After Section 536

The 1961 Act ended quietly. No ceremony, no farewell. A single line in Section 536 of the new statute did the work, and on 1 April a law that had carried India’s direct taxes for sixty-five years was repealed. The Income Tax Act, 2025 is now live: 536 sections, 23 chapters, 16 schedules, down from more than 800 sections and 47 chapters. The headline word is “simplification”. The reality is more interesting, and more difficult, than the headline suggests.

Anyone who has lived inside the 1961 Act for a working lifetime knows that “simplification” is a mild description of what has just happened.

What “simplification” actually changes

The leaner numbers are the easy story. They get repeated in every press release. What they do not capture is the deeper editorial move: provisos folded into the main text, Explanations integrated into the body, and tabular rates and conditions replacing the cottage industry of parsing “Explanation 2 to sub-section (4) of section X” that consumed entire afternoons of an officer’s week.

The unification of “previous year” and “assessment year” into a single “tax year” is the cleanest example. Two financial years to describe one slice of income, with the gap producing systematic confusion in returns, notices and correspondence. Anyone who has tried to explain this dual structure to a first-time taxpayer, or worse to a foreign investor, knows it was always indefensible. Gone. One concept, one period, one number. This sounds trivial. It is not.

Five things actually shift

1. Discoverability

A 536-section Act with consolidated schedules is, for the first time, something a careful non-specialist can navigate. That matters more than the profession has admitted, and it matters enormously for AI. Every retrieval system, every assistant, every chatbot the public sector builds for taxpayers now sits on a cleaner corpus. Anyone who has trained a tax-domain assistant on the 1961 Act knows the specific pain of teaching a model to chase a fifth-level cross-reference into a circular issued in 1987. A flatter statute is easier for humans and easier for machines, in that order.

2. Drafting culture

The bigger contribution may not be the Act itself but the precedent it sets. Government drafting in India has long defaulted to safety through proliferation: another proviso, another Explanation, another sub-clause. The 2025 Act demonstrates, in a statute of national importance, that ruthless consolidation is possible without surrendering legal precision. That lesson needs to travel. GST, Customs, the Companies Act, the FEMA framework: all of them are due the same treatment, and now there is no honest excuse left.

3. The treatment of digital assets

The Act widens the definition of undisclosed income to include virtual digital assets. This is a small line with large implications. A clear statutory hook that earlier had to be assembled, awkwardly, from anti-avoidance rules and circulars now sits inside the main definitional architecture. Crypto investigation is no longer at the margins of the statute. It is inside it.

4. Litigation, slowly

I do not believe clearer text will reduce disputes immediately. For five to seven years, two Acts will run in parallel: pending matters under the old framework, new periods under the new one. The honest expectation is more litigation in the short term, not less, because every transitional provision will be tested in court at least once. The long-term gain is real. It will take the better part of a decade to show up in dispute statistics.

5. The administrator’s reset

Every officer is, in some sense, a new joiner. The institutional memory of the 1961 Act — which sub-section connects to which proviso under which 1985 amendment — is being retired with the statute. That is a generational opportunity for training. It is also a generational risk if training is treated as a formality and officers are left to absorb the new code by osmosis.

The dual-track problem nobody wants to discuss

Section 536 is the cleanest part of this transition. The messy part is everything around it. Assessments for periods up to FY 2025-26 will continue under the 1961 framework. New tax years run under the 2025 Act. Notices, appeals, refunds and recoveries for the next several years will straddle both statutes, often inside the same taxpayer’s file. The new challans are live; the old challans remain in use until FY 2025-26 dues are cleared. A senior taxpayer with an appeal under the old law and a current return under the new one is, in practice, dealing with two governments. He will judge both by the worse experience.

The integrated payment module the e-filing portal now offers, allowing payments across both Acts from a single interface, is a small but telling signal: a unified experience across two statutes is the right design instinct. The same instinct must extend to assessments, faceless proceedings, refunds, grievance handling and the help content the chatbot serves. Otherwise simplification on paper becomes friction in practice, and the public never sees the gain.

The test that matters

The Act is good. Whether it succeeds is a separate question, and the answer will not be visible on 2 April. It will become visible in three places. First, how quickly officers retire 1961-era reflexes — the muscle memory of citing four-level cross-references is hard to unlearn. Second, whether the next Finance Acts resist the temptation to begin re-cluttering this clean statute with new provisos within eighteen months, which is the usual cycle. Third, whether public-facing systems — portals, kar saathi chatbot, helplines, the printed material in field offices — reflect the new structure faithfully, fast. Drafting cannot guarantee any of that. All of it depends on what happens next, inside the administration.

Section 536 ended an Act in a single sentence. The harder sentences are the ones we are about to write.

The Three-Cent Government Hour

A small number in a payments-data paper has been bothering me. Among firms most exposed to generative AI, every $1 fall in spending on online labour marketplaces by the third quarter of 2025 was matched by roughly three cents of added AI model spending. Three cents where a dollar used to sit. That is not a productivity nudge. It is a repricing of a whole category of work.

What the ratio actually says

The number comes from a Ramp analysis picked up in commentary on US federal AI policy. The exposed firms were not abandoning the work. They were buying the same first-pass output — drafts, summaries, light code, document review — at a fraction of the prior price. A slice of knowledge work has moved from a labour line item to a software line item, with the ratio between the two collapsing by more than an order of magnitude.

For private firms, this plays out through hiring and margins. For governments, it plays out through almost everything: workforce composition, training pipelines, procurement rules, and the implicit deal that lets young officers grow into senior ones.

Why tax administrations sit in the bullseye

Walk through any direct-tax office and ask what the work actually is. Reading. Drafting. Summarising. Comparing one provision against another. Translating dense statute into plainer language. Spotting the inconsistencies between a return, a third-party report and a bank statement. Almost the entire stack is language-heavy. That is exactly where the three-cent ratio bites hardest.

I have watched this from the inside. Mapping an old direct-tax statute against a new one — tracking which old section migrates where, what is dropped, what is reorganised — is genuinely difficult professional work. A few years ago that effort would consume dozens of officers for months. A current-generation model, given the right corpus and a careful prompt, will now produce a competent first draft of much of it in an afternoon. Not the final word. But a credible first pass.

The same is true of taxpayer-facing communication. Building an assistant that can field lakhs of routine questions on a new law — what the slabs are, how to elect a regime, what to fill where — was, until recently, a serious capital and talent project. Today the floor for that capability has fallen sharply. The hard part is no longer building the bot. The hard part is governance: what it is allowed to say, how its mistakes are caught, how a taxpayer appeals an answer that turned out to be wrong.

The junior officer problem

A Stanford working paper this year found a 16 per cent relative employment decline for workers aged 22 to 25 in the occupations most exposed to generative AI. Read that and a managerial instinct should fire. In any large department, the junior cadre is not just there to do work. It is there to learn. The years spent reading scrutiny files, drafting orders, sitting through hearings — those years are how a tax officer becomes a tax officer.

If the model does the first draft, what does the junior do? The wrong answer is: nothing, until they are senior enough to “supervise” the model. A supervisor who has never written the draft cannot meaningfully review one. Within a decade we would be running an administration whose middle ranks know how to prompt AI for a note but cannot tell when the note is quietly wrong on a point of law.

What the junior role should become

I think the redesign is closer to this. The junior officer is no longer the drafter. They are the evaluator, the contester, the case-builder. From day one they are taught to interrogate a machine-generated draft: where is the citation, is the authority current, does the inference survive cross-examination by a contrary view. They are taught to construct the hard cases the model gets wrong, and to document them. They become the institution’s quality control function rather than its typing pool. That is more demanding work, not less. It suits the calibre of people the service actually recruits.

A proposal worth piloting

If a tax administration wants a concrete way in, here is one. Pick a single, well-bounded workflow — say, drafting routine rectification orders, or first-level responses to grievance petitions. Build a model-assisted pipeline with three deliberate seams: a machine first draft, a structured human evaluation against a checklist, and a logged audit trail of every override. Track three numbers — time saved per case, override rate, and downstream litigation outcomes for the cases that went out. Run it for a year. Publish the numbers.

This is unfashionable advice in a moment that prefers headline pilots and grand strategies. The three-cent ratio is not going to wait for a strategy document. It is already changing what a dollar of knowledge work buys in the market. A serious department asks what that means for its own internal economics, builds the governance to capture the gain safely, and quietly redesigns its junior roles before the redesign happens to it.

The departments that get this right will not be the ones that bought the most expensive tools. They will be the ones whose officers learned, early, to argue with a machine and win.

After Aadhaar, the Productivity Test

On 28 April 2026, NITI Aayog and the Frontier Technology Hub released a roadmap called DPI@2047. The Chief Economic Adviser described India's next phase of digital public infrastructure as a total factor productivity engine. That phrase is doing more work than it looks. It marks the end of one era and the beginning of a harder one.

Reach was the easy part

The first decade of DPI was a reach problem. Could we give 1.4 billion people a verifiable identity? Could we route real-time payments at population scale? Could we plug welfare into a single pipe? JAM, UPI, DigiLocker and GeM answered yes. DPI@2047 quietly concedes that the welfare-delivery question is settled, and sets a different one. The new task is not to reach the citizen; it is to lift what the citizen, the small firm and the small farm can actually produce.

That is a different test, and most departments are not yet measuring themselves against it. The roadmap proposes eight sectoral transformations across MSMEs, agriculture, education, health, credit, energy and social protection, with a state-led, district-executed model and pilots from 2026-27. Notice the language: district-executed. The unit of accountability is shifting downwards. Productivity, unlike inclusion, cannot be claimed in a press release; it has to show up in somebody's actual output.

Why most departments will misread this

The instinctive reading of DPI 2.0 inside government will be: more APIs, more dashboards, more apps. That misreads the brief.

Phase one of DPI worked because it disentangled the rails, identity, payments and data, from the application layer. Phase two is being asked to do something subtler. It must disentangle existing work from existing process. A welfare benefit can move through a new pipe without changing what the benefit is. Productivity gains demand the opposite. The pipe is uninteresting; what changes is the work itself. Deloitte's Government Trends 2026 puts it crisply: the biggest gains come not from automating old processes but from redesigning the work itself. A UK trial of over 20,000 civil servants using generative AI for three months saved an average of 26 minutes a day per person, nearly two working weeks a year. That is not because the AI replaced anybody; it is because the work was finally allowed to be done differently.

Inside Indian government, I have watched well-meaning officers turn a transformative tool into a faster version of the form it was meant to replace. The form persists, the discretion persists, the file persists. Faster, but unchanged. DPI 2.0 will succeed or fail on whether departments are willing to give that comfort up.

Three moves a department should make immediately

Stop digitising forms; redesign the file. The unit of bureaucratic work in India is the file. Every project I have seen that put a digital wrapper around an unchanged file reproduced the same delays in colour. Pick three high-volume work-streams, write down what an ideal file looks like with AI-assisted drafting embedded in it, and re-engineer backwards. The form is downstream; the file is upstream.

Build agents that draft, not bots that retrieve. Most public-sector AI in India today is a chatbot that finds a circular. That was the right starting point. It is now the ceiling. The gain lies in agents that draft an order, prepare a notice, summarise a representation, and present a ready-to-sign output. The officer reviews and decides; the typing is gone. We are using a five-times leverage tool as a 1.2-times search tool, and calling it transformation.

Measure officer-minutes, not transactions. If DPI 2.0 is about productivity, the metric must be productivity. Most dashboards still count transactions: files moved, returns filed, calls answered. None of that tells you whether the work got lighter. The metric that should matter, and that nobody is asked to report, is officer-minutes saved per case. A department that reports this number will, within two quarters, look very different from one that does not.

The harder test is institutional will

The CEA said something else at the launch that has not been quoted enough: India has strong design capabilities, but success will depend on sustained institutional will to move from strategy to execution. That is the polite version of the real problem. Indian bureaucracy is excellent at announcing platforms and indifferent at reorganising work around them. DPI 1.0 succeeded partly because it was built outside the line department, on rails the rest of government had to either ride or be left behind by. DPI 2.0 is being handed to the line departments themselves.

So the productivity test is, in the end, a leadership test. Which Secretaries will decide that their teams write fewer pages, sign fewer files and answer fewer queries by the end of next year? Those are the departments where DPI 2.0 will arrive. The rest will get a new portal.