If you worked in marketing or sales around the early 2000s, you probably remember struggling with clunky and expensive CRMs that lived in server rooms guarded like treasure. Salesforce flipped that model with its web-based CRM that replaced endless installations, making it feel accessible, flexible, and user-friendly.
If you’re in marketing or sales today, your struggles (hopefully) look different. You’re dealing with data fragmentation, personalization-trust gaps, talent readiness, and the challenge of measuring ROI in the age of AI. As Salesforce addresses these challenges, it’s reinventing itself as an AI CRM, setting the standard for what an AI-powered enterprise platform can be.
We explored this evolution in our recent webinar, “AI-Powered Salesforce Solutions for Enterprises,” released just ahead of Dreamfornce 2025. Our host, Bob Leibholz (SVP, Business Development at BairesDev), was joined by three experts: Anu Varmani, who leads data platforms at Honda; Vikas Kumar, Chief Growth Officer at iOPEX; and Jeanniey Walden, Chief Marketing and Executive Advisor for Rakuten and founder of LiftOff. Their conversation pulled back the curtain on how data strategy, agentic automation, and ROI measurement are rewriting how enterprise systems operate.
In this article, we’ll explore how data fuels AI, how agents are transforming everyday work, and why ROI should be reimaged.
Salesforce Data Cloud as the Foundation of AI Success
If AI is the brain of Salesforce’s next evolution, data is its bloodstream. Every insight, recommendation, and autonomous action depends on how cleanly that data flows. As Anu Varmani said during the webinar, many failed AI projects “can be traced back to poor data quality: not enough, not clean enough, or not governed well enough.”
That’s why Salesforce’s latest focus is on fixing the data underneath. Salesforce reinforced this with new Data Cloud and Einstein 1 updates designed to unify fragmented data and bring trustworthy AI to scale. Integrations with Salesforce Data Cloud, MuleSoft, and Informatica bring order to decades of fragmented enterprise information, connecting records, analytics, and legacy systems into one trusted layer. “With Informatica in the mix,” Varmani noted, “Salesforce is moving toward data-centric AI—improving trust, governance, and integration across the board.”
Vikas Kumar called this stack “a seamless data platform for everything.” Most enterprises still juggle data from dozens of old systems, some built 30 or 40 years ago. Cleaning and merging that legacy data is a nightmare. Now, with Informatica’s master-data tools and MuleSoft’s integration fabric, Salesforce can finally unify it. However, Kumar reminded us that data quality is everything, echoing the old adage: ‘garbage in, garbage out.’”
That foundation enables what he described as intelligence as a service, which is AI moving beyond dashboards to reveal why things happen and where to act. As Jeanniey Walden added, “AI might not tell you exactly why your sales are down, but it will expose the exact point in the funnel where your customers stop listening.”
Clean, governed, connected data is what turns Salesforce from a reporting tool into a reasoning system. It’s the difference between tracking what happened and understanding what to do next. With strong data foundations, AI can move from analysis to action. That’s the leap Salesforce is taking with agentic systems.
Personalization and Human-Centricity in the Salesforce Agentic World
Salesforce’s early use cases for AI integration were email automation and predicting behavior. Now, its AI-powered systems are learning to act on their own. As Jeanniey Walden explained during the webinar, marketing is entering an age of “agentic conversations,” where intelligent agents interact directly with other agents, automating not just responses, but full exchanges.
That shift changes what personalization means. It’s now about systems that understand intent, make decisions, and communicate autonomously, while staying true to a brand’s voice. “Soon,” Walden said, “an agent will be talking to somebody else’s agent, and personalization will need to evolve into something far deeper to break through the clutter.”
Salesforce’s Agentforce framework anchors this new reality. It connects agents across platforms like Slack, Service Cloud, and Data Cloud, turning workflows into fluid, conversational systems capable of executing tasks, summarizing interactions, and learning from context.
Yet as Walden reminded, the more automated interactions become, the more valuable the human touch gets. AI can optimize speed, but trust and empathy still win loyalty. “We’ll see a resurgence in human-led channels,” she predicted—events, TV, or podcasts—“as ways to reconnect outside the agent-to-agent experience.”
Agentic AI can keep business and interactions human-centric, letting people focus on the work that moves the needle: creativity, connection, and strategic impact. That’s where the new ROI begins.
What Does ROI Look Like in the Salesforce AI Ecosystem?
For years, ROI focused on cost savings, faster cycles, or higher revenue, but as AI reshapes how organizations work, success looks different. The real return now comes from how deeply technology improves people, processes, and decision-making.
As Vikas Kumar explained, ROI today is both quantitative and qualitative. Of course, the numbers still matter when showing for time saved, reduced costs, or unified systems, but the human gains matter too. He sees technology, people, and process as the three areas where ROI shows up first, with Agentforce automation and the broader Salesforce AI stack capable of transforming all three at once.
Jeanniey Walden shared that success isn’t just what the data shows, but how the company feels. In one large AI enterprise implementation she led, the CEO asked how leaders would feel that it was working. So she sat with stakeholders and the Chief Legal Counsel said, “if this works, the increased level of trust for our business will improve contract negotiations, reduce counsel costs, and enable closing deals faster.” By thinking from this unique perspective, she realized there were tens of millions of dollars of hidden ROI, that the traditional numeric metrics would have never uncovered.
Achieving these ROI gains is only possible if adoption is front and center. Varmani considers that you can build the perfect system, but if people aren’t using it, you won’t see the return. For her, the next phase of ROI comes from alignment, how seamlessly AI tools fit into daily work, and how much friction they remove.
In the AI-powered enterprise, value isn’t only measured in speed. It’s reflected in how intelligently people and systems move together.
Emerging Trends in Enterprise AI
As Salesforce pushes deeper into AI, the next wave of innovation is already taking shape. The panelists agreed that the future of enterprise technology will be defined by accessibility, emotional intelligence, and the erosion of silos between business and tech.
Vikas Kumar sees Agentforce as only the beginning. He believes voice- and text-based interfaces—like Salesforce’s early demonstrations of “vibe coding,” will let non-technical users instruct systems in natural language instead of code. Combined with advances in personalization and automation, teams will soon create real-time, AI-driven experiences as easily as they once built dashboards.
Jeanniey Walden expects AI to take personalization further, shifting from logic-based recommendations to emotionally aware interactions. The next generation of agents, she noted, could interpret tone and intent, shaping communication not just by what customers say but how they say it.
Anu Varmani pointed to AI’s growing ability to capture tribal knowledge, referring to the unstructured insights hidden in chat logs, meeting notes, and collaboration tools, and turn them into shared intelligence.
The role of sales teams will evolve alongside these trends. As AI handles routine exchanges, human teams will focus more on creativity, strategy, and relationships. Business leaders will move closer to execution, guiding AI integration instead of managing from a distance.
Most importantly, the traditional walls between departments are beginning to fade. As Walden put it, in the AI enterprise, “there are no silos.” Marketing, sales, product, and data now operate through shared systems that learn, adapt, and act together.
Taken together, these trends mark the natural shift from simply adopting AI systems to internalizing how AI elevates the business promise for every customer.
The Path to Intelligent Transformation
The convergence of data governance, intelligent agents, and measurable ROI marks the start of a new phase for enterprises everywhere. Intelligent transformation means shifting from systems that store information to systems that act on it.
AI won’t work perfectly from day one. As Vikas Kumar reminded during the webinar, these models learn and improve through reinforcement, each interaction making the system a little smarter. Leaders who understand that AI is iterative, not static, will be better prepared to adapt, measure progress, and guide their teams through change.
As Dreamforce 2025 makes clear, Salesforce’s journey mirrors the broader enterprise evolution: turning data into decisions, and automation into intelligence.
Watch the full webinar to explore these insights in depth and connect with our team to discuss how we can support your business with enterprise-grade AI solutions. To see how these ideas translate into practice, learn more about our Salesforce development services.
