Salesforce

Kazem Haki, Dorsa Safaei, Adolfo Magan, M. Griffiths

The widespread applications of generative AI (GenAI) have sparked significant interest, with many organisations eager to leverage its transformative potential. Rather than focusing on individual organisations, this study examines GenAI integration within enterprise platforms, which are extensively adopted by many organisations and thus amplify both the benefits and risks of GenAI. We offer targeted recommendations for enterprise platform owners and their complementors, addressing challenges they face when integrating GenAI into these platforms. Drawing on a case study of Salesforce's experience, we recommend actions in three foundational areas – platform capability, architecture and governance – ensuring that our guidance is broadly applicable across enterprise platforms. In platform capability, we advise developing a unified GenAI stack built on existing platform services, offering generic and industry‐specific GenAI use cases to accelerate customer adoption and providing tools for customisation and creation of new use cases to enhance GenAI's transformational impact. For platform architecture, we recommend adding new layers for accommodating diverse GenAI foundation models and creating a trusted environment for secure data access, privacy and content monitoring. We also recommend implementing a prompt architecture to improve content relevance and accuracy. In platform governance, we recommend establishing new mechanisms to mitigate GenAI risks. Partnerships with GenAI providers and proactive investments in GenAI are essential to retain critical GenAI technologies. Personalised consultancy and training along with joint design and implementation with platform customers are also recommended. These combined actions, pursued in parallel across capability, architecture and governance, form a sustainable roadmap for GenAI integration in enterprise platforms.

Sandipkumar Patel, Kirill Patyrykin

This study explores the strategic impacts of Salesforce automation tools on organisational competitive advantage and strategic dimensions, with a focus on mid-sized firms in emerging markets. Adopting a mixed-methods approach, the research combines quantitative data from surveys and qualitative insights from case studies to evaluate how Salesforce automation influences key business outcomes. The results show that Salesforce significantly enhances organisational agility, customer-centric innovation, and strategic alignment, contributing to improvements in competitive advantage. Quantitative analysis reveals a strong positive relationship between Salesforce adoption and organisational performance, with R-square values of 0.986 and 0.989 for competitive advantage and strategic dimensions, respectively. Qualitative findings highlight the themes of improved sales efficiency, increased customer retention, and more effective decision-making, aligning with previous literature on the benefits of CRM systems. Despite the overall positive impact, the study also identifies a negative relationship between one specific Salesforce automation tool and strategic dimensions, indicating varying effects depending on tool implementation. The study’s findings underscore the importance of aligning Salesforce adoption with strategic goals to maximise its potential. Practical implications for organisations include fostering cross-functional collaboration and focusing on customer-driven innovation. The study also suggests directions for future research, particularly in examining the long-term impacts of CRM tool adoption in larger organisations and diverse industries

Jiten Sardana, Rahul Brahmbhatt

In the digital world, there is little room for error when securing data exchange, and industries that work with sensitive data, such as healthcare and retail, depend on it. This paper discusses the integration of Salesforce Marketing Cloud (SFMC) with the healthcare and retail platforms by assessing the methods of data exchange for securing the data operating efficiency and ensuring adherence to stringent privacy regulations such as HIPAA and GDPR. While the technologies that touch upon privacy, such as AI-driven intrusion detection, quantum right-resistant encryption, and zero trust architecture, are new on the block, they are fast emerging as effective ways of keeping sensitive data in trust while still being exchanged. Since machine learning is used in AI intrusion detection systems, they can detect security threats proactively and mitigate them in real time, increasing breach response time. Being quantum resistant corresponds to the face of the advent of quantum computing, which puts traditional encryption methods at risk. Building on the principles of zero trust frameworks, security multiplies with continual verification of users and devices to lessen the risk of unmetered access. For instance, in the healthcare sector, these technologies guard Electronic Health Records (EHR) and remain firm within the regimes of regulatory frameworks. In retail, they keep bank accounts, payment histories, and customers' personal data in the loyalty programs. As technologies evolve, healthcare and retail companies should adapt to such forward-facing security strategies and adopt zero-trust models, AI, and quantum encryption to stay ahead of the foreseeable threats. This article provides insight into these technologies as practical solutions that will allow us to secure the data exchange processes, ensure compliance, and retain consumer trust in the increasingly complex digital environment.

Yutong Dai, Krithika Ramakrishnan, Jing Gu, Matthew Fernández, Yanqi Luo, Viraj Prabhu, Zhenyu Hu, Silvio Savarese, Caiming Xiong, Zeyuan Chen, Ran Xu

We introduce SCUBA, a benchmark designed to evaluate computer-use agents on customer relationship management (CRM) workflows within the Salesforce platform. SCUBA contains 300 task instances derived from real user interviews, spanning three primary personas, platform administrators, sales representatives, and service agents. The tasks test a range of enterprise-critical abilities, including Enterprise Software UI navigation, data manipulation, workflow automation, information retrieval, and troubleshooting. To ensure realism, SCUBA operates in Salesforce sandbox environments with support for parallel execution and fine-grained evaluation metrics to capture milestone progress. We benchmark a diverse set of agents under both zero-shot and demonstration-augmented settings. We observed huge performance gaps in different agent design paradigms and gaps between the open-source model and the closed-source model. In the zero-shot setting, open-source model powered computer-use agents that have strong performance on related benchmarks like OSWorld only have less than 5\% success rate on SCUBA, while methods built on closed-source models can still have up to 39% task success rate. In the demonstration-augmented settings, task success rates can be improved to 50\% while simultaneously reducing time and costs by 13% and 16%, respectively. These findings highlight both the challenges of enterprise tasks automation and the promise of agentic solutions. By offering a realistic benchmark with interpretable evaluation, SCUBA aims to accelerate progress in building reliable computer-use agents for complex business software ecosystems.

Khemraj Sharma, Shanmukha Eeti, Vibhoo Sharma, Devanand Ramachandran, Jabbarov Umarbek, Sachin Kumar

Functionalities of Salesforce's customer relationship management platform with the scalability and flexibility of cloud data warehousing. This allows organizations to connect to their Salesforce data and unify it with other relevant data sources, such as marketing data, financial data, customer service data, etc., from a cloud-based data warehouse. This allows them to conduct thorough analyses and gain a comprehensive perspective on their operations. In addition, the integration automates the process of syncing data from Salesforce to the data warehouse, reducing manual data extraction and loading. Besides that, it also saves time and resources and guarantees data accuracy and consistency. Unified analytics enables organizations to produce insights-driven reports and real-time dashboards on everything from customers and sales performance to marketing campaigns and other key business metrics. This allows decision-makers to base their decisions on data and contribute to the growth of the business.