Competition Law and Competition Challenges in Smart Economies

1. Introduction

A smart economy is an economy in which economic activity is increasingly organised through digital platforms, artificial intelligence, big data, cloud computing, Internet of Things (IoT), smart devices, digital payments, algorithms, connected infrastructure and automated decision-making.

Competition law in such an economy is no longer concerned only with traditional issues such as price fixing or territorial restrictions. Market power may arise from control over data, algorithms, operating systems, app stores, digital ecosystems, interoperability standards, network effects and access to essential digital infrastructure.

The European Commission has specifically recognised data as an important input into digital services and AI, while its IoT sector inquiry identified concerns involving tying, defaults, data accumulation and interoperability.

In India, the Competition Act, 2002—particularly Sections 3, 4, 5 and 6—provides the principal framework, supplemented by the developing jurisprudence of the Competition Commission of India (CCI), NCLAT and courts.

2. Meaning of a Smart Economy

A smart economy generally combines:

1. Artificial intelligence
2. Big-data analytics
3. Cloud computing
4. Internet of Things
5. Smartphones and operating systems
6. Digital platforms and marketplaces
7. Digital payment systems
8. Autonomous and connected vehicles
9. Smart homes and cities
10. Algorithmic pricing
11. Digital advertising
12. Blockchain and distributed technologies
13. Digital financial services
14. Connected energy and transportation systems

The defining characteristic is that technology, data and network effects become economically significant competitive resources.

3. Why Smart Economies Create New Competition Problems

A. Network Effects

A platform becomes more valuable as more users join it.

For example:

More users → more sellers → more transactions → more data → better service → more users.

This can create a self-reinforcing competitive advantage.

A successful platform may therefore become difficult for new competitors to challenge even without charging high prices.

B. Data as a Competitive Asset

Traditional competition analysis often concentrates on price.

In smart economies, however, a firm may obtain market power through control over:

• consumer data;
• transaction data;
• location data;
• behavioural data;
• search data;
• IoT data;
• advertising data;
• AI-training data.

The European Commission has recognised that access to relevant data can materially affect firms' ability to compete, including in AI-related markets.

Competition concerns

A dominant enterprise may:

• deny competitors access to data;
• provide inferior data access;
• combine datasets across markets;
• use customer data to compete against business users;
• impose discriminatory data-access conditions;
• prevent data portability.

4. Algorithmic Competition Problems

Algorithms can make markets more efficient but can also create competition risks.

Potential problems

1. Algorithmic collusion

Competitors may use algorithms that automatically adjust prices.

2. Coordinated pricing

Algorithms can make it easier to implement or monitor coordination.

3. Personalised pricing

A platform may charge different consumers different prices based upon collected information.

4. Algorithmic discrimination

A dominant platform may rank competing products or services differently.

5. Self-preferencing

A platform may use its algorithm to favour its own products.

Thus, competition authorities increasingly need to investigate how algorithms operate, rather than merely looking at written agreements.

5. Platform Dominance and Gatekeepers

Smart economies frequently contain platforms operating simultaneously at several levels.

For example:

Operating system → app store → payment system → advertising → search → cloud → AI services

This creates the possibility of ecosystem dominance.

A company dominant in one market can potentially leverage that position into another market.

This raises concerns involving:

• tying;
• bundling;
• self-preferencing;
• discriminatory access;
• exclusive dealing;
• interoperability restrictions;
• refusal to deal;
• anti-steering restrictions;
• default arrangements.

6. Interoperability Problems

Smart economies depend upon interconnected systems.

Examples include:

• smart watches ↔ smartphones;
• EVs ↔ charging networks;
• smart appliances ↔ voice assistants;
• payment applications ↔ banking systems;
• cloud services ↔ software;
• AI models ↔ data platforms.

A dominant firm controlling an important interface can potentially disadvantage competitors by restricting interoperability.

The EU consumer-IoT inquiry identified fragmentation, proprietary technology and control over interoperability as potential competition concerns.

7. Lock-In and Switching Costs

Consumers may become dependent upon an ecosystem.

For example:

Device → operating system → app store → cloud account → purchased applications → stored data.

Leaving the ecosystem may result in:

• loss of purchased content;
• loss of data;
• retraining costs;
• loss of compatibility;
• switching costs;
• inconvenience.

High switching costs can reduce competitive pressure even when alternative products technically exist.

8. Competition and Smart Device Ecosystems

Smartphones, watches, televisions, vehicles and home devices increasingly operate as ecosystems.

A company controlling the operating system may also control:

• app distribution;
• payments;
• advertising;
• search;
• default applications;
• APIs;
• user data.

This creates opportunities for leveraging and foreclosure.

9. Competition and AI

AI creates several new competition questions.

A. Access to computing power

Advanced AI requires substantial:

• GPUs;
• cloud infrastructure;
• computing capacity;
• energy;
• specialised chips.

If access to these inputs becomes concentrated, downstream AI competition may be affected.

B. Access to training data

Large datasets can provide an advantage in developing AI systems.

C. Foundation-model concentration

A small number of firms may control important foundation models.

D. Distribution

A powerful AI model may be integrated into:

• search engines;
• operating systems;
• browsers;
• office software;
• smartphones;
• cloud services.

E. Acquisitions

Large technology companies acquiring AI startups may raise questions concerning:

• nascent competition;
• innovation;
• access to technology;
• future competitive constraints.

10. Smart Economy and Merger Control

Traditional merger thresholds based primarily upon turnover may fail to capture some digital acquisitions.

A startup may have:

• low revenue;
• high user numbers;
• valuable data;
• important technology;
• strong innovation potential.

Consequently, competition authorities increasingly examine:

• transaction value;
• user numbers;
• data assets;
• innovation pipelines;
• ecosystem effects;
• potential competition.

This is particularly important for killer acquisitions and nascent competitors.

11. Six Important Case Laws

Case 1: Umar Javeed & Others v. Google LLC

CCI, Case No. 39/2018, 20 October 2022

This is one of India's important digital-economy competition decisions.

The CCI examined Google's Android ecosystem and identified several interconnected relevant markets, including:

• licensable mobile operating systems;
• app stores;
• general web search;
• mobile browsers;
• online video hosting.

The case illustrates how competition authorities can examine a digital ecosystem rather than treating every technological product in isolation. CCI imposed a substantial penalty and behavioural directions concerning Google's Android practices.

Significance

It demonstrates:

• ecosystem dominance;
• tying and bundling;
• leveraging;
• defaults;
• pre-installation;
• platform dependence;
• network effects.

Case 2: Federation of Hotel & Restaurant Associations of India v. MakeMyTrip

CCI, Case No. 14/2019 and connected matter, 19 October 2022

The CCI examined competition issues concerning online travel platforms.

The case involved allegations relating to:

• market power;
• preferential treatment;
• price parity;
• exclusivity;
• exclusionary arrangements.

The CCI's proceedings illustrate how traditional competition concepts must be adapted to online intermediation platforms.

Significance

It demonstrates the importance of:

• platform neutrality;
• access to digital marketplaces;
• parity clauses;
• vertical restraints;
• network effects.

Case 3: In Re: Updated Terms of Service and Privacy Policy for WhatsApp Users

CCI, Suo Motu Case No. 01/2021 and connected proceedings

The WhatsApp matter is particularly significant because it demonstrates the relationship between data practices and competition law.

The CCI considered concerns arising from WhatsApp's updated terms and privacy policy and the implications of increased data sharing within the Meta ecosystem. The CCI subsequently issued its order in November 2024.

Significance

It demonstrates that competition concerns in digital markets can involve:

• data collection;
• data combination;
• privacy-related terms;
• network effects;
• leveraging;
• ecosystem expansion.

The case is important because zero monetary price does not necessarily mean absence of competition concerns.

Case 4: Kshitiz Arya & Another v. Google LLC & Others

CCI, Case No. 19/2020

The matter concerned Google's practices relating to Android-based devices and app distribution.

The CCI subsequently dealt with the case in its digital-platform jurisprudence, including issues surrounding Google's mobile ecosystem.

Significance

The case illustrates competition concerns relating to:

• smart-device ecosystems;
• app distribution;
• operating systems;
• pre-installation;
• technological dependence;
• restrictions imposed through platform architecture.

Case 5: Epic Games, Inc. v. Apple Inc.

United States litigation concerning Apple's App Store

This dispute concerned Apple's control over app distribution and payment arrangements within the iOS ecosystem.

Among the central competition issues were:

• App Store restrictions;
• alternative payment mechanisms;
• anti-steering restrictions;
• platform control;
• commissions;
• developer access.

Significance

The case demonstrates how a platform can simultaneously act as:

infrastructure provider + marketplace operator + payment intermediary + competitor.

That structural combination creates difficult questions concerning platform neutrality and vertical restraints.

Case 6: Google Shopping

European Commission, Google Search (Shopping), Case AT.39740

The European Commission examined Google's conduct concerning the display and positioning of its comparison-shopping service in general search results.

The case became an important example of self-preferencing and leveraging through search algorithms.

Significance

It demonstrates how competition law may apply when a dominant platform controls:

• search infrastructure;
• ranking algorithms;
• user attention;
• advertising;
• access to downstream markets.

12. Additional Important Comparative Authorities

Several other cases are useful for studying smart-economy competition.

Amazon Marketplace proceedings

Competition authorities have examined Amazon's use of marketplace data, relationships with sellers and possible self-preferencing.

The OECD has identified Amazon data-use and self-preferencing issues as part of the broader international digital-competition experience.

Qualcomm

The Qualcomm cases demonstrate how control over critical technological inputs, licensing arrangements and standards-related technology can produce competition concerns.

Intel

The Intel litigation illustrates the continuing importance of exclusionary rebates and foreclosure analysis where a technologically powerful incumbent uses commercial arrangements that may affect competitors.

13. Key Competition Challenges in Smart Economies

14. Essential-Facility Issues

Smart economies can create digital essential facilities.

Potential examples include:

• dominant app stores;
• payment infrastructure;
• cloud infrastructure;
• essential APIs;
• interoperability interfaces;
• critical datasets;
• digital identity infrastructure.

A refusal to provide access may constitute an abuse of dominance where the applicable legal test is satisfied.

However, competition law should distinguish genuine essentiality from situations where competitors merely prefer access to another firm's infrastructure.

15. Consumer Welfare in Smart Economies

Consumer welfare cannot always be measured through price.

Digital services may be:

Free in monetary terms but costly in data, privacy, attention or switching costs.

Consequently, competition analysis may consider:

• quality;
• privacy;
• innovation;
• choice;
• interoperability;
• security;
• data portability;
• service quality;
• switching costs.

This does not mean that every privacy problem is automatically a competition-law violation. The competition-law inquiry still requires establishing the relevant market, market power and the applicable theory of harm.

16. Role of Competition Authorities

Competition authorities in smart economies increasingly need:

1. Technical expertise

Authorities need specialists capable of understanding:

• algorithms;
• AI;
• cloud architecture;
• APIs;
• data structures;
• blockchain;
• IoT.

2. Data analysis

Economic analysis increasingly requires large-scale datasets.

3. Faster intervention

Digital markets can change rapidly.

4. Merger monitoring

Acquisitions involving startups and technology assets may require closer examination.

5. Inter-agency cooperation

Competition authorities may need to coordinate with:

• data-protection authorities;
• telecommunications regulators;
• financial regulators;
• consumer-protection authorities;
• cybersecurity authorities.

17. Remedies for Smart-Economy Competition Problems

Competition authorities may employ several remedies.

Structural remedies

• divestiture;
• separation of businesses;
• limits on acquisitions.

Behavioural remedies

• interoperability;
• non-discrimination;
• access obligations;
• prohibition of self-preferencing;
• restrictions on tying;
• data portability;
• transparency obligations.

Technical remedies

• API access;
• interoperability protocols;
• technical separation;
• data portability mechanisms;
• choice screens.

The appropriate remedy depends upon the particular theory of harm and evidence.

18. Indian Legal Framework

The principal provisions of the Competition Act, 2002 relevant to smart economies include:

Section 3

Prohibits anti-competitive agreements.

Relevant digital examples include:

• algorithmic coordination;
• platform agreements;
• exclusivity;
• resale restrictions;
• information exchange.

Section 4

Prohibits abuse of dominant position.

Relevant conduct includes:

• unfair conditions;
• discriminatory access;
• refusal to deal;
• tying;
• leveraging;
• exclusionary practices.

Sections 5 and 6

Concern combinations and merger control.

These provisions become increasingly relevant to acquisitions involving:

• digital platforms;
• AI startups;
• data-rich enterprises;
• cloud companies;
• fintech platforms.

The CCI's digital-market jurisprudence has expanded considerably, including proceedings concerning Google, WhatsApp, MakeMyTrip and other technology platforms. The Government's Committee on Digital Competition also catalogued several important CCI digital-market cases.

19. Special Problem of Zero-Price Markets

One of the biggest conceptual challenges is:

How do we measure market power where consumers pay nothing?

Traditional price-based tests become less useful.

Competition authorities may instead examine:

• user engagement;
• data collection;
• quality;
• advertising exposure;
• switching costs;
• network effects;
• innovation;
• access conditions.

Thus, a service can be economically valuable even when its monetary price is zero.

20. Smart Economy and Innovation

Competition law must maintain a balance between two objectives.

Protecting competition

Preventing:

• exclusion;
• monopolisation;
• discriminatory access;
• foreclosure.

Protecting innovation

Avoiding excessive intervention that could:

• discourage investment;
• reduce technological experimentation;
• increase regulatory costs;
• interfere with legitimate product integration.

Therefore, competition law should focus on demonstrable competitive harm rather than simply penalising successful innovation.

21. Emerging Issues

Future smart-economy competition disputes are likely to involve:

1. AI foundation models
2. Generative AI distribution
3. AI training data
4. GPU and cloud concentration
5. Autonomous vehicles
6. Smart-grid platforms
7. Digital identity systems
8. Quantum computing
9. Metaverse platforms
10. Robotics
11. Digital twins
12. Smart-city infrastructure
13. Connected healthcare
14. AI-enabled financial services
15. Algorithmic pricing
16. Data portability
17. Interoperability
18. Platform-to-business discrimination

22. Conclusion

Competition law in a smart economy is fundamentally concerned with the transformation of technology, data and infrastructure into sources of market power.

The principal challenges are:

• network effects;
• data concentration;
• ecosystem dominance;
• algorithmic coordination;
• self-preferencing;
• tying and bundling;
• interoperability restrictions;
• platform lock-in;
• digital mergers;
• AI-related concentration;
• control over essential digital infrastructure.

The Indian cases involving Google Android, MakeMyTrip, WhatsApp and other digital platforms, together with international cases such as Google Shopping and Epic Games v. Apple, demonstrate the transition from conventional price-centred competition analysis toward an analysis that also considers data, algorithms, ecosystems, innovation, access and technological architecture.

The central legal challenge is therefore to ensure that technological success does not become a mechanism for excluding competitors, while at the same time ensuring that competition law does not punish legitimate innovation, efficiency or the creation of superior technological products.