Why the web as we know it may fade and what AI, personal agents, and data interfaces mean for publishers, SEO, and commerce.
Every day, I’m witnessing people turn to AI for answers, product comparisons, and making quick decisions.
This shift reveals a core issue: the structure of the web wasn’t originally meant for machines.
As AI agents evolve, the way information is delivered – and the need for traditional webpages – could see dramatic changes.
The idea that the web as we know it could end, which I mentioned during a live OXD podcast in Salzburg, drew reactions ranging from thoughtful to angry.
Someone even insisted, “The web will always be there.”
Yet, those of us paying attention understand that “always” and “never” are shaky concepts in technology.
Technological history illustrates that nothing is forever.
Disruptions are noticeable only in hindsight.
Recall August 6, 1991 – could anyone foresee how Tim Berners-Lee’s World Wide Web would transform the world?
This cycle of dismissing new technology as too expensive or complex is as old as technology itself.
People pointed to existing solutions and assumed they’d last.
We also tend to judge new technologies prematurely, comparing immature models to systems we’ve heavily relied upon.
What we often fail to do is envisage the evolved state of a new technology.
This tendency clouds our future outlook.
When I’m in the market for a smartwatch, where do I usually turn for information?
Most often, I start with Google, landing on manufacturer or retailer pages.
Trying to compare the Samsung Galaxy Watch8, Classic, and Ultra to determine if the price difference makes sense is challenging.
Can I get this clarity from Samsung’s site? Probably not.
Each product page praises its uniqueness.
This forces me to jot down notes just to make basic comparisons.
I ponder over the difference between various bands and processors.
To grasp certain features, translations are sometimes necessary.
Even the “compare” function often leaves more questions than answers.
And while expectations would assume the premium model to have a specific feature, marketing priorities often arc differently.
The websites prompt more head-scratchers: Do these technical terms even matter to me?
My search broadens, throwing me onto SEO-crafted pages.
These sites often try leading me towards affiliate links.
Time is the thief here; Google requires nuanced search phrases and countless clicks.
But when I ask ChatGPT, the answer is swift and spot-on.
In less than four seconds, I get a clear comparison, making sense of all distinctions.
Follow-up questions are met with clarity.
If there are specifics to check, I am advised accordingly.
Such instances highlight the inefficiencies of web research.
Manufacturers tend to showcase products as they envision them.
But we often want straightforward comparisons.
We thrive on differences; we’re delta thinkers.
Sellers often prefer presenting products singularly.
If something isn’t present, obfuscation is the strategy.
It’s understandable, but not helpful.
Stop for a moment and try your AI for search queries.
If it’s been a while, you’re likely to be amazed.
In mere seconds, you get detailed answers.
Unsure about source reliability? Tailor your queries:
– “Only search designated expert sites.”
– “Only use well-known institutions.”
– “Give me all sources.”
The updated Google’s Gemini can produce extensive reports after an in-depth research request.
Imagine rich responses, often more comprehensive than solo human efforts.
That’s the growing strength of AI.
Using HTML makes content flexible for human consumption.
This system assists us in seeing and reading what’s online.
However, as AI usage expands, the limitations become apparent.
For example, the figures on a webpage may be clear to us, but the HTML lacks inherent semantic meaning for machines.
Structured data came as a solution but remains underused.
This impedes machine comprehension.
Apart from internal systems or large enterprises, structured data implementation is sparse.
Therefore, the primary content is still somewhat elusive to machines.
Google has worked hard to bridge this understanding gap.
Yet, AI continues to evolve, seeking innovative ways to parse and utilize data.
While AI presently gleans information through pattern matching, its potential remains vast.
Chatbots like ChatGPT offer solutions today.
The real challenge is context comprehension, which remains elusive for AI.
While both amazing and rapid, AI’s journey is just beginning.
The advances have sparked immense growth and excitement.
This era has only begun, opening doors to boundless possibilities.
Imagine a world transformed by personalized AI assistants.
The possibilities intrigue me.
These personal agents will tackle our daily routines, searching for optimal solutions.
AI might soon handle appointments, emails, and much more, offering efficiency and convenience.
Such shifts might alter how we interact digitally.
Content delivery and decision-making will evolve over time.
Our current HTML limitations challenge technological adaptability.
A new paradigm could include AIDIs assisting us with data retrieval.
Incorporating AIDIs means transitioning from HTML to structured forms.
Imagine AIDI extensions making data interpretation effortless.
Personal agents would operate even more efficiently.
The transition hinges on AI development and adoption.
Comparatively, the idea seems vast – but technological evolution often brings surprises.
Before long, our interactions may become distinctly AI-driven.
Offering a personalized touch, these agents may surpass our expectations.
Inspired by this post on Search Engine Land.
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