The AI working behind the Scene
How Artificial Intelligence already runs our Daily Life
Mostly unnoticed
[ Disclaimer: This review has been researched by Claude, the AI from Anthropic, with mayor editing by me to reduce length and improve readability. ]
Most people think of AI as something we interact with — a chatbot we type questions into, a voice assistant you argue with, an image generator that turns your daydreams into pictures.
Something we choose to use, or not.
But that understanding is already out of date.
AI now runs silently inside the infrastructure of everyday life — in your bank, your phone, your doctor’s office, our email inbox, the route our Amazon delivery driver takes, the price you’re shown for a flight, which videos you see on YouTube, which pictures on Instagram …
It makes decisions about us, and for us, constantly and without announcement.
This is not a future scenario. It is now!
The customer service you contacted, that wasn’t human
When you called your mobile provider to dispute a charge, or phoned your health insurer to check a claim status, there is a very good chance you never spoke to a human. You spoke to a system sophisticated enough that many people can no longer reliably tell the difference.
Nine in ten customer contact centers now use AI in some capacity. Telecom companies lead the way, with 95% of providers running AI in their customer support operations. Banks follow at 92%. Healthcare at 79%.
The numbers behind the shift are pretty stark. Bank of America’s AI assistant, Erica, resolves 98% of queries within 44 seconds. Across industries, AI has cut average response times from over 6 hours to under 4 minutes. Resolution times that used to take 32 hours now take 32 minutes.
Which sounds really great and often it helps!
But what does this mean for you and me, when we really need an expert on the line to help with out probem? When something goes wrong and you need a real person who can actually hear you – you are increasingly talking to a system optimized for resolution speed, not human connection.
Our Bank is watching our behavior in realtime
Every time you make a purchase — at a coffee shop, online, at a petrol station abroad — an AI system evaluates that transaction before it clears. Not afterward. Before.
This is fraud detection, and it has become one of the most sophisticated applications of AI in existence. Modern systems no longer check your transaction against a simple list of rules. They model your behavioral patterns in real time — your usual locations, your typical spending rhythm, your device, your connection type — and flag anything that deviates. The question these systems ask is no longer just “Is this you?” but “Does this feel like you?”
The same logic now applies to insurance claims, mortgage applications, credit decisions, and loan approvals.
AI systems make or heavily influence recommendations that a human officer may simply sign off on.
The Route You Took That Wasn’t Random
When your navigation app suggests a route and then quietly re-routes it, this is not a random glitch. AI systems are continuously modeling traffic patterns, accident probabilities, roadwork schedules, weather conditions, and the collective movement of millions of other devices to calculate the fastest path in real time.
Ride-sharing platforms use the same logic to determine surge pricing, driver positioning, and expected wait times before you’ve even opened the app. Food delivery apps use AI to predict when your meal will be ready, which driver is optimally positioned to pick it up, and how to route them in real time to hit an accurate delivery window.
The price you see, the time you’re shown, the driver dispatched to you — none of it is random. All of it is calculated.
Spotify’s recommendation engine — deciding what song plays next, which new artist to surface, which playlist to generate for your mood — is a deep learning system that has been modeling your listening behavior, your skips, your replays, and your time-of-day patterns for years.
Netflix and other streaming services operate the same way. What you see when you open these platforms — the artwork, the ordering, the first suggestion — is personalized to you specifically, generated fresh, designed to keep you engaged.
You are not browsing a catalog. You are being offered a curated experience designed by a system that knows your habits better than most of your friends do.
The digital tools we use every day, are being quietly transformed
Every major software platform has spent the past two years embedding AI into products that millions of people use without thinking about it as AI at all.
Microsoft has wired AI into Word, Excel, Outlook, Teams, and PowerPoint. Copilot — their AI assistant — now drafts emails, summarizes meeting recordings, generates presentation slides, analyzes spreadsheet data, and reviews contracts for legal risk, all from inside the applications you were already using.
Adobe — maker of Photoshop, Premiere, Acrobat, and the creative tools used by designers, photographers, and filmmakers worldwide — has integrated generative AI into its core applications.
You can remove objects from photos, change backgrounds, extend images beyond their original edges, and generate entirely new visual content from text descriptions, all from inside applications that existed long before AI was part of the conversation.
Adobe’s own research shows that 76% of organizations report significant improvements in content production from these tools.
Google is embedding its Gemini AI across Android, Chrome, Search, Gmail, and Maps.
Your Android phone can now complete multi-step tasks across applications — copying a grocery list into a shopping cart, filling out forms, browsing the web — in response to a natural language instruction.
Google Search increasingly presents you with an AI-generated answer above the traditional search results, which many users click on without noticing the distinction.
Apple is rearchitecting Siri with large language model capabilities. Your phone’s keyboard now predicts not just the next word but entire sentences, drafts replies to messages, and summarizes notifications you haven’t read.
These are not add-on features marketed separately.
They are the new baseline of ordinary software.
Within two years, the expectation will be that any serious application does this.
The email that you found in your inbox this morning
There is a reasonable chance that the promotional email in your inbox this morning — from a brand you’ve shopped with before — was generated by an AI, personalized for you specifically, sent at the precise time a model determined you were most likely to open it, with a subject line tested against thousands of variations to maximize your likelihood of clicking.
This is now standard practice in digital marketing.
AI generates and tests content, personalizes it at the individual level, determines optimal send times, adjusts pricing dynamically based on your browsing behavior, and tracks your journey across websites and apps to determine when and how to re-engage you.
When you visit a website and are shown a price for a hotel room or a flight, that price may have been calculated specifically for you — based on your device, your location, your browsing history, and your apparent urgency. Prices for the same product can and do vary between users viewing the same page at the same time.
This is not illegal in most jurisdictions. It is simply the current reality of commerce online.
In the Doctor’s Office
Healthcare has been slower to adopt AI than finance or retail — the stakes are higher and the regulatory environment more demanding. But the pace has accelerated sharply.
Between October 2025 and March 2026, Anthropic, OpenAI, and Amazon Web Services each launched dedicated, purpose-built healthcare AI platforms — not general AI with a medical disclaimer, but systems specifically designed and compliance-certified for clinical environments.
AI now assists with medical imaging analysis — screening X-rays, MRIs, and CT scans for anomalies — often with accuracy that matches or exceeds trained radiologists on specific tasks.
It manages appointment scheduling, insurance verification, billing, and prescription refill requests. It drafts clinical notes from doctor-patient conversations, freeing physicians from documentation time.
It monitors patient data for early warning signs. In drug discovery, it has already identified novel candidates now entering human trials.
The phone call you make to your GP’s office to check a test result or request an appointment is, in many healthcare systems, now handled by an AI that can access your records, answer your question, and schedule your follow-up — without a human being involved.
The Shadow Side
All that I have mentioned can definitely be helpful and improve efficiency and quality of service.
But none of it is neutral.
Every system described above collects data about us. Our spending patterns, our health queries, your navigation history, your viewing behavior, your click timing, your emotional state as inferred from your communication patterns.
This data trains the models that serve you — and it is also, in most cases, an asset on someone else’s balance sheet. Mostly the advertisement agencies.
Personalization is also manipulation. The recommendation engine that helps you discover music you love is the same mechanism that keeps you watching content past the point where you would have chosen to stop.
The pricing system that finds the offer most likely to appeal to you is also the one most likely to extract the maximum price you’re willing to pay.
And perhaps most obliquely:
AI systems make consequential decisions about people — credit, insurance, medical triage, job applications — in ways that are often opaque, not easily challenged, and not always explained even to the humans nominally responsible for them.
The Point of this Report
The point is not fear. It is clarity.
AI is not arriving. It is not something that will change our life when it matures. It has already changed the infrastructure of our daily experience, largely without announcement, mostly without our explicit consent, and at a speed that has left public awareness, regulation, and honest conversation well behind.
Understanding that this is already happening — not theoretically but right now in your phone, your bank account, your inbox, your doctor’s office — is the first step toward engaging with it consciously rather than sleepwalking through it.
The technology itself is neither good nor bad.
Like with electricity, with the printing press or the internet, like with every transformative technology before it, what matters is who controls it, how it is governed.
And whether the people most affected by it have any meaningful voice and choice in how it is used.
Right now, for most people, the answer to that question is: not much.
I think, this needs to change.
(One of the reasons why I write such articles 🐸
Research compiled May 2026 from Adobe Digital Trends Report 2026, Gartner Customer Service surveys, Zendesk CX Trends 2025, Microsoft product announcements, Stanford HAI AI Index 2026, AARP/Microsoft Fraud Research, Ringly.io, and multiple industry sources.