: A Deep Dive

AI implementation in large organizations isn’t simple, but well worth the effort. Learn more about what to expect in the transition to AI-driven automation.

AI Implementation: Not Just a Flip of a Switch

Explore how generative AI transforms test case debugging and diagnosis in software development, enhancing the identification and resolution of issues for more efficient, reliable automated testing.

Diagnosing and Debugging in a Gen AI World

AI-based testing is heavily reliant on the quality of data used for training. Learn about the significance of data quality, including common challenges and best practices to ensure high data quality in AI-based testing.

The Importance of Data Quality in AI-based Testing

Mamba machine learning explores a new deep-learning paradigm using selective state-space models for fast, efficient long-sequence modeling. Read now!

Mamba Machine Learning: Rethinking Sequence Modeling for the Future

Uncover the power of transformers in test automation and their wide-reaching influence in NLP, computer vision, and more.

From Language Processing to Test Automation: The Evolution of Transformers

Discover how the future of software testing is being shaped by the increasing integration of artificial intelligence, and why human oversight remains essential in this collaborative environment.

The Human Element in AI-Driven Testing Strategies

Here’s how QA professionals can prepare for an AI-dominant future in software testing. Upskill in AI fundamentals and automated testing, explore emerging roles, and embrace continuous learning in this transformative landscape for a successful career.

Welcoming the Inevitable: How QA Professionals Can Prepare for an AI-Dominant Future

Explore the transformative potential of AI-augmented testing in software QA, offering insights into its efficiency, precision, and the synergy between AI and human testers.

What Exactly is AI-Augmented Testing?

Big data is a game-changer for businesses of all sizes. Scalable cloud solutions, open-source tools, and strategic outsourcing have dismantled barriers, placing advanced analytics within reach.

Democratizing Data: A Look at Big Data's Potential for Small and Medium Businesses

Our Deep Learning series concludes with a feature on mission-critical domains. Learn more about how mission-critical operations are leveraging deep learning to benefit from adaptive decision-making, scalability and efficiency.

Learning about deep learning: Applications in Mission-critical Domains

Part 2 of our Deep Learning blog series explores the transformative potential of transfer learning and reinforcement learning techniques. Learn about real-world applications and how these techniques can optimize decision-making and drive innovation.

Learning about Deep Learning: Transfer Learning & Reinforcement Learning, part 2

Deep learning encompasses neural network architectures and generative models, which are key concepts in this field.

Learning about Deep Learning: Neural Network Architectures and Generative Models

5 absolutely essential books on Machine Learning for any level

The Best Books to Learn About Machine Learning in 2023

AI/ML models require cloud servers to optimize their performance. In this post, we will dive into the reasons why AI technology necessitates the use of cloud servers and the advantages that can be anticipated.

Why AI/ML Testing Needs Cloud Infrastructure

A detailed look at how different software testing tools use AI to enhance testing, including visual testing, unit testing, quality optimization, and performance testing.

Different Ways to Use AI to Augment Software Testing

Functionize is a world-leading AI-powered test automation platform. But this is only possible because we collect a vast volume of data. Read on to learn why.

What data does Functionize collect, and why?

AI is here to stay, but should you build your own solution or buy one off the shelf? Here, we look at the pros and cons of building your own AI testing tool

Building Your Own AI-Testing Tool: Pros and Cons

AI lets us deliver the most reliable test automation platform out there. But as we explain, this is only possible because our system learns by making mistakes.

Learning from its mistakes. How the Functionize AI really works

CTOs have a hard job delivering digital transformation. Often, test debt is the blocker. Learn how AI cuts test debt to deliver faster digital transformation.

AI-powered testing. Why every CTO should leap at the opportunity.

AI test automation can transform testing for your company. But you might feel worried about your career. Here, we show why you needn’t stress about it.

AI test automation sounds great, but what’s in it for me?

Transitioning to a new test framework is a big step for any team. Here, we give you the knowledge you need to successfully transition to AI-powered testing.

4 winning approaches to migrate to AI powered testing

Modern web applications need a different approach to testing. Here, we see how AI-powered solutions increase the number and type of tests you can automate.

The top 10 test cases that benefit from AI power

Digital Experience Monitoring focused on metrics like availability and backend performance. But do they guarantee your customers' constant positive experience?

Why AI is essential for continuous digital experience monitoring

The software market is highly competitive, so you need any edge you can get. QA productivity may be a blocker. We show you how AI improves it.

How AI helps you improve software testing productivity

3 Reasons not to worry about AI replacing your testing job

Read about Artificial Intelligence from Functionize. Click now to learn why to trust AI for testing.

Why should you trust AI for testing?

Discover the top AI trends in testing, with the changing QA landscape, growth of continuous testing, the rise of shift left and a lot more!

Top AI Trends in Testing for 2021

Functionize 4.0 introduces SmartFix, a powerful feature that helps testers with debugging and fixing broken tests in test maintenance.

SmartFix: 3 ways it solves your test maintenance headache

So many products promise to be ML/AI when they are just an impressive algorithm. But smart isn't the same as intelligent when it comes to the minds of machines.

Things that are called ML/AI that really aren’t

Discover how machine learning quality assurance ensures accuracy, fairness, and reliability in AI systems with best practices and tools. Read now!

Machine Learning Quality Assurance: Ensuring Reliable, Ethical & Performant Models

Functionize is the winner at the 2019 AIconics Awards

Machine learning is at the heart of AI. But most ML models need to be trained. Here, we see how humans are essential for creating good training data.

Machine learning and the humans behind the screen

Software testing is expensive – it can often cost up to 40% of the total budget. Here we look at 5 ways to avoid budget overflow through AI test automation.

AI test automation: 5 ways to avoid budget overflow

Boosting ML models allows you to eliminate bias, improve model accuracy, and boost performance.

Boosting ML models to create strong learners

Dynamic IDs cause problems for test scripts. Here we see how AI helps, & contrast a dumb application of AI with Funcitonize's intelligent approach

Handling dynamic element IDs with AI

Functionize’s NLP makes English the language of testing. We explain why this reconnects you with your users and contrast it to traditional test automation.

How NLP reconnects you with your end users

For the last few years, Artificial Intelligence has dominated the world of technology. But what is AI? How many so-called apps are an intelligent use of AI?

What Is Artificial Intelligence - When Is an AI Not An AI?

If applied in the right way, AI business transofrm betters processes, boosts efficiency, and give significant ROI. Learn more in the article!

AI Business Transformation - Getting It Right

AI test automation can bring you real benefits. We look at it is, your strategy for using it, and how it can impact your bottom line.

AI test automation – a 101 for executives

Infrastructure and operations (I&O) is ripe for AI transformation. We look at how and why you might use AI for Infrastructure management & operations.

AI Transformation for Infrastructure and Operations

Artificial intelligence is a true game chaning technology. But is AI good or bad for society? Discover more about this topic.

Is AI Good For Society? - The Good, The Bad & The Ugly

Have you ever wondered "Is AI really intelligent or not?" And what do we actually mean by artificial intelligence in the context of software testing?

AI - Artificial, Yes, But is AI Really Intelligent?

In this blog, we’ll explain why AI-based system testing is such a hard problem and look at how autonomous template recognition can help!

Autonomous Template Recognition

Are we prepared to QA artificial intelligence? In this blog we will look at the real impact AI will have on you as a QA engineer

Is QA/Testing Prepared For Artificial Intelligence?

A closer look at how AI can be used to improve software testing, regression tests methodologies, machine vision visual processing, etc.

Ai In Software Testing - 3 Ways AI is Improving Software Quality

To make shift left testing possbile, you need to integrate some form of AI based test automation software like Functionize.

How AI Enables Shift Left Testing For Software Teams

A closer look at Functionize's noscripts, cloud based software testing platform using artificial intelligence, NLP ML, and machine vision.

No Scripts AI Software Cloud Based Testing

Machine Learning in AI software testing is a tool for extracting important features from fuzzy and fast-changing information.

AI Software Testing: Machine Learning

The first part in a blog series to promote greater clarity about what’s possible right now with AI in software testing. Check out the article for more!

AI Software Testing: Making QA ‘Smarter’

Explore how autonomous AI is being used to create new models for business, that improve the performance of their companies and protect the bottom line.

AI-Autonomous Models That Are Transforming Business

Part two of our series on AI's impact on business, and how neural networks, computer vision, visual intelligence are just a few that can empower all businesses.

Part 2: AI's impact on Business | Visual Intelligence

An overview of AI including influences on business and future implications of this driving force behind many of the greatest innovations in computing.

Impact of AI on business

Have a closer look at machine learning and deep learning, explore some of the nuances and break some myths.

Discovering the Children of AI: Machine Learning & Deep Learning

Discover how Functionize is revolutionizing the automated regression testing world with artificial intelligence.

Automated GUI Regression Testing Using AI Planning

Ready for an IQ/Test?