By Falak Sher Khan
Pakistan’s Digital Pakistan vision and emerging AI ambitions rest on an invisible foundation: data. Yet data, the fuel of artificial intelligence, remains unpriced, unmeasured, and largely surrendered to global platforms. Unless Pakistan aligns its digital strategy with a clear data-value framework, it risks becoming a raw-data exporter in the AI age rather than a competitive digital economy.
Artificial intelligence is rapidly reshaping the global economy, redefining productivity, competitiveness, and power. Governments now speak of AI readiness with the same seriousness once reserved for industrialization or energy security. Pakistan is no exception. Through its Digital Pakistan vision and ongoing AI policy work, the country has signaled its intent to become a digitally enabled, innovation-driven economy.
But beneath the rhetoric lies a critical blind spot that is the Wealth of Raw Data.
AI systems do not operate in a vacuum. They are trained, refined, and monetized using massive volumes of data—financial transactions, mobility patterns, consumer behavior, biometric records, and digital interactions. Pakistan generates this data at scale, yet captures only a fraction of its value. The rest flows outward, embedded in platforms, algorithms, and services owned elsewhere.
Data Is Not a Natural Resource—It Is an Economic Output
Unlike oil or minerals, data is not extracted from the ground. It is produced through economic activity. Every digital payment, tax filing, ride-hailing trip, telecom interaction, and e-commerce purchase generates structured information. That information becomes valuable only because citizens and firms participate in the digital economy.
This distinction matters for policy. Treating data as something that “just exists” leads to regulatory neglect. Treating it as an economic output—produced through transactions—forces a reassessment of ownership, pricing, and compensation.
In effect, Pakistani citizens are active contributors to AI value creation, even if they never see a line item acknowledging it.
The Invisible Transaction at the Heart of Digital Pakistan
Every digital interaction in Pakistan involves two simultaneous exchanges. Consumers purchase a service, and at the same time, they provide data. The monetary price is visible; the data price is not.
This hidden exchange explains why digital services appear cheap or free. Firms are not discounting out of generosity. They are acquiring data. More users mean more data; more data improves algorithms; better algorithms generate higher profits. This logic is especially powerful in price-sensitive markets like Pakistan, where marginal discounts unlock large increases in usage.
The result is a systematic undervaluation of Pakistani data, embedded invisibly in millions of daily transactions.
Bundling and the Failure of Market Learning
From an economic perspective, the problem is bundling. Consumers cannot buy a digital service without simultaneously selling data. They are rarely offered a genuine alternative: pay more, keep your data private.
Markets rely on price signals to function. When prices are hidden, learning is impossible. Pakistani consumers cannot know whether they are fairly compensated for their data, because they never see its price.
This undermines one of the core goals of Digital Pakistan: informed participation in the digital economy. Without transparency, digital inclusion becomes digital extraction.
Why This Matters for Pakistan’s AI Ambitions
Pakistan’s AI aspirations focus on productivity gains, improved governance, fintech expansion, and export-oriented digital services. All of these require high-quality data. Yet if data remains invisible and unpriced, three strategic risks emerge.
First, value leakage. Raw data flows to global platforms, while value-added analytics and AI products are imported back at a higher cost.
Second, policy blindness. When data is not counted as an asset, national accounts underestimate digital output and misguide investment priorities.
Third, strategic vulnerability. Critical datasets, such as financial behavior, mobility patterns, and citizen records, remain outside meaningful domestic control.
For a country seeking digital sovereignty without digital isolation, this is an untenable position.
Making Data Measurable: Tools for Policymakers
Economists have developed several approaches to estimating data’s value, each relevant to Pakistan’s policy toolkit.
Some data is traded on international markets, offering observable prices. While limited, these benchmarks provide reference points for valuation.
Another method measures how much revenue data enables estimating profits that would disappear without it. This approach aligns closely with AI policy, as it links data directly to productivity.
A third approach infers value from complementary investments. When firms spend heavily on data scientists, cloud infrastructure, and analytics tools, they reveal how valuable the underlying data must be.
A fourth examines improved decision accuracy. Better targeting, forecasting, and resource allocation all signal valuable data at work.
The most transformative but most challenging approach is cost accounting: identifying how much firms implicitly pay consumers through discounts and free services to encourage data generation. This requires visibility that current market structures do not provide.
The Case for Unbundling in Pakistan
If Pakistan is serious about building an AI-capable economy, it must make data visible. One regulatory shift would be decisive: mandatory data unbundling.
Platforms would be required to offer two prices: one that allows use of transaction data, and one that does not. This would not ban data use or undermine innovation. It would simply introduce transparency.
Consumers could make informed choices. Firms would compete openly for data. Regulators could observe market prices. National accounts could begin to reflect digital value creation.
Unbundling aligns directly with Pakistan’s stated goals of consumer protection, digital trust, and innovation-led growth.
From Digital Inclusion to Digital Equity
Digital Pakistan has emphasized access, connectivity, platforms, and services. The next phase must emphasize equity, ensuring that those who generate value also share in it.
Data pricing is not about taxing innovation or restricting flows. It is about recognizing data as an economic asset and aligning incentives accordingly. Countries that fail to do so will remain upstream suppliers in the AI economy, while downstream value accrues elsewhere.
Toward a Data-Aware AI Strategy
Pakistan stands at a crossroads. It can continue treating data as a by-product of digitization, or it can recognize it as the foundation of AI competitiveness.
The first path leads to dependency. The second leads to leverage.
As AI reshapes global power, data will determine which countries merely participate and which ones lead.
The author serves as Deputy Director General at the Institute of Strategic Communication & Economic Studies (ISCES) and previously held the appointment of Director Administration at DGPR, Pakistan Air Force. He has published extensively in leading national and international periodicals and is a specialist in strategic communication. He can be reached at ddg@iscesthinktank.org