Sri Lanka's Ride-Hailing Economy: Platform Scale and Regulatory Gaps

Sri Lanka’s ride-hailing economy is visibly larger than it was a few years ago, but national measurement has not kept pace. A listed platform reports rapid growth and profit, travellers can book app-based transport at the country’s main airport, and a large three-wheeler fleet provides potential supply. None of those facts, separately or together, establishes the size or market share of national ride-hailing.

The most defensible analysis is therefore evidence-bounded. It uses PickMe as a company case, not as a proxy for the whole sector, and treats regulation, worker outcomes, competition and electrification as questions requiring better public data.

Data cut-off: 12 August 2026. Company operational explanations and impact measures are attributed to the company.

Scope and definitions

Digital Mobility Solutions Lanka PLC operates PickMe and is listed on the Colombo Stock Exchange. Its audited financial statements provide unusually strong evidence for one Sri Lankan platform. They do not provide a national census, and their operating totals combine trips and deliveries.

The distinction between revenue and gross transaction value is also important. PickMe defines gross transaction value, or GTV, as the aggregate monetary value of trips and deliveries processed through its platform. Most of that amount represents gross earnings generated for drivers and merchants. GTV is a non-SLFRS operating measure. Company revenue consists of the net platform and service fees recognised under the applicable accounting standard.

No ride-hailing-specific national market series or regulator-published operator-share table was identified in official sources reviewed through the cut-off. The earlier US$8.77 million market estimate, US$42.6 million 2034 scenario and 70%/25% operator split are consequently removed.

What PickMe’s results establish

PickMe’s audited 2025/26 Annual Report, for the year ended 31 March 2026, reports:

Company measure	FY2024/25	FY2025/26	Reported change
Revenue	Rs5.84bn	Rs8.68bn	+49%
Gross transaction value	Rs56.9bn	Rs84.5bn	+49%
Operating profit	about Rs1.6bn	about Rs3.1bn	+90%
Net profit	about Rs1.2bn	about Rs2.2bn	+88%

These results overturn the legacy statement that profitability remained elusive. They demonstrate a profitable and growing listed platform. They do not isolate ride-hailing from delivery, measure Uber, identify cash and street-hail activity, or establish total sector value.

The latest interim filing for the three months ended 30 June 2026 is unaudited. It reports revenue of Rs2.512 billion, 40% above the year-earlier quarter; operating profit of Rs833 million, up 38%; and consolidated profit of about Rs631 million, up 45%. GTV rose 48% to Rs25.3 billion, while total platform movements rose 43%.

Management attributed a two per cent sequential decline in movements and one per cent decline in net revenue to fuel rationing, constrained driver availability and affordability pressure. That explanation is plausible but remains management commentary. One quarter does not establish a national demand elasticity or long-run growth rate.

Platform scale and economic contribution

The annual report says more than Rs73 billion was distributed to over 167,000 independent drivers and riders and more than 5,000 merchants during FY2025/26. It also reports a 14% increase in driver net earnings and Rs2.7 billion in taxes.

These measures help describe PickMe’s ecosystem, but they require careful labels. “Independent” is the company’s contractual description, not a judicial finding about employment status. The number of registered or earning providers is not a full-time-equivalent employment measure. An aggregate distribution does not show the median driver’s hourly net income after fuel, vehicle finance, maintenance, insurance, waiting time and platform charges.

A credible labour assessment would need hours logged on and engaged, completed trips, cancellations, gross fares, each deduction, operating expenses and earnings distributions by location and vehicle type. It would also need to examine safety, deactivation, complaints and access to review. The public filings do not answer those questions.

Mobility context without a false market total

The Department of Census and Statistics’ Statistical Pocket Book 2025 reports 8.45 million registered vehicles in 2024, including 1.18 million three-wheelers. A 2026 UNDP policy brief uses Department of Motor Traffic data to report 1.20 million motor tricycles in 2025.

This is a large asset base, but registered stock is not the number of roadworthy vehicles, taxis, active app drivers or daily available rides. Private use, inactive registrations and activity across several channels prevent a direct conversion.

Bandaranaike International Airport’s passenger guide currently identifies both Uber and PickMe taxi options. This establishes current availability at a high-value transport node, not coverage in every district. Tourism provides additional demand context, but visitor totals cannot be translated into platform trips without booking data.

Competition and the measurement gap

The evidence supports the presence of at least two prominent app-based operators. It does not support the legacy 70% PickMe, 25% Uber and 5% other split. A CSE research report described a PickMe–Uber duopoly, but its operating data were derived from company research and it did not provide an authoritative share series.

Competition should be assessed across more than app downloads. Relevant measures include active riders and drivers, fulfilled movements, geographic coverage, waiting time, effective fares and commissions, multi-homing, service quality, complaints and switching. Publishing consistently defined aggregates would improve policymaking without requiring disclosure of personal or commercially sensitive microdata.

Regulatory architecture and public interest

The Draft National Land Transport Policy 2025 addresses paratransit, integrated digital mobility platforms, safety, accessibility and transport data. Its own commencement language makes effectiveness conditional on approval, and public comments were invited through January 2026. It should therefore be treated as a proposal, not enacted ride-hailing regulation.

The draft also reflects Sri Lanka’s division of transport responsibilities between national institutions and Provincial Councils for intra-provincial passenger services. Platform operations can cross those practical boundaries, raising questions about coherent licensing, vehicle standards, insurance and complaint handling.

A proportionate framework would identify who is responsible for driver and vehicle verification, fare and surcharge transparency, emergency support, accessible service, incident reporting, commercial insurance, platform records and appeal of material decisions. The design should also distinguish safety and consumer protection from price control, so that regulation does not unintentionally reduce supply or prevent service innovation.

No national ride-hailing-specific statute or regulator-published market series was identified in the official sources reviewed. That is a research finding, not a categorical legal opinion. Operators and drivers should obtain current advice on national, provincial and local requirements.

Data governance before January 2027

Ride-hailing can involve precise location, routes, identity, telephone, device, payment-linked records, driver documents, ratings and inferred behaviour. These data can improve dispatch and safety, but they also create risks of over-collection, unauthorised access, unfair profiling and indefinite retention.

Sri Lanka enacted the Personal Data Protection Act No. 9 of 2022 and amended it in 2025. Extraordinary Gazette No. 2498/16, dated 22 July 2026, appoints 1 January 2027 for sections 2 and 3, Part I processing obligations and Part III controller and processor duties. It does not mean that every right, enforcement power and penalty begins on that date; commencement must be checked provision by provision.

Platforms should map data and responsibilities now: identify a lawful purpose, minimise collection, define retention, control access, secure processors and cross-border flows, assess high-risk uses, prepare incident response and give people usable explanations and channels for review. This is prudent governance as well as legal preparation.

Electric three-wheelers

UNDP’s 2026 electric three-wheeler policy brief identifies potential savings and lower emissions from fleet electrification. Its possible US$500 million annual fuel-import saving assumes full electrification and is a modelled scenario, not a forecast.

The current UNDP eTukTuk pilot covers 208 vehicles. Scaling requires conversion and road-safety standards, affordable finance, charging access, suitable insurance, trained technicians, after-sales support, battery durability and end-of-life management. Ride-hailing platforms could help recruit vehicles and measure utilisation, but a pilot should compare total ownership cost, downtime, earnings and battery performance with a credible conventional baseline.

Assessment

PickMe’s audited results establish material platform scale, rapid growth and profitability. They do not establish the size of Sri Lanka’s ride-hailing market because the company’s revenue and GTV aggregate trips and deliveries, while comparable national and competitor series are absent.

The priority is therefore better measurement and a clear public-interest framework. Reporting active supply and movements in privacy-preserving aggregates, defining platform and driver responsibilities, implementing data governance and testing electric vehicles against real operating costs would support better decisions. Until those foundations exist, a precise 2034 market forecast would add confidence without evidence.