Driven by advanced analytics and AI’s increased adoption, enterprises across industries are better realizing their business goals and bolstering new initiatives. The Oil and Gas (O&G) industry is one among the industries quick to adopt data analytics and AI(DAAI) adoption with major investments seen in use cases related to improving operational efficiency, strengthening decarbonization initiatives, reducing demand fluctuations, mitigating volatility in asset management and maintenance, and enhancing cyber resilience. While major DAAI applications are seen in upstream businesses, O&G firms are also now, investing in solutions related to downstream and midstream firms to develop differentiation in the market and better realize operational efficiencies. Stimulated by post-pandemic conditions, O&G organizations are focusing more on digital initiatives that ensure workforce safety and build operational resilience. In this report, we assess DAAI adoption’s current state in the O&G industry, emerging themes causing enterprises to adopt DAAI, assessing market adoption levels and value delivered by DAAI across use cases in the O&G value chain. Furthermore, the report discusses advanced analytics and AI use cases that support O&G enterprises across the value chain and the future landscape shaping for enterprises and service providers. Scope Industry: O&G Services: DAAI Geography: global Sources: publicly available information, including 120+ DAAI case studies Contents In this report, we assess: The O&G market overview – current state of analytics, DAAI engagement types, and challenges hindering further DAAI adoption The emerging themes in O&G industry such as digital twins, generative AI applications, AI-based decarbonization initiatives, 5G’s implications in AI adoption, and AI-enhanced cybersecurity initiatives DAAI adoption use cases across O&G value chain based on value delivered and market adoption The future landscape for enterprises and providers to stay relevant under dynamic business environments Memberships Data & Analytics Artificial Intelligence (AI) Sourcing and Vendor Management

The global spend on AI is growing as enterprises across various sectors increasingly leverage its transformative potential. With the emergence of generative AI / large language models, enterprises worldwide are adopting AI at an accelerating pace to unlock new revenue streams, streamline operational costs, enhance user experiences, and establish significant differentiation within their respective industries. However, the foundation of AI development hinges on large training datasets, often tailored to the unique requirements of each business. Data Annotation and Labeling (DAL) services play a vital role in curating these high-quality training datasets essential for AI development. However, maintaining in-house DAL capabilities proves to be costly, time-consuming, and labor-intensive for enterprises. As a result, businesses are turning to external DAL service providers to implement DAL solutions. In their pursuit, enterprises seek partners capable of expediting their time-to-market by executing annotation projects at scale and speed without compromising data quality. They prioritize providers that prioritize building strong relationships, cost-effectiveness, agility, and a steadfast commitment to delivering tangible business impact and RoI at every stage of their transformation journey. Providers with a trained workforce and advanced annotation platform capabilities can efficiently guide these enterprises through the DAL landscape. This compendium provides detailed snapshots of 20 DAL solutions providers featured on Everest Group’s DAL solutions for AI/ML PEAK Matrix® Assessment 2024. Each profile offers a comprehensive overview of the provider’s operational overview, delivery locations, solutions offered, investments, and market success. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with DAL service providers, client reference checks, and an ongoing analysis of the DAL services market Contents In this report, we examine: DAL service providers landscape DAL PEAK Matrix® characteristics Providers’ leadership, presence across geographies and industries, global FTE and revenue estimates, buyer size, and overall practice structures DAL delivery locations and intellectual property overview, along with an analysis of flagship IP and key partnerships across the DAL value chain Provider investments in DAL across talent, infrastructure (centers of excellence / labs), acquisitions, research, academic partnerships, and solutions Recent case studies and projects won, with a detailed description of solutions provided Providers’ key strengths and limitations Enterprise sourcing considerations Membership(s) Artificial Intelligence (AI) Outsourcing Excellence

This report underscores synthetic data’s vital role in addressing data challenges during AI initiatives. It highlights the significance of leveraging synthetic data to train and optimize AI models effectively. Additionally, it explores best practices for using synthetic data and its effectiveness in mitigating privacy concerns and biases commonly associated with using real-world data The report also explores key industry trends, use cases and adoption patterns related to synthetic data. It examines different buyers offering synthetic data solutions, providing insights into the diverse provider landscape to assist technology buyers in making informed decisions. Furthermore, the report will educate professionals developing AI/ML solutions on the benefits of synthetic data. It offers a comprehensive understanding of synthetic data’s working principles, highlights key nuances, and equips professionals with the knowledge necessary to leverage synthetic data effectively, thereby enhancing their AI/ML projects. Contents: In this report, we examine: An overview of synthetic data Synthetic data’s role in the AI development cycle Key applications and adoption of synthetic data across different industries The synthetic data supplier ecosystem Scope: Industry: cross-industry Geography: global Membership(s) Artificial Intelligence (AI) Outsourcing Excellence

Amid the macroeconomic headlines, many enterprises seek a proven RoI track record before committing to investments in Analytics and AI. Additionally, a stringent regulatory environment is prompting enterprises to cautiously approach the adoption of generative AI. These enterprises are seeking assistance from analytics and AI services specialists to run pilot projects and scale up implementations. This demand is driving providers to invest in deepening their data, analytics and AI capabilities and expanding their industry knowledge. In this report, we assess 26 analytics and AI services specialists featured on the analytics and AI services specialists PEAK Matrix® 2024. Scope: Industry: data and analytics Geography: global The assessment is based on Everest Group’s annual RFI process for the calendar years 2022 and 2023 H1 (January-June), interactions with leading analytics and AI services specialists, client reference checks, and an ongoing analysis of the analytics and AI services market Contents: This report features detailed profiles of 26 analytics and AI services specialists and includes: Everest Group’s PEAK Matrix® evaluation of analytics and AI service providers, categorizing them into Leaders, Major Contenders, and Aspirants Providers’ key strengths and limitations Membership(s) Data & Analytics Artificial Intelligence (AI) Outsourcing Excellence

The global spend on AI is soaring as enterprises across diverse sectors increasingly tap into its transformative potential. With the emergence of generative AI / Large Language Models (LLMs), enterprises worldwide are swiftly adopting AI to unlock new revenue streams, reduce operating costs, enhance user experiences, and gain significant industry differentiation. However, at the core of AI development lies the need for large training datasets, a challenge met by Data Annotation and Labeling (DAL) services. However, managing DAL capabilities in-house appears to be costly, time-intensive, and resource-draining for enterprises. As a result, businesses are outsourcing DAL solutions to external providers. In their quest, enterprises seek partners capable of accelerating their time-to-market with annotation projects delivered at scale and speed without compromising data quality. They prioritize providers that emphasize relationship-building, cost-effectiveness, agility, and a steadfast commitment to deliver tangible business impact and RoI throughout their transformation journey. Equipped with trained workers and robust annotation platforms, these providers efficiently guide enterprises through the DAL landscape. In this report, we assess 19 providers featured in the Data Annotation and Labeling (DAL) solutions for AI/ML PEAK Matrix® Assessment 2024. Each profile offers a comprehensive overview of the provider’s strengths and limitations, enabling enterprises to make informed decisions as they navigate the evolving DAL landscape. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with DAL solutions providers, client reference checks, and an ongoing analysis of the DAL services market Contents In this report, we examine: DAL solutions providers’ landscape DAL PEAK Matrix® characteristics Enterprise sourcing considerations Membership(s) Artificial Intelligence (AI) Sourcing and Vendor Management

Enterprises currently face the challenge of harmonizing value realization and experimentation in their Data and Analytics (D&A) investments amid prevailing macroeconomic conditions. They are striving to attain RoI and tangible business outcomes from their D&A initiatives. At the same time, the advent of technologies such as generative AI is compelling enterprises to explore and establish a robust data foundation to effectively leverage these technologies. D&A service providers, including IT/BPO firms and consulting companies with extensive D&A capabilities, domain expertise, and readily deployable accelerators, can assist enterprises in reducing time-to-value and improving business outcomes by facilitating consistent and data-driven decision-making. Their recent strides in next-generation technologies and their shift toward delivering direct business value for clients can help enterprises navigate the market’s complexities. This compendium provides detailed profiles of 27 IT service providers featured on Everest Group’s D&A Services PEAK Matrix® 2023. Each profile offers a comprehensive snapshot of the provider’s service focus, key Intellectual Property (IP) / solutions, domain investments, and case studies. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading D&A service providers, client reference checks, and an ongoing analysis of the D&A services market Contents In this report, we examine: D&A service provider landscape D&A Services PEAK Matrix® characteristics Providers’ leadership, presence across geographies and industries, global FTE and revenue estimates, buyer size, and overall practice structures D&A delivery locations D&A intellectual property overview, along with an analysis of flagship IP and key partnerships across the D&A value chain Provider investments in D&A across talent, infrastructure (centers of excellence / labs), acquisitions, research, academic partnerships, and solutions Recent case studies and projects won, with a detailed description of solutions provided Providers’ key strengths and limitations Membership(s) Data & Analytics Sourcing and Vendor Management

Enterprises are struggling to strike the right balance between value realization and experimentation through their D&A investments. While Return on Investments (RoI) and direct business outcomes from D&A initiatives are becoming key priorities for enterprises, emerging technologies such as generative AI are pushing enterprises to experiment and build a solid data foundation to enable these technologies. Current  themes in the market such as data modernization, data observability, and D&A and sustainability are being driven in conjunction with these two forces. As a result, enterprises are looking to rationalize their D&A spend, evaluate key metrics to measure RoI of their D&A investments, build a strong data foundation, and experiment with generative AI. This research covers a comprehensive analysis of the D&A services market based on Everest Group’s proprietary database of D&A deals, interactions with leading D&A  providers and enterprises, and an ongoing analysis of the D&A services market. Scope All industries and geographies Contents In this report, we examine: D&A services adoption – global D&A services market size and growth, geography-wise adoption, industry-wise adoption, adoption by buyer size, and key D&A demand themes The dichotomy in the D&A market – value realization from D&A and experimentation driven by generative AI Key implications for service providers and enterprises Membership(s) Data & Analytics Sourcing and Vendor Management

Enterprises are struggling to strike the right balance between value realization and experimentation through their Data and Analytics (D&A) investments amid the macroeconomic conditions. They are prioritizing RoI and direct business outcomes from D&A initiatives. At the same time, the emergence of technologies such as generative AI is pushing enterprises to experiment and build a solid data foundation to enable these technologies. D&A service providers, which include IT/BPO firms and consulting companies with a broad set of D&A capabilities, domain expertise, and off-the-shelf accelerators, can help enterprises reduce the time-to-value and improve business outcomes through consistent and data-driven decision-making. Their recent investments in next-generation technologies and their transition toward driving direct business value for their clients can help enterprises navigate the market’s dichotomy. In this report, we analyze 27 D&A service providers featured on Everest Group’s D&A Services PEAK Matrix® 2023 and highlight the strengths and limitations of each provider. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against each other. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2023, interactions with leading D&A service providers, client reference checks, and an ongoing analysis of the D&A services market Contents In this report, we examine: D&A service provider landscape D&A Services PEAK Matrix® characteristics Enterprise sourcing considerations Membership(s) Data & Analytics Sourcing and Vendor Management

Driven by the exponential growth of data and the impact of the pandemic, enterprises have rapidly adopted Artificial Intelligence (AI) as a strategic tool to gain a competitive edge and enhance their business models. Recognizing its potential, they seek to leverage AI to reduce dependency on human workforce and unlock new revenue streams while cutting costs. As a result, enterprises are striving to develop improved AI tools and technologies. However, implementing AI has its own set of challenges such as availability of high-quality curated data and responsible AI implementation. In this report, we discuss the importance of high-quality curated data in the success of enterprises’ AI initiatives. We explore different aspects of preparing high-quality data such as data annotation, using synthetic data when real data is insufficient, incorporating a human-in-the-loop approach, and ensuring data inclusivity and mitigation of biases. Additionally, the report examines emerging trends in AI data services that enterprise should consider before making implementation decisions. Scope  All industries and geographies Contents In this report, we examine: AI / Machine Learning (ML) life cycle Features and benefits of data annotation and labeling Importance of AI-assisted data annotation and synthetic data Human workforces’ role in the AI life cycle Data annotation and labeling services ecosystem Emerging trends in AI data services Membership(s) Artificial Intelligence (AI) Sourcing and Vendor Management

Enterprises looking to adopt Artificial Intelligence (AI) initiatives are struggling to implement them at scale due to data-related challenges, the inability to acquire skilled talent, advanced IP, and lack of AI and cloud capabilities. As a result, they are turning to analytics and AI services specialists to serve their needs. In turn, these providers are improving their capabilities through investments in talent, products and platforms, partnership, industry expertise, and AI-based solutions tailored to serve specific client needs. In this compendium, we provide detailed and fact-based profiles of 22 analytics and AI services specialists featured on Everest Group’s Analytics and AI Services Specialists PEAK Matrix® 2022. Each profile presents a comprehensive overview of the provider’s service focus, key Intellectual Property (IP) / solutions, domain investments, and case studies. Scope Industry: data and analytics Geography: global The assessment is based on Everest Group’s annual RFI process for calendar year 2021 and 2022 H1 (January-June), interactions with leading analytics and AI services specialists, client reference checks, and an ongoing analysis of the analytics and AI services market Contents In this report, we examine: Specialist providers’ leadership, presence across geographies and industries, and global revenue estimates Partnership overview along with key IP and overall IP strategy Technology provider investments across talent, infrastructure (centers of excellence / labs), acquisitions, research, academic partnerships, and solutions Recent case studies Key strengths and limitations Membership(s) Data & Analytics Artificial Intelligence (AI) Sourcing and Vendor Management