The future of airport operations is increasingly shaped by advanced technologies. Leading global airports like Singapore Changi, Doha Hamad, and Tokyo Haneda have already embraced data-driven systems, contactless services, and AI-powered automation to enhance both operational efficiency and passenger experience. With rising air travel demand, especially in developing markets, building smarter airports has become a necessity rather than an option.

In the Philippines, the conversion of airports into smart airports involves the cooperation of several stakeholders such as government agencies, airport operators, airlines, technology suppliers, and passengers. Each group plays a key role in bringing together innovative solutions that enhance security, efficiency and customer experience.

Ninoy Aquino International Airport (NAIA), the country’s busiest gateway, is seeing more passengers. The trend is still on the rise as NAIA alone accommodated up to 5 million passengers in January 2026. But the surge has resulted in airport congestion and operational concerns, including long queues, bad luggage handling and delays, underscoring the need for reforms.

This study recommends the use of sophisticated technologies such as artificial intelligence, IoT, biometrics, robotics and big data to overcome these difficulties, to make procedures more efficient and to improve the passenger’s journey.

The study uses surveys, research, and personal observations to identify major issues and suggest measures that will help the Philippines achieve its greater objective of modernizing its airport infrastructure.

The Philippine agriculture industry is plagued by serious economic problems. Major perishable crops lose about 40% of their value due to subjective manual grading, information asymmetry, and transportation bottlenecks. The paper discusses the feasibility of Project Luzon Bagsakan, an integrated artificial intelligence (AI) system that can classify agricultural products, facilitate sales, and establish an Automated Knowledge Analysis Network to address major gaps in the supply chain. In this paper, we assess the technical, economic, legal, operational, and scheduling feasibility of three core AI components using the TELOS Feasibility Framework. These components are a Computer Vision Module based on a Convolutional Neural Network (CNN), for objective crop grading, a Predictive Analytics Engine for price forecasting and supply-demand matching, and a Logistics Optimization Module based on vehicle routing and backhaul optimization algorithms. Methodologically, a mixed-method approach was used to assess the AI readiness and feasibility among 65 stakeholders of La Trinidad Trading Post (LTVTP), Benguet Agri-Pinoy Trading Center (BAPTC) hub, and Balintawak Market via logic-branched digital and paper-based surveys. The study culminates in the proposal of a strategic roadmap designed to model a digitally traceable and environmentally sustainable agricultural supply chain for the Philippines. This ecosystem shows that there is a way to secure a fair value for local farmers and at the same time stabilize food prices for urban dwellers, even with a modest level of initial technological infrastructure

Philippine public procurement has operated under a robust legal framework since Republic Act No. 9184 of 2003, updated by Republic Act No. 12009 of 2024. Yet the 2025 flood control investigations, which identified approximately 421 ghost projects out of roughly 8,000 national-government infrastructure projects inspected, confirmed that procurement irregularities at scale persist not because of missing rules but because of missing integration: procurement records, audit findings, tax filings, contractor licensing status, and disqualification notices sit in five separate institutional systems that cannot be aligned in real time. This capstone study applies Design Science Research methodology to design, build, and evaluate ProcureGuard PH, a blockchain-anchored, AI-augmented procurement transparency prototype that unifies these silos into a single citizen-accessible, tamper-evident platform.

The study is guided by three research questions covering systemic gap analysis and the Senate Bill No. 1506 (CADENA Bill) legislative response, vendor qualification and eligibility enforcement through blockchain and artificial intelligence, and the prototype’s role as a demonstration vehicle for procurement transparency policy institutionalization. ProcureGuard PH implements five role-based modules, an append-only SHA-256 chained ledger, a Vendor Qualification and Eligibility Enforcement Module operationalizing the complete twelve-document RA 12009 eligibility framework including ledger-anchored NFCC computation that verifies government contract obligations across participating procuring entities, a rule-based analytics layer with seven implemented and six designed extension rules (two rule types actively firing in the current demonstration dataset), and an AI-augmented analytics layer.

Walkthrough self-evaluation confirms substantial coverage of design requirements derived from the three-lens conceptual framework. Practitioner expert evaluation was conducted via Focused Group Discussion in May 2026 with seven participants representing BAC Secretariat, Technical Working Group, Requesting Unit, Commission on Audit, Bureau of Internal Revenue, and Finance and Accounting roles; findings confirm that the prototype addresses the most consequential operational gaps identified by practitioners, and identify Senate Bill No. 1506 (CADENA Bill) Section 15 enactment as the governance prerequisite for converting technical tamper-evidence into legally actionable audit evidence. Comparative architecture assessment establishes alignment with the CADENA Bill Section 15 prima facie evidentiary standard within the system boundary.

This research assessed the current Service Transition Management practices within a suborganization of a Fast-Moving Consumer Goods (FMCG) company. The study revealed significant challenges in the current STM processes, notably insufficient knowledge transfer, inadequate documentation, and communication breakdowns. These deficiencies directly led to the operations team consistently failing SLAs, impacting business efficiency, and overall service quality. The investigation incorporated stakeholder feedback and benchmarked against industry standards, underscoring the critical need for a more structured approach for managing Information Technology (IT) product transitions.

To address these identified challenges, this study proposes an operative service transition framework - Service Transition – Dimensions, Deliverables, and Evaluation (ST-DDE) This framework systematically integrates key dimensions of service management, with essential deliverables, and a comprehensive evaluation component utilizing specific KPIs and metrics. The framework provides structured, phased approach designed to enhance efficiency, mitigate operational risks, and improve service quality and reliability of utilizing the applications. Recommendations stemming from this framework emphasize formalizing knowledge management, strengthening training, improving communication, and developing data-driven evaluation process, thereby offering a practical pathway for continuous improvement in the team’s service transition capabilities and supporting its digital transformation journey.

This paper studies the organizational readiness and performance in the adoption of agentic artificial intelligence (AI) in the medical knowledge process outsourcing (MKPO) industry, with a focus on Optum Philippines. The study discusses the transformative potential of agentic AI and presents the specific challenges posed by this AI system. MKPO companies are uncertain as to whether they are prepared to deploy agentic AI, given the current technical, workforce and governance challenges. The study adopts the conceptual framework of technology acceptance theory and recent AI adoption literature as of January 2026, to analyze organizational readiness in successful AI integration. A combination of quantitative surveys and qualitative interviews are done. The study also reviews secondary data about Optum’s use cases to evaluate AI performance. The research findings resulted in Optum having a high organizational readiness index however, barriers to adoption were identified. The study is limited to a single organization, and it acknowledges that agentic AI and its regulations are rapidly changing, so its relevance is relative at the time when the research is conducted. The research concludes that organizational readiness and technological innovation alignment are the key to sustainable business performance improvement. It recommends to invest in a more simulation-based training for clinicians, to strengthen data privacy measures, to support legacy system integration, to advance governance and monitoring frameworks, to weave AI into daily workflows, and to develop a structured AI maturity roadmap. All these will collectively unlock the full potential of agentic AI and foster responsible innovation within the healthcare outsourcing companies.