A recent survey of 600 IT professionals reveals a new mandate from their leaders: incorporate generative AI into the technology stack — fast. IT is pushing back, raising concerns over resources, data security, and data quality. Nearly 3 in 5 IT professionals say business stakeholders hold unreasonable expectations on the speed and agility of new technology implementation. In fact, 88% of IT professionals claim they’re unable to support the deluge of AI-related requests they receive at their organization.

Why it matters: We are in a productivity and efficiency revolution with the introduction of generative AI — businesses are beginning to see productivity gains and executives want a piece of the pie. While businesses seek to stay ahead of the competition by rapidly implementing generative AI, the investment might see diminishing returns without the proper infrastructure, resources, and partners. IT must work with their leadership to ensure that quickly integrating generative AI doesn’t mean sacrificing data security and quality.

Executives are understandably excited about the promise of AI – and productivity gains are a big part of that.

Juan Perez, EVP and Chief Information Officer

Salesforce perspective: “Executives are understandably excited about the promise of AI – and productivity gains are a big part of that. CIOs and IT teams can either hang back and potentially miss the opportunity to take advantage of the technology before their competitors, or they can lead the way, rethinking how companies implement trusted AI in a responsible and sustainable manner.” – Juan Perez, EVP and Chief Information Officer

The Salesforce research found:

IT in the hotseat as pressure mounts to implement generative AI quickly

Most IT professionals surveyed (87%) believe generative AI has so far met or exceeded its hype. As a result, IT is tasked with getting the technology implemented — and fast

Generative AI is the #1 technology IT feels pressure to onboard quickly.

As demand increases, IT is at the front lines.

Company leadership prioritizes speed above security and data quality, IT says

According to the research, IT teams identified the C-suite as the #1 influencers demanding fast generative AI implementation. When asked about their team’s priorities compared to those of their leadership, IT reports they’re focused on data security and quality while they view their leadership as prioritizing speed‌. 

Salesforce’s recent Connectivity Benchmark Report further highlights IT’s data concerns, with 95% of IT leaders reporting integration issues as an impediment to AI adoption.

As they juggle various priorities, nearly half (48%) of IT professionals agree that they struggle to find a balance between speed, business value, and security when implementing new technology. 

IT faces AI challenges, putting fast implementation at risk

Amid this pressure to deliver, IT faces rising concerns on how to budget and resource effectively to implement new technologies like AI. 

Additionally, almost one-third (31%) of IT workers say they lack the time to implement and train AI models and algorithms, and nearly half say their infrastructure can’t keep up with demand:

“For those who are ready to lead, approaches like retrieval augmented generation (RAG) can help, both reducing costs from training LLMs while keeping data safe and secure and giving companies a faster time to market with AI-powered solutions,” said Perez.

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In partnership with Vanson Bourne, Salesforce conducted a double-anonymous survey of 600 IT professionals (200 IT leaders and 400 IT individual contributors) in Australia, France, Germany, the United Kingdom, and the United States. The survey was fielded in December 2023 and January 2024.

BACA Systems, a small business that produces equipment for the global natural stone industry, is using the Einstein 1 Platform, including Einstein 1 Sales and Service, to manage the entirety of its manufacturing process. 

At-a-glance: The BACA Systems sales team was spending too much time on manual tasks, including searching for prospect information, creating call summaries, and drafting emails. Reps also needed a way to better understand and service their clients, with a 360-degree view of their customers. 

The impact: BACA Systems moved its resource planning system to Salesforce, giving its sales team an extra edge in efficiency with generative AI powered by the Einstein 1 Platform. 

The BACA Systems perspective: “We’ve found combining Salesforce’s AI with the Einstein 1 Platform is a perfect recipe for success. It’s boosted our productivity and we are committed to continuing to integrate AI into our sales work because we see the results, both in sales growth and in how much the sales team loves using it.” – Andrew Russo, Enterprise Architect 

With Einstein 1 Sales, BACA Systems has been able to unify all of their data, simplify their tech stack, and unleash a productivity super cycle.

Ketan Karkhanis, EVP and GM of Sales Cloud

Salesforce perspective: “With Einstein 1 Sales, BACA Systems has been able to unify all of their data, simplify their tech stack, and unleash a productivity super cycle. Purpose-built Sales AI embedded in the flow of work has unlocked new opportunities of growth for their sales team.” – Ketan Karkhanis, EVP and GM of Sales Cloud 

Learn more: 

Generative AI and large language models (LLMs) are reshaping how companies build business applications for sales, customer service, marketing, commerce, IT, finance, legal, and HR teams. Behind this shift is a legion of app developers who are tapping into generative AI-powered development tools to build apps faster and augment employee experiences for the better. 

That’s a big reason why 86% of IT professionals say their jobs have become more important since the introduction of generative AI.

Here, Alice Steinglass, Salesforce’s EVP & General Manager, Platform, shares her thoughts on the future of AI-powered app development, the collaboration between developers and AI copilots, and more.

AI is what every developer, CIO, and frankly, every organization is talking about. We’re going to see a dramatic revolution in the kinds of apps available on the market — and how they’re being built.

Initially, AI was used for simple tasks like recommendation systems and voice recognition. With advancements in deep learning and Natural Language Processing (NLP), AI is now capable of helping with complex tasks such as image recognition, sentiment analysis, and predictive analytics. And with generative AI, we now see apps that are capable of generating highly personalized content like images, webpages, and emails customized for individual users. 

It’s a dramatically new way of thinking about development, and it provides a new kind of experience for the end user.

Alice Steinglass, Platform EVP & General Manager, Salesforce

AI is also changing how we build apps — moving from click-based UIs to conversational UI, from hard-coded logic to semantic LLMs, and from limited structured data to unified data layers leveraging structured and unstructured data in decision-making.

What I find so interesting about building apps with AI is the unexpected. Developers have to think of all the different scenarios that could happen — envision what kind of new workflow their end users will need. The amazing part about using a copilot is that it’s able to generate a plan in real time at runtime for the user based on the capabilities that I give it as a developer. It’s a dramatically new way of thinking about development, and it provides a new kind of experience for the end user.

With AI assisting them every step of the way, experienced developers can code and build faster. And at the same time, AI can democratize the app dev space by lowering the barrier to entry and opening the door for more business users to be able to build apps themselves. 

Q. What is the single biggest challenge in using AI for app development?

The AI revolution is a data revolution. Companies are struggling with vast amounts of data “trapped” across too many apps and silos, making it difficult to amalgamate into a single, useful dataset. With access to large quantities of data, using a hyperscale data engine like Salesforce’s Data Cloud, AI’s potential expands, especially when you can pair these new AI capabilities with your unstructured data.

When we talk about data, about 20% of it is structured data. This is what you would find in spreadsheets and transactional databases — names, customer information, and order details. However, the remaining 80% is unstructured data, including PDFs, emails, transcripts, and social media content. Previously, finding relevant information through this unstructured data was challenging, requiring exact keyword matches. 

With AI, we now have patterns like retrieval augmented generation (RAG) that help companies retrieve and use their data, no matter where it lives, for better AI outputs. 

This is transforming the way software is written and enhances the customer and employee experiences companies can offer today.

Q. What does it take to build powerful AI apps? 

First, the app needs to have access to the right data and metadata. Without the necessary data, an AI app becomes nothing more than a party trick. For example, if I asked a chatbot to simply “generate an email,” the resulting email would lack contextual relevance without the required information. Who am I sending the email to? What details should be included? Gathering all of this information can be a cumbersome task for the end user. 

This is where app development plays a crucial role. As app developers, we can take the responsibility of gathering the necessary data and metadata for the user. We can identify the structured and unstructured data, as well as any relevant information, to effectively use AI in a given scenario.

Q. What else should developers consider when building or integrating AI-powered apps in an enterprise?

It’s not enough to generate the perfect email — if a salesperson or customer agent has to manually copy and paste the content from somewhere else to send it, that becomes an extra step and hinders productivity. That’s why it’s critically important to incorporate AI into the workflow itself. This means having AI functionalities as buttons on the page, part of the copilot, and embedded into the organization’s existing workflows. 

Additionally, the AI app should have deep integrations with the systems where actions take place. In an enterprise setting, there are often numerous systems involved, with over 900 different systems being used for various tasks like creating purchase orders, checking shipping status, and placing orders. A powerful AI app not only analyzes data and provides intelligent insights, but also operates within the user’s workflow, taking real actions on their behalf. It goes beyond generating text and is capable of executing meaningful actions for the user.

Salesforce’s Einstein Copilot, for example, allows companies to create custom actions leveraging their CRM data and existing workflows, APIs, and code.

Q. How is collaboration between developers and AI copilots shaping the future of app development? 

For experienced developers who know how to write complex code, collaboration with AI speeds up the development process. Oftentimes, there’s a lot of boilerplate code that needs to be written, and one of the top requests from our developer community is test case generation with AI. This is an area where AI can truly assist. Developers can write a piece of code that is crucial for their users, and AI can provide a starting point for test cases, saving time and allowing developers to focus on making them specific to their organization. 

Secondly, collaboration with AI copilots democratizes app development by making it accessible to more people. It can help beginners get started, fill in missing information, and even explain concepts and functions. When learning new technologies, such as making an Apex callout, AI acts as a supercharged assistant, providing guidance and support throughout the process.

Lastly, AI presents an opportunity to improve the quality of the code being written, elevating the type of code that developers write and their reliability. This is just the beginning, as there is untapped potential in using AI for performance optimization, scalability, bug detection, and enhancing code reliability.

Q. How does low-code development intersect with AI and what are the implications? 

Low-code developers will play an exciting role enabling actions within AI.

When implementing AI in an enterprise setting, it becomes crucial to determine the places you want to embed AI capabilities and the actions that the copilot should be able to take. Low-code developers are often business users or administrators who have a closer connection to the needs of the business. This proximity allows them to collaborate with business stakeholders to understand their needs and implement AI solutions accordingly.

Whether it’s sending an email, initiating a purchase order, or making an order request, low-code developers can work closely with business units to understand the specific data requirements for each action. Then, they can identify the necessary data sources and integrate them into the AI system. 

Low-code tools like Prompt Builder empower Salesforce Administrators to create, ground, test, and implement AI across experiences, apps, and workflows. And, AI can also help them build these workflows. Tools like Salesforce’s CodeGen — a new, large-scale language model built on the concept of conversational AI programming — allow low-code developers to deliver on the needs of the business.

Q. What’s your vision for the future of AI-powered app development? 

AI will become an integral part of every app, creating truly personalized UX that collaborates with the user to provide intelligent insights and accomplish tasks. And, multimodal input will transform how we interact with software — particularly on mobile. 

What’s more, how we build these apps will change. AI-powered app development platforms will continue to get better at helping us realize our goals through code: democratizing development while also supercharging engineering productivity with more support, better testing, and higher quality code. Basically, it will let developers, admins, and architects spend more time on the fun part — creating and building — and less time looking up how a library works, debugging esoteric issues, or writing boilerplate tests. It’s going to be a fun time to be a builder.

As AI continues to advance, its impact on app development will become increasingly significant. From enhancing functionality to improving security measures, AI is transforming the way apps are built and experienced. With collaboration between developers and AI copilots, the democratization of AI development, and the intersection of low-code development with AI, the future of AI-powered app development looks promising. 

More information:

Salesforce released Einstein Copilot, a customizable, conversational, generative AI assistant, and we’re answering the big questions about what it is and what it can do for businesses. 

What is Einstein Copilot?

Einstein Copilot combines the power of Salesforce CRM with the convenience of an AI assistant that interacts with users in a conversational way. 

Unlike other AI assistants or copilots that lack adequate company data to generate useful responses, Einstein Copilot utilizes an organization’s own unique data and metadata to produce powerful customer insights and recommendations, while maintaining privacy and data governance and without requiring costly AI model training.

It can answer questions, summarize content, create new content, interpret complex conversations, and dynamically automate tasks for users — all from a consistent conversational UI across Salesforce’s #1 AI CRM applications. Marketers can use Einstein Copilot to build more effective digital storefronts. Customer service agents will be able to quickly handle requests, from generating replies to suggesting activities. And sales professionals can employ it to understand customers more deeply and close deals. 

Einstein Copilot comes with a library of pre-programmed capabilities, automated responses, and business tasks that the AI can perform for users when prompted. Actions can be combined to execute dynamic multi-step plans. 

How do Einstein Copilot, Data Cloud, and Einstein 1 Platform fit together?

Einstein Copilot is part of Salesforce’s Einstein 1 Platform, which integrates the user interface, a variety of AI models, and data in a single metadata-driven platform. A trusted AI platform for customer companies, Einstein 1 Platform gives companies the ability to safely connect any data to build AI-powered apps with low code and deliver entirely new CRM experiences.

How does Einstein Copilot work?

AI is only as good as the data it’s trained upon, and that’s why grounding Einstein Copilot in Data Cloud makes it so powerful. Data Cloud connects, federates, and harmonizes any data type from any product and system, and connects it back to the Salesforce applications that business users need to use every day, to deliver a comprehensive, 360-degree view of customers and power CRM, AI, automation, and analytics across any business process.

BYOL (Bring Your Own Lake) means companies can integrate any system with Data Cloud, accessing all of their trapped data from data lakes like AWS Redshift, Google BigQuery, Databricks, and Snowflake within Salesforce. They also no longer need to move data across platforms because of Data Cloud’s zero-ETL integration, and it connects to external predictive models for seamless use in Salesforce workflows.

Also, for the approximately 80% of data that is unstructured, semantic search and vector embeddings in Data Cloud unlock a brand new way to interact with data. Einstein Copilot Search enhances Einstein Copilot, providing sales, customer service, marketing, commerce, and IT teams with an AI assistant capable of solving problems and generating content by accessing real-time unstructured and structured business data.

With Data Cloud, all the relevant, trusted customer and business data — structured and unstructured, within and beyond Salesforce, across many disparate data lakes — can be unified and made available for use by every team and workflow. 

How does Einstein Copilot empower teams to work faster?

How does Einstein Copilot empower teams to work faster?

Einstein Copilot brings together an intuitive interface for interacting with AI, world-class AI models, and deep integration of the data and metadata needed to benefit from AI. 

Einstein Copilot is the only copilot with the ability to truly understand what is going on with your customer relationships.

Marc Benioff, Chair & CEO, Salesforce

All of this means Einstein Copilot, which is integrated with all Salesforce CRM applications, will provide a significant productivity boost, improve customer experiences, and increase margins.

How can companies customize Einstein Copilot?

How companies can customize Einstein Copilot for their business.

Users can customize Einstein Copilot and seamlessly embed AI prompts and actions across any CRM app with Einstein 1 Studio, a set of low-code tools deeply integrated with Data Cloud.

How does Salesforce ensure trust in Einstein Copilot?

How do we deploy conversational AI that we can trust? 

Trust couldn’t be more important to today’s businesses. In fact, Salesforce research found the likelihood of business buyers using AI to improve their experiences declined in 2023 compared to the previous year. Another study found that most people (57%) do not trust AI

Einstein Copilot addresses such concerns by serving up trusted AI interactions with privacy and security measures provided by the Einstein Trust Layer. Every AI interaction passes through the Einstein Trust Layer, part of Salesforce’s Einstein 1 Platform, which can perform functions like masking personally identifiable information (PII), scoring outputs for toxicity, and helping to protect information from unauthorized access and data breaches through zero-data retention from Salesforce’s LLM partners. 

New to the Einstein Trust Layer is customer-configured data masking, enabling admins to select the fields they want to mask, providing greater control. Additionally, the audit trail and feedback data collected from AI prompts and responses is now stored in Data Cloud, where it can be easily reported on or used for automated alerts through Flow and other Einstein 1 Platform tools. 

Salesforce believes trusted AI needs a human at the helm. Instead of asking humans to intervene in every individual AI interaction, Salesforce is designing more powerful, system-wide controls that let humans focus on the high-risk items that really need their attention. In other words, humans let the AI row the boat but remain very much in charge of steering the ship. This means customers can get the very best from both human and machine intelligence. 

How will Einstein Copilot shape the future of CRM? 

Copilot is the first glimpse into a future where people primarily interact with software using conversational interfaces rather than clicking buttons, and will fundamentally change the way people use technology.

By integrating Einstein Copilot into Salesforce’s Einstein 1 Platform, businesses of all sizes can take full advantage of generative AI. 

Just by asking a question or giving an instruction, Einstein Copilot can free up time for more strategic work by automating repetitive tasks and providing users with easy access to information. Copilot also analyzes data to provide insights that would be difficult or time-consuming for humans to uncover. These insights can help businesses make better decisions about everything, ranging from sales and marketing strategies to product development and customer service.

New Einstein Copilot capabilities, such as the customization available through Einstein 1 Studio, allow businesses to build and customize their own AI assistants with skills and prompts that fit their needs. 

How can customers get Einstein Copilot?

Customers can access Einstein Copilot by purchasing Einstein 1 Editions or by adding it on to Enterprise or Unlimited Editions. Detailed pricing information is available here

Einstein Copilot is available globally now for Sales Cloud and Service Cloud and will be available in Marketing Cloud later in 2024. Additionally, Einstein Copilot for Tableau will be launching in the second half of this year. Tableau currently supports generative AI capabilities with Tableau Pulse and Tableau Copilot (now in Beta). Einstein Copilot initially supports data residency in the United States and the English language. 

Go deeper:

Today, Salesforce announced the Data Cloud Spring ‘24 Release, which includes new innovations to make data in Data Cloud more usable across Salesforce’s CRM applications and platform services. Features like Data Cloud Related Lists and Data Cloud Triggered Flows make it possible to view customer engagement data from a website on every customer record in Salesforce and automate an alert to a salesperson.

Data Cloud makes it possible to connect data from any source or data lake and use it within the applications that business users need to use every day. This is possible because Data Cloud is built on Salesforce’s foundational metadata layer, which provides a common language that integrates all Salesforce applications and low-code platform services including Einstein AI, Flow for automation, Lightning for UI, and Apex for deep, pro-code customization.

Why it matters: Despite significant efforts, a staggering 81% of business leaders report struggling with data fragmentation and data silos. This disconnected information hinders crucial tasks like improving the customer experience, even though 80% of customers expect better experiences based on the data companies collect.

Salesforce Data Cloud is the first data platform that not only unifies data from across the enterprise, but also uses this harmonized data to power the AI and applications that businesses use every day.

David Schmaier, President and Chief Product Officer, Salesforce

This powerful combination of data and CRM enables customers to build richer, more personalized customer experiences and connect all of this data in real time to Salesforce’s powerful Einstein AI services to ground generative AI and fuel predictive insights with trusted company data.

What’s new in Data Cloud Spring ‘24:

“Salesforce Data Cloud is the first data platform that not only unifies data from across the enterprise, but also uses this harmonized data to power the AI and applications that businesses use every day,” said David Schmaier, President and Chief Product Officer, Salesforce. “This enables salespeople, marketers, customer service agents, and more to develop deeper customer relationships, save time, and dramatically improve productivity. Data Cloud truly unlocks trapped data to power a better customer experience.” 

How it works: The power of Data Cloud in Salesforce

Before Data Cloud, Sales Cloud users acted on data that was manually entered, created via system generated activities, or via APIs with other systems. Now, with Data Cloud, customers can enrich their Sales Cloud experience with a comprehensive view of their customer across all systems and touchpoints with insights about customer behavior — whether that data sits in external sources or across Salesforce applications. All of this data can now be leveraged to power workflows and customer experiences. For example, (a) automatically creating an opportunity based on web engagement data, and (b) providing propensity scores about upsell opportunities based on product usage trends from data in an external data lake.

Sales Cloud without Data Cloud vs. Sales Cloud with Data Cloud

Customers everywhere embrace Data Cloud

With record-breaking adoption, Data Cloud is quickly becoming the go-to solution for unified data management. The high demand is evident, with 25% of million-dollar deals in Salesforce’s fourth quarter including Data Cloud, and the recent addition of over 1,000 new customers in one quarter. Salesforce was recognized as a Leader in the inaugural Gartner Magic Quadrant for Customer Data Platforms, validation of the power of hyperscale data combined with Salesforce’s data, metadata, and leading CRM applications.

Companies across all industries, geographies, and segments are driving growth and productivity by connecting their enterprise data to business applications with Data Cloud and the #1 AI CRM. 

Get hands on with Data Cloud

At TrailblazerDX, Salesforce will empower all Trailblazers to take advantage of Data Cloud and offer a comprehensive suite of resources to empower customers on their journey. This includes:

More information:


Gordon Lee has spent the last two decades transforming his life and career in the Salesforce ecosystem. 

But that almost didn’t happen. 

Unfulfilled in his role as a financial underwriter, in 2007, Lee saw an internal job post seeking a Salesforce Administrator. Despite his interest, self-doubt made Lee think the position was too technical for his skills.

But when the post was still there six months later, he made the leap.

A leap of faith 

Lee, a first-generation Chinese American who was born in San Francisco, graduated from the University of California, Davis, just after the early 2000s dot-com boom.

At the time, his peers were landing technology jobs at exciting, high-tech companies. Lee, however, didn’t even apply, since he had struggled with most of his programming classes in college, and felt his lack of coding and technical skills would disqualify him. 

Instead, he landed his first gig at a Bay Area financial services company. Lee’s innate curiosity and resourcefulness guided him in those early years, and he progressed in roles ranging from sales to underwriting. Despite landing on a solid career, Lee missed being creative and solving puzzles — the things he most enjoyed while building LEGO blocks as a child. So when he stumbled upon the Salesforce Admin job, he was intrigued.

So when he stumbled upon the Salesforce Admin job, he was intrigued.

Learning that the job was a combination of data operations and project management, Lee realized that with the right training and resources, he could make the leap into tech and change the trajectory of his career.

The launch of Trailhead… “a game changer”

He got the job, and dove right into his new role. Early on, though, Lee encountered challenges as he grappled with complex concepts and technical intricacies. 

“At first, I was pretty overwhelmed. It felt like learning a new language, especially after nearly failing my programming courses in college,” he said. 

With no mentor to guide him and finding it difficult to find online communities of Salesforce professionals, Lee had to find a way to skill up on his own.

While he was able to make it work, Lee always wondered if he could have saved himself time and trouble with the right training.

In 2014, Salesforce launched Trailhead, its free online learning platform. This was seven years after he had become an Admin – but Trailhead was exactly what Lee wished he had had when he began his Salesforce career.

“There was nothing like it that existed when I started out,” said Lee. When he joined Trailhead, he realized, “It was like having a personal tutor guiding me through a wide range of modules. A playground of free, hands-on learning and skills that you could just keep practicing until you figured it out.” 

Ten years later, Lee is now a Triple Star Ranger and Community Group Leader with 300+ badges. “Trailhead is a place I keep going back to learn – whether I need a refresher or a deeper dive into new concepts, like AI, or products.”

Trailhead is a place I keep going back to learn – whether I need a refresher or a deeper dive into new concepts, like AI, or products.

Gordon Lee, Salesforce Admin

Lee said what sets Trailhead apart from other online training platforms is the wide array of topics it offers — beyond just technical acumen, it champions the soft skills necessary for well-rounded professionals.

For example, as Lee grew in his career and made the transition from an individual contributor to a manager, he turned to Trailhead — honing in on soft skills like public speaking, interpersonal communication, and managing others. 

Salesforce and Trailhead have been invaluable to his career journey, he said. “I’ve been growing with Salesforce and it has been growing with me.”

A community-driven impact 

While Lee was forced to navigate his career largely on his own in those early days, he now has the Trailblazer Community — a global network of millions of Trailblazers who help each other learn new skills and thrive within the Salesforce ecosystem — to guide him.

“I can’t overstate the impact of the Trailblazer community on my career journey,” he said. “I remember going to meetings and immediately finding a huge sense of community and camaraderie. All of us here are having shared experiences, learning together, and looking out for one another.” 

Among Lee’s proudest moments was the recognition he received from the Salesforce ecosystem — the Salesforce MVP award for his work co-leading the San Francisco Nonprofit User Group. Salesforce MVPs are community-nominated individuals recognized for their expertise, leadership, and generosity within the Trailblazer Community. 

“It was validation of the hard work and dedication I’ve put into the community over the years,” he shared. “Salesforce User Groups are run by non-employees and made up of a community of volunteers. It’s really a group of people who care about the product and want to gather to help others learn it.” 

And in the age of AI, opportunities within the Salesforce ecosystem are only growing. The technology is reshaping how Salesforce professionals — across industries — approach tasks and data management. 

“AI opens up new possibilities, new frontiers to explore,” said Lee. “It will help remove the mundane, repetitive tasks and low cognitive activities within my team, allowing them to dedicate their energy to high-level strategic projects they find fulfilling.”

AI opens up new possibilities, new frontiers to explore. It will help remove the mundane, repetitive tasks and low cognitive activities within my team, allowing them to dedicate their energy to high-level strategic projects they find fulfilling.

Gordon Lee, salesforce admin

The people behind the tech

As Lee reflects on his journey with Trailhead over the last 10 years, one piece of advice resonates above the rest — prioritize people over technology. 

“To succeed, focus 90% on the people and 10% on the tech. At the end of the day, technology is just a tool, and tools are used by people – if you don’t know how to deal with people, then you won’t be able to use the tool effectively,” he said. 

“It’s the relationships we build that matter most.” 

Learn more:

The Ethisphere Institute, a global leader in defining and measuring corporate ethical standards of business practices, has again recognized Salesforce as one of the World’s Most Ethical Companies™.

Why this matters: Trust is Salesforce’s number one value. Since the company’s founding in 1999, Salesforce has placed trust and ethics squarely at the center of its model. This latest recognition illustrates Salesforce’s commitment to transparency, ethical conduct, good governance, and delivering on its commitments to all stakeholders. 

Go deeper: The Ethisphere Institute’s 2024 list honors 136 organizations across 20 countries and 44 industries. 

What they’re saying: “It’s always inspiring to recognize the World’s Most Ethical Companies®. Through the rigorous review process, we see the dedication of these organizations to continually improving their ethics, compliance, and governance practices to the benefit of all stakeholders. Companies that elevate best-in-class cultures of ethics and integrity set a standard for corporate citizenship for their peers and competitors to follow. Congratulations to Salesforce for achieving this honor and demonstrating that strong ethics is good business.” – Erica Salmon Byrne, Chief Strategy Officer and Executive Chair, Ethisphere

At Salesforce, we are all stakeholders of trust and our ethical culture. It is this shared purpose that unites us and drives us to do our best for our customers, community, and each other every day.

Sabastian Niles, President & Chief Legal Officer

The Salesforce perspective: “At Salesforce, we are all stakeholders of trust and our ethical culture. It is this shared purpose that unites us and drives us to do our best for our customers, community, and each other every day. As the AI revolution takes hold, infusing trust, responsibility, and impact in all we do is more important than ever to a company’s success and to the success of our customers and all of our stakeholders.” – Sabastian Niles, President & Chief Legal Officer


Find more Stakeholder Capitalism news and stories from Salesforce here

Today, Salesforce announced 15 grantees of its Catalyst Fund, which provides unrestricted capital to smaller and younger nonprofits focused on increasing access to quality education and advancing climate justice.

Why it matters: Disparities in education quality remain a significant challenge, limiting socioeconomic opportunities for many individuals. Climate change also impacts the most vulnerable communities. These grants are helping smaller, younger organizations grow their programs and reach new audiences, innovate for solutions and test big ideas, and secure additional funding.

Go deeper: Salesforce’s latest round of funding will allocate a total of $2 million to nonprofits to support 15 organizations across the United States, Australia, Canada, and the United Kingdom.

What they’re saying:

We’ve seen the transformative impact of our education Catalyst Fund partners and we’re thrilled to broaden our reach to support climate justice organizations.

Becky Ferguson, SVP of Philanthropy at Salesforce & CEO of the Salesforce Foundation

New Catalyst Fund grantees: These 15 grantees are committed to driving access to education and economic opportunity and advancing climate justice in the communities they serve:

More information:

Data Cloud, Salesforce’s hyperscale data engine, is deeply integrated into Einstein 1 Platform. In fact, it’s at the heart of Einstein 1, unifying all of a company’s structured and unstructured data to create a 360-degree view of its customers, and allowing employees on any team to quickly access and act on real-time customer information across their product and service interactions. Through Data Cloud, automation, predictive and generative AI, and analytics are powered across every Salesforce application and workflow.

Data Cloud’s success is generating industry recognition: Salesforce was recently named a Leader in the Gartner® Magic Quadrant™ for Customer Data Platforms (CDP). “We believe this recognition underscores the pivotal role of data and AI in delivering exceptional customer experiences and driving growth for Salesforce customers across every business application,” said Rahul Auradkar, Salesforce’s EVP and General Manager of Unified Data Services & Einstein.

In this interview, Auradkar explores the evolution of Data Cloud, and shares what’s on the horizon for this disruptive innovation.

Q. How does Data Cloud differ from traditional CDPs on the market today?

Data Cloud brings a company’s disconnected, structured, and unstructured enterprise data together to deliver an actionable, comprehensive, 360-degree view of a customer. With deep integration into Salesforce’s Einstein 1 Platform, the harmonized and unified data coupled with our rich metadata (data about data) and the insights gleaned from having a complete view of customers is natively available within all the Salesforce services and applications. This means Salesforce services like Flow automation, Apex code, Lightning web components, and Reports can now natively use this rich data and insights. Data Cloud is a binding layer for Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud, as well as our industry clouds and AppExchange apps. 

Essentially, Data Cloud addresses the core challenge businesses face — unlocking trapped data and making it actionable for CRM, AI, automation, and analytics across all touchpoints and channels.

Other CDPs were built for marketers, making it not easily accessible or usable by other business functions without custom solutions, custom APIs, queries, and multiple requests. Companies were required to develop and maintain custom solutions to bring trapped data to life, unlock the power of AI, and directly benefit customer experiences in the flow of work. 

Full Customer 360 view in Data Cloud

With an open and extensible architecture (BYOL, BYOM, zero-copy) that is native to Salesforce’s Einstein 1 Platform, Data Cloud leverages the power of Salesforce metadata. This flexibility enables companies to ingest or federate data across all sources — including Snowflake (generally available in March), AWS Redshift (currently in pilot), Google BigQuery (generally available in March), and Databricks (currently in pilot) — and harmonize and unify the data to power automation, activation, and analytics, and take action across sales, service, marketing, commerce, and other customer engagement scenarios.

Unlike traditional data platforms, Data Cloud seamlessly integrates with external data lakes like Snowflake or Databricks. With zero-ETL, data from these platforms becomes immediately accessible and usable within Salesforce applications, empowering customer-facing teams like sales to leverage valuable insights directly within Sales Cloud. By bringing the power of structured and unstructured data together, Data Cloud offers quick and secure entry into predictive and generative AI, helping make outcomes accurate, relevant, and grounded with your company’s data. 

Q. Why did Salesforce develop Data Cloud?

As the #1 AI CRM provider, Salesforce’s mission has always been to help make our customers into customer companies, including bringing the power of data and AI to deliver amazing integrated experiences. 

Despite efforts to centralize data and build a 360-degree customer view in their CRM, most company data remains disconnected, and therefore unusable or only partially effective to improve the customer experience. In fact, 80% of customers expect customer experiences to improve given the amount of data companies collect.

Many customers have invested in migrating their data to the cloud and implementing data governance policies. Some have even invested in marketer-specific CDPs. Why? Marketers have concerns about trapped customer data that is not easily accessible or usable without custom APIs and constant requests to the data team. While CDPs exist, they don’t always meet the mark. 

Nearly 70% of companies say their customer interactions are now purely digital, yet only 26% of organizations report providing a completely connected experience across all channels. And, 81% of business leaders report that data silos are hindering their digital transformation efforts. 

The data our customers have about their customers should be a competitive advantage.

Rahul Auradkar, EVP and General Manager of Unified Data Services & Einstein

We knew that if we were going to build a true customer data platform, it could not be another silo just for marketers. We had to unleash this data across our entire suite of applications and make that data useful for insights, AI, and actionability. The data our customers have about their customers should be a competitive advantage for our customers.

Q. Salesforce went from not having a CDP to being named a Leader in the 2024 Gartner® Magic Quadrant™ for Customer Data Platforms in just over three years. What do you attribute that to?

Salesforce has been the leader in the CRM market for over two decades. Customer success is one of our core values, and we actively listen to customer feedback and insights to fuel our product development. It became abundantly clear that all the structured and unstructured data customers have is not used effectively for them to engage with their customers. The explosion of digital transformation and the secular shift toward privacy makes the value of first-party data increasingly valuable. 

Salesforce rose to the challenge to deliver Data Cloud as an organic innovation. It is our fastest-growing organic innovation with astonishing growth and tremendous customer adoption and success. Over the past quarter, Data Cloud processed 7 trillion inbound records, with 1.2 trillion activations that drove customer engagement, growing at an astonishing pace. We innovated across our platform capabilities, applications, and core clouds on the same metadata layer that made us successful. 

We are humbled and excited about Data Cloud’s success and the value we are delivering to our customers, while at the same time, moving the industry forward with our innovation at a rapid clip. 

Q. What value does Data Cloud provide for businesses?

Data Cloud brings disconnected and trapped structured and unstructured data together to deliver an actionable, comprehensive, 360-degree view of customers. It empowers teams across organizations with access to real-time data and insights about their customers and their interactions with its products and services, enabling them to deliver personalized customer experiences at every touchpoint. Key benefits include:

Q. Why is data so critical in the age of generative AI?

The AI revolution is a data revolution and is also a trust revolution. The quality of generative AI output is directly linked to the relevance and context of the data that fuels it. In fact, 58% of workers believe that trusted customer data is essential for successfully utilizing generative AI in their roles. However, 62% of IT leaders say their organization isn’t yet equipped to harmonize data systems to fully leverage AI. What’s more, 90% of enterprise data exists in unstructured formats such as PDFs, emails, social media posts, and audio files, making it largely inaccessible for business applications and AI models. 

The AI revolution is a data revolution and is also a trust revolution.

Rahul Auradkar, EVP and General Manager of Unified Data Services & Einstein

And while 80% of IT leaders acknowledge the transformative potential of generative AI in leveraging data more effectively, 59% still require a unified data strategy to unlock this power. This is where Data Cloud plays a pivotal role.

Q. What are some interesting Data Cloud use cases you’ve seen from customers?

Customers of every size, across every industry, are using Data Cloud to transform their business and redefine what a CDP can and should do. 

For example, Mascoma Bank uses Financial Services Cloud with Data Cloud to see a customer’s entire relationship with the bank and understand activity surrounding the customer and their accounts. By using Salesforce as its single source of truth for all customer, account, and transaction data, bankers are now better equipped to help their clients reach their financial wellness goals.

Heathrow Airport also uses Salesforce Data Cloud and Einstein — grounded in the real-time data of tens of millions of passenger records — to personalize interactions with customers, allowing the airport to provide the right services to the right passengers at the right time. Data and AI-powered experiences also allow the airport to anticipate passenger needs before their next airport visit.

And, FedEx is improving the customer experience through recent investment in Salesforce Data Cloud by integrating customer service, marketing, and sales, giving the customer a more informed, efficient, and personalized experience.

Learn more:

Any unreleased services or features referenced here are not currently available and may not be delivered on time or at all. Customers should make their purchase decisions based upon features that are currently available.

Wonolo, which stands for “work now locally,” is a website that connects job seekers to local businesses that are hiring. Today, they are using Einstein AI to assist their customer service agents.

The impact: Using Salesforce Service Cloud generative AI, Wonolo has bolstered the confidence of its agents and increased overall efficiency. 

Dive deeper: Wonolo uses Salesforce across its business, driving operational efficiency and increasing sales. For example, the company has used Service Cloud to boost agent response times and customer satisfaction scores through automation and AI. This includes auto-generated texts that give customers important job details, like role requirements and next steps, which have contributed to a three-point increase in customer satisfaction. 

Wonolo perspective: “Salesforce took the time to understand Wonolo’s needs and offer solutions that addressed our pain points. We have been able to bring all the information our agents need together in one place. Generative AI has helped our agents be more efficient and confident in their work, without losing the human connection we pride ourselves on as a company.” – Adam Ashworth, Senior Salesforce Administrator

Einstein enhances the human element of candidate matching, making Wonolo even better at what they do best.

Kishan Chetan, EVP and GM of Service Cloud 

Salesforce perspective: “Einstein enhances the human element of candidate matching, making Wonolo even better at what they do best. Helping people do their jobs more effectively and providing more consistent service is a great example of the opportunities that can be unleashed when generative AI is coupled with great customer service.” –  Kishan Chetan, EVP and GM of Service Cloud 

Explore more:

Today, Salesforce shared that Iron Mountain is using the Einstein 1 Platform to consolidate its systems into one 360-degree solution to make data more actionable by being baked seamlessly into the flow of work.   

Why it matters: Iron Mountain is a global information management services company that serves more than 225,000 organizations around the world, including 95% of the Fortune 1000. With a mission to protect and elevate the power of its customers’ work and with a customer base of this size and scale, providing an exceptional customer experience is a top priority.

At-a-glance: Despite having massive amounts of customer data, Iron Mountain’s service agents couldn’t easily access it or use it meaningfully to address customer requests. Agents had to switch between multiple apps and databases to gather enough data for customer inquiries. Plus, the order process was manual and information was located across numerous places, forcing agents to go back and forth between systems. 

The impact: Iron Mountain turned to Salesforce technology to improve agents’ experience. It helped the company:

Fast facts:

Iron Mountain perspective: “Salesforce Einstein has brought greater consistency to our customers’ experience and saved our agents’ time. Leveraging the power of the Einstein 1 Platform has helped us address many of our biggest pain points. The increased productivity and higher customer satisfaction is a combination that is driving increased revenue.” – Josh Langley, CIO 

Einstein’s ability to integrate and provide generative AI in multiple ways brings automation across the process, saving time and enhancing customer service.

Kishan Chetan, EVP and GM of Service Cloud

Salesforce perspective: “Our customized solutions for Iron Mountain moved them from a disjointed process to a streamlined experience that’s better for both the agents and customers. Einstein’s ability to integrate and provide generative AI in multiple ways brings automation across the process, saving time and enhancing customer service.” – Kishan Chetan, EVP and GM of Service Cloud 

Explore more:

John Lewis Partnership (JLP), the U.K.’s largest employee-owned business and parent company of major retail brands John Lewis and Waitrose, is optimizing its returns program with AI-driven insights from Tableau Pulse. With these insights, JLP is driving better decision-making and efficiency for both employees and customers.

Why it’s relevant: Eighty-three percent of global retailers have seen operational efficiency improvements with AI. And the majority of senior IT leaders believe generative AI has the potential to help them better serve their customers, take advantage of data, and operate more efficiently.

At-a-glance: Employees in JLP’s returns program needed trusted, accessible, and real-time insights on the company’s retail supply chain to help them understand where they need to focus their efforts. To get there, JLP needed to migrate a high volume of disparate legacy data onto a single platform where the company could visualize and act on this data, quickly. 

A deeper look: With AI-driven insights from Tableau Pulse, employees have been able to improve internal processes and drive better decision-making around key metrics like inventory management and product availability. Ultimately, this ensures that there are products available for customers to purchase when they want them. Tableau Pulse has helped JLP:

Customer perspective: “Tableau Pulse has been a game-changer for our returns program. Its intuitive and predictive generative AI-driven insights have empowered our buyers, enabling them to make informed decisions quickly. This has not only enhanced our operational efficiency but also translated into significant financial benefits. We’re excited about the future possibilities with Tableau Pulse.” – Barry Hostead, Director of Data Management, John Lewis Partnership

We will continue to deepen our collaboration as they scale Tableau Pulse and look forward to helping their employees make better and faster decisions and drive better experiences for their customers.

Ryan Aytay, CEO, Tableau 

Salesforce perspective: “We’re excited to work with JLP as they use trusted AI and data across their businesses and transform their returns program. We will continue to deepen our collaboration as they scale Tableau Pulse and look forward to helping their employees make better and faster decisions and drive better experiences for their customers.” – Ryan Aytay, CEO, Tableau 

More information: Learn more about Tableau Pulse