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AI-washing: Are we fooling ourselves with artificial intelligence?

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This week, my laundry machine broke. Bummer. Like any normal person, I dove into research mode, scrolling through endless product pages, feature lists, and discounts. After a while, one machine caught my attention. It was a Samsung model labelled “AI-enhanced”. (Not going to lie, it came with a solid discount, making it one of the cheapest among the top-rated options, but I was really excited about the AI feature)

In full honesty (this is not a sponsored post), it works great. From what I could observe, when you throw the clothes inside the machine, it weighs the clothes, and based on that, it selects the most suitable wash setting: water level, soap, temperature, and timing. Yes, it’s clever, efficient, and genuinely helpful. But it got me thinking: is that really AI, or just a well-designed automation?

We love “washing” and much more than just clothes

In business, as in life, those who tell the most compelling story tend to succeed. We love to use fancy words, set expectations high, and hold attention long enough to turn curiosity into conversion. Labels matter. Language sells. That is where the “washing” comes in.

Suddenly, the customer changes. With so many options available, they are no longer just buying products; they are buying into a story, a value, a promise. We saw it clearly with greenwashing. Everything became “eco-friendly”, “sustainable”, and “recyclable.” Some of it was real progress, but much of it was just clever marketing with little substance behind it.

The same thing is now happening with AI. Buzzwords like “AI-powered” or “intelligent assistant” are being applied to products that, while often smart and useful, are not truly driven by artificial intelligence. Just as greenwashing exaggerates a product’s environmental credentials, AI-washing misleads consumers about what the technology is actually doing. The line between automation and artificial intelligence is not always 100% clear. On that note, let’s review 5 cases where the buzzword was blurred into the product to fit the market

AI or not AI? That is the question 

1. Samsung AI-enhanced washing machines

This product sparked the idea of the whole article, so it clearly had to go first. Samsung has marketed several washing machine models as “AI-enhanced”, highlighting features that supposedly adjust wash settings based on load type and user habits. On the surface, it sounds like the machine is learning from behaviour and optimising accordingly, in line with what consumers might expect from AI.

What actually happens is simpler. When the laundry is loaded, the machine weighs the clothes and then selects the appropriate settings for water level, detergent, temperature, and cycle length. It is a smart use of sensors and automation, no doubt, but is it actually learning anything new, or simply taking note of what program you use the most?  I would personally not call this AI rather a well-executed piece of engineering.

Builder-ai

2. Builder.ai

The most obvious and famous case this year. Builder.ai was widely promoted as an AI-powered software development platform that could build custom apps without the need for developers. The promise was clear: type in your app idea, and their so-called “AI” would generate a working product quickly and affordably. It sounded like a revolution in software development, and investors bought into the story. The company raised over €440 million from major backers, reaching the billion-dollar valuation, positioning itself as a leader in AI-driven app creation.

The reality was far less futuristic. Investigations revealed that the platform relied heavily on a workforce of over 700 human developers based in India who manually executed most of the work. The AI component was minimal, mostly limited to interface suggestions and templates. While the human support may still deliver good results, the branding misled customers and investors into thinking they were witnessing automation at its peak, when it was mostly outsourced labour hidden behind a tech buzzword.

Logitech-M750

3. Logitech’s AI Edition M750 mouse

A few months ago, Logitech introduced the Signature AI Edition M750 wireless mouse. Curious buyers expecting next-gen input technology might be surprised to find that the “AI” upgrade is, quite literally, just an extra button. This button is preprogrammed to launch the ChatGPT prompt builder from Logitech’s Options+ app. That’s the standout feature. The rest of the mouse remains largely unchanged from the M650 model, which launched back in 2022.

Technically, the AI functionality does not reside in the mouse itself, but in the software layer. The M750 simply makes a shortcut default. It is a sleek mouse, but calling this product AI-enhanced when it is a clear case of trend alignment rather than a transformative capability.

OralB

4. Oral-B iO Series “AI” toothbrush

Oral-B’s iO Series toothbrushes are marketed as “AI-powered,” promising real-time feedback to improve brushing technique. According to the brand, the AI tracks your brushing style and helps you cover all areas of your mouth evenly. It sounds impressive, a smart toothbrush that understands your habits and coaches you to better dental hygiene.

In practice, the toothbrush uses motion sensors and pressure detection, then compares that data to a predefined ideal brushing path. (Note on predefined ideal brushing path). It gives feedback via a companion app, but there is no machine learning, no adaptation to individual patterns, and certainly no evolution over time. And let’s be honest, you’ll probably pay attention to the app during the first week or maybe the first month, but would you really check it every single time you use your toothbrush? Helpful, maybe. AI-powered? That is debatable.

LG-DUALCOOL

5. LG DUALCOOL AI Air Conditioner

The last one today is the LG’s DUALCOOL AI Air that has been marketed as a next-generation appliance, using AI Core-Tech to deliver personalised cooling based on user preferences. The product description includes terms like “AI DUAL Inverter”, “Human Detecting Sensor”, and “spatial analysis” through the ThinQ app. It promises to optimise airflow by tracking your location, learning your usage patterns, and adjusting the temperature and fan speed automatically. Add in features like Sleep Timer+, Auto Clean+, and energy-saving modes, and it sounds like the air conditioner of the future.

But strip away the marketing language, and you are left with a series of high-end sensors, pre-set routines, and app integrations that respond to motion, room temperature (a thermometer), and inactivity. Does that count as AI? Or is it simply a movement sensor connected to a smart control system? There is no clear evidence of true learning, prediction, or dynamic model training. It is smart, sure. But whether it is truly intelligent remains open to question, especially when every modern appliance wants to ride the AI wave.

The AI label is here to stay, even when the intelligence is not

These five cases are just a sample. The list could easily go on with smart fridges that suggest recipes based on scanned ingredients, AI fitness apps that follow static routines, or robot vacuums that use simple sensors to map your living room and call it machine learning. As AI continues to dominate the tech narrative, we can expect more devices to advertise questionable features related to the technology.

This is not necessarily harmful. Some of these tools are genuinely useful. But we should stay alert to what is actually being offered. Not every product that carries an “AI” label is smarter, and not every smart feature needs to be framed as artificial intelligence. If that is the case, maybe Excel should start branding its formulas as AI, too. They have been around for decades, but they can follow logic, adapt to inputs, and even simulate decision-making.

The label may help increase sales, attract investors, or drive media attention, but as consumers and professionals, we should learn to look past the branding and ask a basic question: Is it really AI, or just well-packaged automation?





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The Greatest First Basemen of All Time According to Artificial Intelligence

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In the intricate dance of Major League Baseball, the first baseman stands as a unique blend of offensive powerhouse and defensive anchor. They are the receivers of throws, the stretchers for outs, and often, the most prolific sluggers in the lineup. But who among these giants of the diamond truly represents the pinnacle of the position? Leveraging vast datasets of offensive metrics, defensive prowess, awards, and historical impact, Artificial Intelligence has meticulously analyzed the MLB careers of baseball’s greatest first basemen. The result is a definitive ranking of the top, based on an impartial assessment of their unparalleled contributions to the game.



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I asked ChatGPT to help me pack for my vacation – try this awesome AI prompt that makes planning your travel checklist stress-free

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It’s that time of year again, when those of us in the northern hemisphere pack our sunscreen and get ready to venture to hotter climates in search of some much-needed Vitamin D.

Every year, I book a vacation, and every year I get stressed as the big day gets closer, usually forgetting to pack something essential, like a charger for my Nintendo Switch 2, or dare I say it, my passport.



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Denodo Announces Plans to Further Support AI Innovation by Releasing Denodo DeepQuery, a Deep Research Capability — TradingView News

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PALO ALTO, Calif., July 07, 2025 (GLOBE NEWSWIRE) — Denodo, a leader in data management, announced the availability of the Denodo DeepQuery capability, now as a private preview, and generally available soon, enabling generative AI (GenAI) to go beyond retrieving facts to investigating, synthesizing, and explaining its reasoning. Denodo also announced the availability of Model Context Protocol (MCP) support as part of the Denodo AI SDK.

Built to address complex, open-ended business questions, DeepQuery will leverage live access to a wide spectrum of governed enterprise data across systems, departments, and formats. Unlike traditional GenAI solutions, which rephrase existing content, DeepQuery, a deep research capability, will analyze complex, open questions and search across multiple systems and sources to deliver well-structured, explainable answers rooted in real-time information. To help users operate this new capability to better understand complex current events and situations, DeepQuery will also leverage external data sources to extend and enrich enterprise data with publicly available data, external applications, and data from trading partners.

DeepQuery, beyond what’s possible using traditional generative AI (GenAI) chat or retrieval augmented generation (RAG), will enable users to ask complex, cross-functional questions that would typically take analysts days to answer—questions like, “Why did fund outflows spike last quarter?” or “What’s driving changes in customer retention across regions?” Rather than piecing together reports and data exports, DeepQuery will connect to live, governed data across different systems, apply expert-level reasoning, and deliver answers in minutes.

Slated to be packaged with the Denodo AI SDK, which streamlines AI application development with pre-built APIs, DeepQuery is being developed as a fully extensible component of the Denodo Platform, enabling developers and AI teams to build, experiment with, and integrate deep research capabilities into their own agents, copilots, or domain-specific applications.

“With DeepQuery, Denodo is demonstrating forward-thinking in advancing the capabilities of AI,” said Stewart Bond, Research VP, Data Intelligence and Integration Software at IDC. “DeepQuery, driven by deep research advances, will deliver more accurate AI responses that will also be fully explainable.”

Large language models (LLMs), business intelligence tools, and other applications are beginning to offer deep research capabilities based on public Web data; pre-indexed, data-lakehouse-specific data; or document-based retrieval, but only Denodo is developing deep research capabilities, in the form of DeepQuery, that are grounded in enterprise data across all systems, data that is delivered in real-time, structured, and governed. These capabilities are enabled by the Denodo Platform’s logical approach to data management, supported by a strong data virtualization foundation.

Denodo DeepQuery is currently available in a private preview mode. Denodo is inviting select organizations to join its AI Accelerator Program, which offers early access to DeepQuery capabilities, as well as the opportunity to collaborate with our product team to shape the future of enterprise GenAI.

“As a Denodo partner, we’re always looking for ways to provide our clients with a competitive edge,” said Nagaraj Sastry, Senior Vice President, Data and Analytics at Encora. “Denodo DeepQuery gives us exactly that. Its ability to leverage real-time, governed enterprise data for deep, contextualized insights sets it apart. This means we can help our customers move beyond general AI queries to truly intelligent analysis, empowering them to make faster, more informed decisions and accelerating their AI journey.”

Denodo also announced support of Model Context Protocol (MCP), and an MCP Server implementation is now included in the latest version of the Denodo AI SDK. As a result, all AI agents and apps based on the Denodo AI SDK can be integrated with any MCP-compliant client, providing customers with a trusted data foundation for their agentic AI ecosystems based on open standards.

“AI’s true potential in the enterprise lies not just in generating responses, but in understanding the full context behind them,” said Angel Viña, CEO and Founder of Denodo. “With DeepQuery, we’re unlocking that potential by combining generative AI with real-time, governed access to the entire corporate data ecosystem, no matter where that data resides. Unlike siloed solutions tied to a single store, DeepQuery leverages enriched, unified semantics across distributed sources, allowing AI to reason, explain, and act on data with unprecedented depth and accuracy.”

Additional Information

  • Denodo Platform: What’s New
  • Blog Post: Smarter AI Starts Here: Why DeepQuery Is the Next Step in GenAI Maturity
  • Demo: Watch a short video of this capability in action.

About Denodo

Denodo is a leader in data management. The award-winning Denodo Platform is the leading logical data management platform for transforming data into trustworthy insights and outcomes for all data-related initiatives across the enterprise, including AI and self-service. Denodo’s customers in all industries all over the world have delivered trusted AI-ready and business-ready data in a third of the time and with 10x better performance than with lakehouses and other mainstream data platforms alone. For more information, visit denodo.com.

Media Contacts

pr@denodo.com



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