Inviting feedback and suggestions on the Report submitted by Committee on Knowledge Systems

1. At a Glance

• What it is: MoSPI has put out the Actionable Policy Paper of the Committee on Knowledge Systems for public comment. The paper sets out a framework for measuring how knowledge and knowledge products contribute to the Indian economy [1].
• Core idea: Knowledge drives growth, productivity, competitiveness and strategic capability. Measuring it shows where India is strong, where capabilities are missing and what to prioritise [1].
• Method: The paper does not propose one headline number. It proposes a family of thematic statistics/accounts consistent with SNA 2025, assigned to institutions through a federated model [1].
• UPSC value: It links national income accounting (GS-III), statistical governance and federalism (GS-II), and AI, R&D and the digital economy (GS-III S&T). It is also part of a wider push to measure new sectors such as the culture, space and digital economies [1].

2. Why in the News

• MoSPI invited feedback and suggestions on the Committee's Actionable Policy Paper. The last date is 12 December 2026 [1].
• The paper builds on the Base Paper (May 2026), which came out of the work of the Technical Advisory Group [1].

3. Background & Evolution

• Rationale: Knowledge is increasingly central to growth and strategic capability. AI systems now produce knowledge in ways beyond conventional human knowledge creation, which makes measurement harder [1].
• Milestones, in order:
• May 2025: MoSPI's Technical Advisory Group (TAG), chaired by Dr. R. Balasubramaniam, guides development of the measurement framework [1].
• 2025: India begins work on a Culture Satellite Account [1].
• 2025: A study estimates the Digital Economy's contribution to GDP for 2022–23 [1].
• May 2026: The Base Paper comes out of the TAG's work [1].
• 5 May 2026: The release gives this date for the Committee on Knowledge Systems, chaired by Shri Ratan P. Watal, which prepared the Actionable Policy Paper [1].

• Up to 12 December 2026: Public consultation on the Actionable Policy Paper [1].

• Related efforts: The Space Economy GDP framework (ongoing), the Culture Satellite Account and the Digital Economy GDP study [1].

• International standard: The 2025 SNA was adopted by the UN Statistical Commission at its 56th session (2025). It updates the 2008 SNA [2].

4. Core Static Facts

Item	Fact
Nodal ministry	Ministry of Statistics & Programme Implementation (MoSPI) [1]
Committee	Committee on Knowledge Systems, chaired by Ratan P. Watal; output: Actionable Policy Paper [1]
Earlier body	TAG (May 2025), chaired by Dr. R. Balasubramaniam; output: Base Paper (May 2026) [1]
Knowledge Ecosystem: 8 components	(1) Knowledge; (2) Capabilities and assets; (3) Enabling infrastructure; (4) Knowledge creation activities; (5) Knowledge products; (6) Knowledge-embedded products; (7) Knowledge-intensive entrepreneurship; (8) Knowledge application [1]
5 boundary conditions for knowledge products	Knowledge as input; knowledge content; identifiability; codification; economic value. These are broad guiding principles, not rigid criteria [1]
Measurement approach	Family of SNA 2025-consistent thematic accounts, not a single aggregate. Measuring the whole ecosystem at once is not feasible, and other countries also use several complementary accounts [1]
Prioritisation criteria	Contribution to growth; productivity; competitiveness; inclusive growth and livelihoods; future significance; cost-effective measurability [1]
Priority areas (7)	Human Capital; R&D; Creative Economy; AI systems; Data and Databases; High-Tech Products and Frontier Technologies; Digital Economy [1]
Institutional design	Federated model with 3 roles: System integrators provide the common framework. Domain institutions (sectoral ministries and departments) measure specialised components. Key partners (State Governments, regulators, research and academic institutions) support them [1]
Feedback deadline	12 December 2026 [1]
Enabling Act	None stated. This is an administrative or statistical exercise, not a statutory one [1]

5. Multi-Dimensional Analysis

Economic

• Conventional GDP may undercount intangibles: R&D, data, AI and creative output. Thematic accounts make these visible to policy [1].
• Prioritising on "inclusive growth and livelihoods" ties the measurement work to development goals, not only to frontier-tech output [1].
• Better data on capability gaps can guide where public R&D and skilling money goes. This is an inference from the paper's stated aim of finding strengths, gaps and priorities [1].

Scientific / Technological

• Treating AI systems and Data and Databases as separate priority areas reflects that AI produces knowledge beyond conventional human creation, which makes it harder to value [1].
• High-Tech Products and Frontier Technologies being measured separately points to an interest in strategic technology capability [1].

Governance / Federal

• The federated model assigns work by each institution's mandate and comparative strengths. It does not concentrate all measurement in MoSPI [1].
• State Governments are named as key partners, which brings in cooperative federalism. How strong a role they get is a likely point of debate.
• Public consultation before finalising makes the process more open and lets stakeholders shape the framework [1].

Statistical / Methodological

• Keeping the accounts consistent with SNA 2025 allows comparison with other countries. The 2025 SNA is the current international standard, adopted in 2025 [1][2].
• Flexible boundary conditions can cover new kinds of products. The cost is that they may be classified differently by different people, which raises the bar for consistency [1].
• Accounts by theme, rather than one aggregate, lower the risk of double-counting and keep the work feasible. The trade-off is that there is no single headline "knowledge GDP" number [1].

Administrative

• Many institutions will measure different pieces. Integrators must keep definitions and methods uniform across them [1].
• The cost-effective measurability criterion means data that already exists is likely to come first [1].

6. Recent Developments (last 12–18 months)

• May 2025: TAG formed under Dr. R. Balasubramaniam to guide the framework [1].
• 2025: Culture Satellite Account work starts. The Digital Economy GDP study is done for 2022–23 [1].
• 2025: The UN Statistical Commission's 56th session adopts the 2025 SNA [2].
• May 2026: The Base Paper is released. The Committee on Knowledge Systems (chaired by Ratan P. Watal; release date 5 May 2026) prepares the Actionable Policy Paper [1].
• Nov–Dec 2026: Public feedback window on the Actionable Policy Paper, closing 12 December 2026 [1].

7. Prelims Hooks

• The Committee on Knowledge Systems was set up under MoSPI, not NITI Aayog or DST [1].
• The Committee is chaired by Ratan P. Watal [1].
• The TAG on measuring knowledge was chaired by Dr. R. Balasubramaniam and formed in May 2025 [1].
• The Base Paper came from the TAG. The Actionable Policy Paper came from the Committee [1].
• The Knowledge Ecosystem has 8 interrelated components [1].
• There are 5 boundary conditions for knowledge products: knowledge as input, knowledge content, identifiability, codification and economic value [1].
• The boundary conditions are guiding principles, not rigid criteria [1].
• The paper recommends a family of thematic accounts, not a single aggregate measure [1].
• The thematic accounts are to be consistent with SNA 2025 [1].
• The federated model has 3 roles: system integrators, domain institutions and key partners [1].
• State Governments are classed as key partners, not domain institutions [1].
• AI systems and Data and Databases are listed as separate priority areas [1].
• The 2025 SNA was adopted at the 56th session of the UN Statistical Commission and updates the 2008 SNA [2].
• The Digital Economy GDP study (2025) covered 2022–23 [1].
• The feedback deadline is 12 December 2026 [1].

8. What SNA 2025 Lets India Count, and What It Still Leaves Out

• Data now counts as an asset in GDP, not only the database software
• The 2008 SNA counted a database as an asset, but not the information stored inside it [3].
• The 2025 SNA also counts the information content of electronic data used in production [3].

• So the 'Data and Databases' priority area has a real place inside core GDP. It is not a side estimate.

• Brands and customer lists are still kept out of core GDP

• Marketing assets (the value of a brand name or a customer list) were proposed for the 2025 SNA. The proposal was not taken into the draft, and the topic went to the research agenda (the list of issues still being studied) [4].

• In India's knowledge-intensive firms, a large part of the value sits in such brand and customer assets. That value stays outside the main GDP figure.

• A thematic account can show value, but it cannot raise GDP

• A satellite account (a separate table that rearranges or adds to GDP data for one sector) can show value that GDP leaves out. That value does not enter the official GDP number.
• So when a knowledge account is published, read it as a map of where value sits. Do not read it as proof that India's GDP has been undercounted by that amount.

9. Why AI and Data Are the Hardest Items to Put a Price On

• Most data is never sold, so there is no market price for it
• Firms collect and use most of their data themselves. It rarely changes hands in a market.

• The OECD says data is a stored input that existing economic statistics capture only in part [5].

• When there is no price, statisticians add up the cost, and that usually undervalues it

• The usual fallback is the sum-of-costs method: value the data by what it cost to collect, store and clean (staff, servers, software) [5].

• A dataset that cost little to build can still be worth a lot once an AI model is trained on it. Valuing it by cost misses that gain.

• AI blurs the line between knowledge as an input and knowledge as an output

• Two of the five boundary conditions are 'knowledge as input' and 'economic value' [1].
• An AI model is trained on data (an input) and then produces new code, text or designs (outputs). Count the data, the model and the output separately and the same value can be counted two or three times.
• So the 'AI systems' account will need clear rules on what is counted at which step before its numbers can be trusted.

10. Why Traditional Knowledge May Fall Outside the Definition

• The codification test favours written, owned knowledge
• To count as a knowledge product, knowledge must be codified (recorded in a fixed form such as a document, code or patent) and identifiable (clearly separate from other things) [1].
• Much of India's traditional knowledge is oral. Examples are tribal medicine, farmers' seed selection and craft techniques. No single owner holds it and nothing writes it down.

• Under these tests, such knowledge may be left out because it was never written down, not because it has no value. This is an inference from the stated boundary conditions [1].

• The flexibility clause cuts both ways

• The paper says the boundary conditions are guiding principles, not rigid criteria [1]. That leaves room to include traditional knowledge.
• But no priority area covers it. The seven priority areas are all modern sectors, from R&D to the digital economy [1].
• Measurement follows the priority list. So traditional knowledge is likely to wait the longest to be measured, even though inclusive growth is one of the stated criteria [1].

11. Measuring a Gap Does Not Close It

• India already knows its biggest knowledge gap: R&D spending
• Gross Expenditure on R&D (GERD, all spending on research by government, firms and universities) has been falling as a share of GDP since 2009–10 [6].
• It stays far below the 2% of GDP goal that India set itself under the 2013 science policy [6].

• The gap has been measured for years. Measuring it did not raise the spending.

• Cost-effective measurability can push the hardest gaps to the back

• 'Cost-effective measurability' is one of the six criteria for choosing what to measure [1].
• Areas with ready data, such as the digital economy (already studied for 2022–23 [1]), get measured first.

• Areas where India is weakest, such as informal skills and firm-level innovation in MSMEs (small businesses), often have the least data. So they risk staying unmeasured.

• What should follow: each domain ministry should report its account together with the budget it controls

• For example, the Department of Science and Technology (DST) would present the R&D account next to its own R&D spending, and the Ministry of Electronics and IT (MeitY) would do the same for the digital economy account.
• Then the account shows a gap and also names who is answerable for it.

12. Who Checks the Ministries' Own Numbers

• In the federated model, ministries measure their own sectors
• Domain institutions (sectoral ministries and departments) measure the parts of the knowledge economy that fall under their own mandate [1].
• A ministry that measures its own sector is also judged by those numbers, so it has a reason to show them in a good light.

• In the paper, the integrator's role is to provide a common framework [1]. It is not given any power to audit or reject a ministry's estimate.

• What should follow: MoSPI as system integrator should publish the method before the numbers

• Each thematic account should come with its method in writing: its data sources and its valuation rules (for example, sum-of-costs for data [5]).
• The UN took this route itself. Where a topic such as marketing assets was not ready, it put the topic on a public research agenda and asked countries for extended accounts (separate tables outside core GDP), not core estimates [4].

• MoSPI can do the same. It can mark weak accounts as 'experimental' until their methods have been tested.

• States are partners, but they hold much of the ground-level data

• States are key partners, not domain institutions [1]. Yet a lot of the data on universities, skilling and local firms is collected at the state level.
• Unless states get a clear data-sharing role and funding for it, state-level knowledge capacity will stay invisible. The national accounts cannot then show which regions are falling behind.

13. Anchors for Answers

• Data: GERD (all R&D spending as a share of GDP) has fallen since 2009–10 and is well below the 2% goal of the 2013 science policy [6]
• Report/Committee: Committee on Knowledge Systems (chaired by Ratan P. Watal), Actionable Policy Paper, 2026; TAG Base Paper, May 2026 [1]; OECD, Measuring Data as an Asset (Economics Department Working Paper No. 1731, 2022) [5]
• Comparison: The 2025 SNA counts the information content of data as an asset, which the 2008 SNA did not [3]. It put marketing assets on its research agenda and did not add them to core GDP [4]
• Scheme: Traditional Knowledge Digital Library (TKDL), which has written down traditional knowledge in a fixed form. It is the kind of codification the boundary conditions require [1]

14. Mains Relevance

• GS-III: Indian economy and issues of planning, mobilisation of resources, growth and development (national income accounting). Science and technology: developments and their effects; awareness in IT, AI and IPR-related areas.
• GS-II: Government policies and interventions; statutory, regulatory and quasi-judicial bodies; federal relations (federated statistical system).
• Possible question stems: 1. "Conventional GDP accounting under-captures the knowledge economy." Discuss the challenges of measuring knowledge products and assess MoSPI's 'family of thematic accounts' approach. 2. Examine how a federated model of statistical responsibility can improve the quality and coverage of India's official statistics. What coordination problems might arise? 3. "AI is changing the very nature of knowledge creation." Discuss the implications for national accounting and for evidence-based policymaking in India.

15. Related Topics to Study Next

• SNA 2025 vs 2008 SNA: The framework the knowledge accounts must follow; covers the treatment of data, digitalisation and intangibles.
• Satellite Accounts (Culture, Tourism, Health): The same approach of measuring a sector outside the core accounts.
• Digital Economy measurement (MeitY study, 2022–23): A priority area here and a forerunner exercise.
• Space Economy GDP framework: A parallel MoSPI/India effort to measure a frontier sector.
• GDP base revision and MoSPI statistical reforms: The setting in which the knowledge accounts will sit.
• R&D expenditure (GERD) and the ANRF: R&D is a priority area. Ties to India's low R&D spending as a share of GDP.
• IndiaAI Mission and data governance (DPDP Act, 2023): Context for the AI-systems and data/database components.
• Traditional Knowledge Digital Library (TKDL): A test case for applying codification and identifiability to traditional knowledge.

16. NCERT Concepts to Revise

• Knowledge economy (Economy): The whole paper is about measuring how knowledge drives the economy, so this is the core idea.
• Gross Domestic Product (Economy): The paper asks whether GDP undercounts knowledge assets, and thematic accounts sit outside the headline GDP figure.
• National income (Economy): Knowledge accounts follow SNA 2025 national income accounting, which is the basis for measuring value.
• National Statistics Office (Geography): MoSPI's statistics office compiles national accounts and would lead as system integrator of the federated model.
• Statistics (Economy): The article is about statistical governance: how to define, collect and standardise data on knowledge.
• Artificial intelligence (Economy): AI systems are a priority area because they create knowledge in ways that are hard to value.
• Digital economy (Economy): The digital economy is a priority area, and its 2022–23 GDP study is a forerunner exercise.
• Double counting (Economy): Counting data, AI models and their outputs separately risks counting the same value twice.
• Cooperative federalism (Polity): States are named key partners in the federated model, which links to Union-State cooperation.
• Federalism (Polity): The federated model divides measurement work among institutions, much as federalism divides powers between governments.
• Traditional knowledge (Economy): Oral, uncodified traditional knowledge may fall outside the paper's codification and identifiability tests.
• Space economy (Economy): The Space Economy GDP framework is a parallel MoSPI effort to measure a new sector.
• Orange economy (Economy): The Creative Economy is a priority area, and the Culture Satellite Account measures the same kind of sector.
• Inclusive growth (Economy): Inclusive growth and livelihoods is one of the criteria for choosing what to measure first.

17. Common Errors / Trap Areas

• Wrong body: The exercise belongs to MoSPI. It is not NITI Aayog, DST or MeitY, even though MeitY ran the earlier digital economy study [1].
• Mixing up the two papers and two chairs: The TAG (Balasubramaniam) produced the Base Paper. The Committee (Watal) produced the Actionable Policy Paper [1].
• Assuming one "Knowledge GDP" index: The paper explicitly prefers several thematic accounts to a single aggregate [1].
• Treating the boundary conditions as legal tests: They are flexible guiding principles [1].
• Misplacing States: States are key partners. Sectoral ministries and departments are the domain institutions [1].
• Unverified figure: The widely quoted "11.74% of national income" share of the digital economy (2022–23) comes from news reports. I could not confirm it from a whitelisted source, so check it on meity.gov.in before relying on it.