“AI for Work”: A Profession-Based Model for Sustainable Personal AI

In just a few years, artificial intelligence has gone from research labs to our personal pockets. Millions now interact daily with mass-market AI applications like ChatGPT, Grok, Gemini, Copilot, Claude, Perplexity etc—for help with homework, emotional struggles, writing emails, exploring news, and even preparing job interviews.


Much of this access has been free. Powerful tools backed by expensive compute infrastructure and knowledge retrieval pipelines have been made available to all—democratizing capabilities previously available only to experts. But this model is on borrowed time.


The Problem with Free AI

While enterprises and governments pay for large-scale access to AI services, individual users—by far the largest in number—mostly ride free. And their usage is not trivial. A single detailed query may require access to multiple content sources, inference from large models, memory storage, and server-side rendering—none of which are costless.

As the global user base swells into the hundreds of millions, this cross-subsidy model—where a minority of paying users and corporate clients fund the entire ecosystem—is increasingly strained.


If we want AI to remain widely available, sustainable, and ethically sourced, we must design a monetization model that’s fair, transparent, and user-friendly. Not one that locks away capabilities behind a paywall, but one that aligns access with utility.


A New Approach to Personal AI: Profession-Based Personalisation (and Monetisation)

Just like Microsoft Office or Adobe offers different features for students, educators, designers, or business users—AI providers could offer modular, profession-specific plans tailored to the actual needs of users in various fields.

Let’s call this model: “AI for Work”.


What Would “AI for Work” Look Like?

Under this model, users select a professional identity—which determines the bundle of tools, databases, and real-time integrations they get access to. Here’s what it could look like, for example:-


Profession: Lawyer

Paid Offering: Court judgments, legal databases, statutory updates, case summaries

Price: ₹199


Profession: Journalist

Paid Offering: Real-time news aggregation, bias-checking tools, press brief access

Price: ₹159


Profession: Academician 

Paid Offering: Journal access (JSTOR, Elsevier), citation tools, dataset discovery

Price: ₹199


Profession: Business Executive 

Paid Offering: Financial data, policy briefs, analyst reports, corporate news

Price: ₹229


Profession: Teacher/Educator

Paid Offering: Curriculum-specific modules, quizzes, education policy digests

Price: ₹129


Profession: Civil Service Aspirant

Paid Offering: PIB updates, budget summaries, bills and acts, static GS content

Price: ₹129


Profession: Healthcare Professional

Paid Offering: Drug databases, research updates, medical guidelines (WHO, ICMR)

Price: ₹199


A base layer of general-purpose features remains free: personal advice, basic general knowledge, simple creative writing, and basic summaries. But job-relevant, high-value content is unlocked only through the profession plan.


This approach introduces fairness—you only pay for what helps your profession—and sustainability, as usage patterns become predictable and fundable.


Behind the Scenes: How It Would Work

To implement this, AI providers would need to:

1. Build profession-specific modules trained on verified data relevant to that profession.

2. Secure licensing deals with journals, media houses, research publishers, or government bodies.

3. Tag queries by professional context. When a subscribed user makes a query, the model checks if it relates to their selected profession plan, and routes the response through the correct modules.

4. Respect user privacy. No user should be forced to reveal their real-world profession. “Profession” here means intended usage context, not legally verifiable identity.


Why This Model Is Likely To Work

1. It’s Familiar

It mirrors real-world professional subscriptions—like CA tools, legal search engines, or stock trading platforms—but now democratized and AI-enabled.

2. It’s Predictable

Users know exactly what they’re paying for. There’s no confusion about whether a query is “news” or “legal.” The user’s declared profession resolves that.

3. It Respects the Free Layer

The system doesn’t kill off free users. Instead, it keeps common-sense, recycled web knowledge free, while making specialized, high-compute, or licensed content paid.

4. It Opens B2B Possibilities

Employers could bulk-subscribe employees to AI for Work plans—just as they already do for Zoom or Slack.


All said and done, there could be users who wear multiple hats. For them, multiple offerings can be provided in bundle and with discounts, for example, ₹100/month for one profession plan, ₹180 for two, ₹250 for three, and nd so on. This would encourage power users to scale up, without burdening light users.


Conclusion: Less Netflix, More Electricity Board

AI apps should not be sold like generic entertainment subscriptions. They are more like modern utilities—powerful, contextual, profession-enhancing tools. And their business model must reflect that.

The “AI for Work” model offers a sustainable path forward—where value, access, and responsibility are aligned.

It ensures AI doesn’t just serve the richest or the loudest but becomes an infrastructure for productivity—one that understands what you do, not just what you ask.

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