This article first appeared on GuruFocus.

Salesforce (NYSE: CRM) offers a compelling long-term opportunity due to its leadership in the customer relationship management (NYSE:CRM) market, expanding AI integration, and growing addressable market. because of its continuous leading position in the customer relationship management (NYSE:CRM) market, the fast-growing adoption of artificial intelligence, and rapidly increasing the total addressable market. The business model that the company provides allows subscriptions and grants profits that are predictable, moreover, the platform-based approach increases the switching costs and provides opportunities to expand within the existing client bases. Thus, theThe business model enables high visibility into recurring revenue and long-term client retention.

Standing at the forefront of the global CRM market, Salesforce has captured nearly a quarter (23%) of the market share, leaving behind formidable adversaries like Microsoft, Oracle, and SAP. The position of being number one provides Salesforce with a multilayer competitive fortifications; thus, it builds a strong economic moat.

Network Effects and Ecosystem Dominance: There are over 4,000 applications on the AppExchange belonging to the Salesforce ecosystem, reinforcing its self-expanding cycle where developers attract customers, and vice versa. This network effect, which grows stronger with the addition of new applications thus the ecosystem expands, creates a barrier to entry that competitors find it almost impossible to duplicate. Independent software vendors (ISVs) devote a large amount of time and energy in creating applications that work with Salesforce, which in turn, makes the customers think that if they switch to another platform they would be missing out on the benefits of the whole partner network.

Data Network Effects: The greater the number of customers availing of Salesforce services, the larger is the amount of the data which is being accumulated by the platform on customer interactions across different sectors and applications. This data facilitates the enhancement of AI models, predictive analytics, and benchmarking capabilities; thus, the platform continues to generate value that compounds over the years and is not easily reproduced by new entrants.

Salesforce’s artificial intelligence strategy is a key component not just because it adds features, Salealos because sforce’s artificial intelligence strategy enhances its platform differentiation and supports operational leverage.. The company introduces the next generation of AI technology and improves the algorithmic base inspiring the organizations to work different with the which they produce and hold about their own customer data.

Einstein Platform Foundation: By means of the Salesforce Einstein accouting, the platform processes 200 billion predictions a day, thus, it is leveraging the collective data of hundreds of thousands of customers for the purpose of the constant improvement of AI models. This magnitude of data processing and machine learning approach creates predictive features that do not have any equivalent among smaller competitors who do not have a similar scale of data or equal access to it.

Salesforce Empowers Generative AI Integration: By launching Einstein GPT and merging it with large language models Salesforce enters a new arena of generative AI market and value retrieval. Unlike isolated AI appliances, Salesforce’s AI is integrated with the knowledge of customer data, ongoing work processes, and the history of past interactions which makes it more precise and applicable for straight-tied AI-generated analytical views and suggestions.

Industry-Specific AI Models: In order to increase the vertical-specific AI functionality, Salesforce is working on certain technologies for the fields of healthcare, financial services, and retail. These individual models not only take into account the industry standard rules and jargon but also best practices, thereby creating additional switching costs and competitive differentiations that generic AI platforms cannot compete with easily.

Recurring Revenue Model: Salesforce’s subscription-based model provides an excellent forecast of the company’s financial outcome and adds up to the long-term investors’ value in a compounding way. The company with more than 90% of the revenue recurrence and contracts being mainly over one year gives the insiders a rare opportunity to see the metric trends moving forward. The remaining performance obligation (RPO) backlog of the company which is over $25 billion is the contracted future income and it brings both risk mitigating and growth visibility effects.

Salesforce evolved from single-app CRM to a multi-solutions customer management platform that now has several advantages in running the business and growing.

Multi-Cloud Synergies: The connected system of Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud, and Analytics Cloud is a source of valuable cross-selling potentials and a customer switching cost increase. Enterprises using multiple clouds of Salesforce enjoy unified customer data, a consistent user experience, and an integrated workflow that becomes hard to build in the same way if the applications were used across different vendors.

Industry Verticalization: Salesforce has produced vertical-specific solutions for healthcare, financial services, retail, manufacturing, and other segments. These industry clouds merge the core platform with the prebuilt processes, compliance features, and the specific data models of the industry. This verticalization strategy will sidestep a generic CRM program by offering more suitable tools, which leads to further competitive moats.

Salesforce’s major acquisitions: MuleSoft (2018), Tableau (2019), and Slack (2021), have all been integrated into its broader platform strategy, not as standalone tools but as functional extensions of the core CRM architecture. MuleSoft’s API capabilities enable connectivity across enterprise systems, making Salesforce more interoperable within legacy environments. Tableau enhances data visibility across Salesforce products, giving users embedded analytics tailored to operational workflows. Slack has become central to Salesforce’s vision of asynchronous collaboration, now embedded directly into Sales and Service Cloud interfaces.

Each acquisition has followed a clear integration path: building native connectors, embedding dashboards or features directly into Salesforce interfaces, and enabling data-sharing across clouds. This approach has allowed Salesforce to expand the surface area of customer engagement without disrupting platform cohesion.

EBITDA Productivity Trends

Between FY2022 and FY2024, Salesforce significantly enhanced its operational efficiency. According to its 10-K filings, EBITDA per employee grew from approximately $63,000 in FY2022 to over $145,000 by FY2024 , more than doubling in just two years.

This improvement was driven by a two-fold strategy:

First, Salesforce undertook a substantial restructuring in 2023, reducing its global workforce by about 10%, or over 7,000 employees.

Second, the company implemented tighter cost controls, improved operating discipline, and began integrating AI-driven productivity tools internally, helping expand operating margins from ~3% in FY2022 to ~17% in FY2024.

The net result was a leaner, more focused organization generating more value per employee a trend that aligns with broader tech-sector shifts toward profitability over pure growth.

Salesforce’s Change of Operations Dramatically

Salesforce’s expansion from about $60K EBITDA per employee in 2022 to $149K in 2025 was a huge leap with a 150% increase in operational efficiency. The report suggests that the company has undergone a fundamental restructuring of its cost base and has gained important operating leverage, likely through the use of AI for automation, process optimization, and adopting more disciplined hiring practices after the 2022 tech downturn.

Salesforce’s trajectory of improvement implies that the management’s insistence on profitability is yielding positive results, which lends credence to the investment thesis. On the other hand, Oracle’s consistent efficiency combined with the lower valuation multiple entails a strong value proposition. SAP’s lambing statistics underscore the execution risks involved in large-scale business model transitions which render it the riskiest despite its market position.

AI Integration and Competitive Positioning

Salesforce is experiencing other execution risks in its AI strategy that could generally change its competitive position and attractiveness to investors.

Technical Integration Complexity

Efficiently integrating AI across Salesforce’s really wide platform ecosystem takes the complete integration with existing workflows, data models, and user interfaces to be totally free of any bugs. An imperfect implementation of AI could site planning disruption since customers would need to operationally integrate core CRM components which they cannot omit, and this could further lead to system instability or user resistance. The shortfall of technical supports lies in maintaining platform reliability while allowing multiple clouds to introduce advanced AI capabilities is a difficult execution task.

Competitive Vulnerability

Microsoft’s superb AI know-how via the OpenAI partnership and the Azure infrastructure presents a strong competitive menace to Salesforce’s AI hopes. When Salesforce’s AI capabilities are slower than Microsoft’s Copilot integration, or else when they do not introduce any substantial improvement in productivity, enterprise clients may change to the Microsoft ecosystem for cohesive AI-revealed productivity implements. This risk is further increased due to the fact that Microsoft has already established Office 365 customer relationships and its holistic approach to the market.

ATOMVEST has a comparatively huge 48.91% portfolio concentration in a likely single position of $23.4 million. This is a very acute concentration risk that contradicts essential portfolio management guidelines. The concentration has actually increased from 40.55% to 48.91% of the portfolio, which implies either poor rebalancing discipline or severe underperformance in other investments.

VALUEACT on the other hand, follows far better diversification strategies with a 16.98% allocation, down from 22.08% but poses different issues regarding position management. The primary sizeable holding of 2.9 million shares worth $778 million denotes deep belief and their 0.30% ownership stake would make them the notable influence as an activist investor. Nevertheless, the company hasn’t made any position changes while the stock has seemingly gone down considerably in value. The change from 22.08% to 16.98% seems to be the result of price drop rather than active selling. This is odd for an activist investor who would be expected to influence outcomes.

Salesforce is a high-quality growth stock suitable for both investors who are into technology and energy and those who seek to gain from digital transformation. The firm’s dominance in the market, its stable recurring income, and the AI-based innovative developments all act to create a strong foundation for value creation in the long term. The call for investment stays valid for people who believe in the ongoing digitization of commercial processes and Salesforce’s capability to run its multi-cloud platform with efficiency thus keeping its leadership role in the evolving CRM space.

Too often, AI initiatives begin with a promising tool or use case, but fail to address an immediate, measurable business problem. The most successful finance functions start small—but deliberately—with real client data and concerns. Whether it’s improving query turnaround times, accelerating dispute resolution or streamlining reconciliations, the goal is to build trust quickly through visible outcomes. These early wins build confidence—and more importantly, the momentum needed to scale. 

For example, a global building materials manufacturer engaged IBM Consulting® to tackle a backlog of over 1.2 million customer queries annually. Using real operational data, we implemented a coordinated set of AI-powered agents to triage queries, assess financial risk and automate enterprise resource planning (ERP) updates. The result was a 60% improvement in query resolution efficiency, faster deliveries and measurable cash flow gains. This approach helped the client to reduce the number of days sales outstanding (DSO) within the same fiscal year. 

On Sept. 3, the United States House Committee on Energy and Commerce Subcommittee on Health held a hearing on the critical issue of advancing American health care through artificial intelligence.

Championed by many organizations, including the American Medical Association, the use of AI in health care is seen as one of the new technology’s most important benefits. It is utilized in ways that improve patient health outcomes, provide surgical precision, enhance diagnostic accuracy and much more.

Florida State University’s Zhe He, a professor in the College of Communication and Information and director of the Institute for Successful Longevity, recently developed a study highlighting AI’s impact in diagnostic accuracy, personalized treatment plans, interpreting medical images, streamlining operations and supporting remote patient monitoring among many successful initiatives.

His research lies in the intersection of biomedical and health informatics, artificial intelligence, and big data analytics. He is an elected fellow of the International Academy of Health Sciences Informatics (IAHSI) and the American Medical Informatics Association (AMIA).

“AI has already reshaped health care in tangible ways,” He said of the new technology’s transformative impact. “We now use AI to analyze electronic health records, medical images, and even predict differential diagnosis, mortality and hospital readmissions. These tools don’t replace clinicians, but they extend their reach and help reduce diagnostic delays, personalize treatments and improve efficiency. Importantly, AI is also opening doors to rural communities by enabling new models of remote monitoring and telehealth support.”

Delaney La Rosa, teaching professor at the College of Nursing, is an educator and academic leader whose work bridges clinical practice, digital innovation, and equity-centered curriculum design. She is a nationally recognized researcher and speaker on the ethical application of AI in nursing and education.

La Rosa has expertise in health care informatics, the use of AI in health care and the integration of AI in health care education. She explores how emerging technologies can be aligned with human-centered, accessible approaches to teaching and care.

“The area that AI is transforming health care most is in the preemptive area,” La Rosa said. “We’re finding out when a patient is about to decline or when a patient is about to go septic. We are looking through data across populations.”

“In rural primary care clinics, we know that these areas are stretched for staffing,” she added. “What these AI tools can do is they can use the data across that primary office’s entire population of patients and, using the training that it was trained with, can identify patients who are most likely to develop conditions or who are most likely to benefit from preventive programs.”

Media interested in learning about the multitude of ways AI is advancing health care can reach out to Zhe He at zhe@fsu.edu and Delaney La Rosa at dwl25b@fsu.edu.

Zhe He, professor in the College of Communication and Information and director of the Institute for Successful Longevity

1. We’ve seen enormous impacts already, but what other areas in health care do you feel AI can potentially change in the future?

 I see three big frontiers:

 Patient engagement: Tools that help people better understand their lab results, medications and care plans can empower them to make more informed choices.

 Aging and chronic disease management: With our aging population, AI can play a vital role in predicting risks, supporting caregivers and promoting adherence to treatment.

 Clinical research and drug discovery: AI is accelerating trial recruitment, optimizing study design and uncovering new therapeutic targets. Over the next decade, I think these areas will be transformed just as radiology has been over the past decade.

2. How has AI impacted the work you do?

My research focuses on making health information more accessible and actionable with informatics and AI. For example, my team is developing LabGenie, a GenAI-powered system that helps older adults and caregivers interpret lab test results and generate personalized questions for their clinicians. We are also developing AI-based systems to promote adherence to cognitive training, support post-transplant care and identify strategies for HIV prevention and management for young adults. Across all of this work, AI is not an end in itself—it’s a means to improve patient engagement, adherence to treatment and shared decision making.

Delaney La Rosa, teaching professor, College of Nursing

1. What kinds of advancements has the College of Nursing made as it invests heavily in AI?

From my personal perspective, the biggest contribution we are making for AI is two-fold: The first is we lead the nation. We are the first with a degree in health care AI for our students. There is a big juggernaut out there — we must quickly learn how to use AI and then we must quickly teach our students how to use AI and use it ethically, which is another big issue, and then graduate workforce-ready individuals. Not only do we have our degree program, but we are about to release a microcredential where we develop six total courses for a certificate program called Nursing Essentials of Responsible AI. We are also beginning our postgraduate certificate. We’re leading the nation in graduating. We’re getting workforce-ready students.

 The second thing is we are leading an AI consortium and having our first launch summit that’s happening in Orlando on Sept. 17 – the Nursing and AI Innovation Consortium Launch Summit. And what that means is that we have leaders from across industries — research, practice, higher education — who are coming together, and we’re going to sit at the table and determine where we want to go next in AI.

2. How critical is the role you play in terms of AI education?

 I think the most important thing to me is our foundational essentials course. This course gives you a good grounding in the things that are not going to really change much in AI. It’s that base understanding so we can know the language. One thing that nurses are great at is being able to assess the data and information that’s coming out to see if it’s quality and it’s scientific. But you can’t do that in AI unless you have a basic understanding of how it works.