Salesforce bets on AI Agents strategy with Google Cloud and Unisys to redefine the future of CRM
Salesforce is making some major moves on the enterprise technology chessboard, and the past few weeks have made that crystal clear.
Two partnerships announced almost simultaneously have put the company at the center of a conversation that goes far beyond corporate contracts: the alliance with Google Cloud and the expansion with Unisys point to a new chapter in how large enterprises will use AI Agents to automate processes, manage data, and transform the customer service experience.
And the most interesting part of all this isn’t just the size of the partnerships, but what they reveal about Salesforce’s bigger strategy.
The company is betting big on making its Agentforce and Data Cloud 360 stack a central automation layer within large enterprise operations, with artificial intelligence agents moving between different platforms without needing to copy data or create redundancies.
This significantly changes the narrative around traditional CRM, which for a long time was synonymous with customer databases and sales pipelines.
Now the game has changed entirely. 🚀
But are these moves enough to turn demos and announcements into real revenue growth? That’s exactly what we’re going to explore here.
Salesforce and Google Cloud: what this partnership actually means in practice
The alliance between Salesforce and Google Cloud isn’t exactly a surprise for anyone following the industry, but the depth of what was announced goes beyond what many people expected. The integration allows AI Agents from Agentforce to operate directly within the Google Cloud ecosystem, accessing data stored in BigQuery and interacting with other tools in Google’s portfolio without the need to move information between environments. This matters because it eliminates one of the biggest bottlenecks of AI applied to business: data fragmentation across different platforms and the latency that comes with it.
In practice, what does this mean for a company already using Google Cloud as infrastructure and Salesforce as its CRM? It means an AI agent can pull up a customer’s purchase history from Data Cloud 360, cross-reference it with behavioral data stored in BigQuery, and generate a personalized response in real time — all within an automated flow that doesn’t require human intervention at every step. This level of integration was hard to achieve before because it required custom data pipelines, dedicated technical teams, and a lot of implementation time. With this partnership, the promise is to drastically reduce that friction.
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Another point worth noting is the joint distribution model the two companies are adopting. Salesforce will be listed on the Google Cloud marketplace, which makes adoption much easier for companies that already have contracts and credits with Google. This isn’t just an operational detail — it’s a go-to-market strategy. Shortening the sales cycle and reducing procurement effort for enterprise clients is one of the biggest growth accelerators in this market, and both companies know that very well. The question that remains is whether the execution will match the ambition of the announcements, which historically is the biggest challenge in large-scale partnerships like this. 🤔
Agentforce 360 at Unisys: automation across more than 120 countries
While the partnership with Google Cloud grabs more headlines because of the visibility of both brands, the expansion with Unisys deserves equal attention — maybe even more in terms of operational impact. Unisys announced the deployment of Agentforce 360 across more than 120 countries, with the goal of automating millions of service tickets per year and supporting a global network of technicians with field service tools powered by artificial intelligence. We’re talking about a company with a strong presence in sectors like logistics, government, healthcare, and finance — exactly the segments where complex processes and high volumes of interactions make automation via AI Agents most valuable.
Unisys adopting Agentforce puts Salesforce’s technology inside operations that deal with critical infrastructure, and that raises both the level of demand and the level of impact at the same time.
The most discussed use case in this context is customer service at industrial scale. Large companies serving millions of people per month face a structural problem: hiring and training enough teams to handle the volume is expensive and slow, but delivering a poor experience is even more costly in the long run. Agentforce’s AI Agents step in as an intelligent middle layer, capable of resolving a significant portion of requests autonomously and escalating to a human agent only when the complexity requires it. Unisys already has the infrastructure and the contracts; Salesforce brings the intelligence and the CRM platform that ties it all together.
What makes this combination interesting from a technical standpoint is that Agentforce was built to be multichannel from the start, operating across voice, chat, email, and web interfaces without needing separate configurations for each channel. When that’s combined with Unisys’s ability to integrate these flows with legacy systems that many enterprise clients still depend on, the potential result is an automation layer that works both to modernize old operations and to supercharge newer systems. This flexibility is what separates an automation platform that truly adapts to the client from one that requires the client to adapt to it. 💡
New revenue structure: Agentforce Apps and Data 360
One detail that might seem bureaucratic at first glance but carries enormous relevance for anyone following Salesforce closely is the planned change in how the company will report its revenue. Salesforce plans to consolidate its numbers into just two major groups: Agentforce Apps and Data 360, Platform and Other.
This reorganization is strategic. With this new structure, investors and analysts will have a much clearer view of how the AI Agents and data businesses are growing relative to the legacy cloud portfolio. Until now, it was hard to separate what was revenue from real innovation and what was organic growth from traditional solutions. With two well-defined buckets, Salesforce is basically telling the market: look over here — this is where the future of the company is being built.
This transparency matters because partnerships like those with Google Cloud and Unisys gain a layer of verification. Instead of being confined to the world of press releases and conference demos, these initiatives will need to show results in the quarterly numbers — and that benefits anyone who wants to make decisions based on facts, not promises.
CRM is changing, and fast
For years, when someone mentioned CRM, the mental image was basically a glorified database: contacts, opportunities, funnel stages, sales reports. Salesforce pioneered turning that into software as a service, but even so, the essence of the product remained very centered on managing relationships in a static way, where humans enter data and other humans query that data to make decisions. What’s happening now is a shift far more profound than a simple feature update.
The introduction of AI Agents as a central component of CRM changes the very nature of the product. The system stops being a repository that people consult and becomes an engine that acts autonomously based on available data. An agent can identify that a customer is showing churn behavior, send a personalized message, escalate to an account manager if there’s no response, and log everything in the history — without any human needing to orchestrate each step. This isn’t simple task automation — it’s decision-flow automation, and the difference between the two is enormous in terms of value generated.
Salesforce isn’t the only one betting in this direction. Microsoft with Copilot integrated into Dynamics, HubSpot with its generative AI features, and SAP with the Joule platform are all racing to reposition their products within this new paradigm. What sets Salesforce’s approach apart is the bet on the concept of agency — meaning not just assisting or suggesting, but actually executing actions. This raises the perceived value, but it also raises the risk, because an agent that acts incorrectly creates real consequences, not just misguided suggestions. The trust that companies place in these agents will depend heavily on how Salesforce manages transparency, auditability, and control. ⚙️
The numbers behind the narrative
For those who like to look at projections carefully, Salesforce’s current narrative projects revenue of approximately $51.9 billion and earnings of $10.3 billion by 2028. Hitting those numbers requires annual revenue growth in the range of 9.6% and a profit jump of $3.6 billion from the current $6.7 billion.
On the more optimistic side, some analysts have already projected that the company could reach around $58.9 billion in revenue and $11.6 billion in earnings by 2029. These more aggressive estimates depend heavily on the AI lock-in thesis playing out in practice — meaning that companies adopting Agentforce and Data Cloud 360 become increasingly dependent on the ecosystem and grow their contracts over time.
The partnerships with Google Cloud and Unisys are moves that support this thesis. If the cross-cloud integration truly works as announced and if Unisys can demonstrate concrete results across its 120-plus countries of operation, that could serve as a catalyst for positive forecast revisions. But the opposite is also possible: if execution stumbles or if hyperscalers like Google, Microsoft, and AWS decide to develop competing capabilities more aggressively, Salesforce’s competitive advantage in this space could be challenged faster than expected.
The competition with hyperscalers: a real risk
This is a point that can’t be ignored. Salesforce is, in a way, building its AI Agents strategy on top of infrastructure that belongs to its potential competitors. Google Cloud is a partner now, but it also has its own AI products for enterprises. AWS has Amazon Bedrock and is investing heavily in autonomous agents. Microsoft has Copilot and the Azure AI ecosystem, plus it owns LinkedIn and has native integration with Dynamics 365.
This dynamic of simultaneous cooperation and competition — the famous coopetition — is common in the tech market, but it creates a strategic tension that investors need to watch. Salesforce needs to remain relevant enough that the hyperscalers prefer having it as a partner rather than a direct competitor. And for that, Agentforce adoption needs to grow fast enough to create an installed base that’s hard to replace.
The fact that Salesforce owns one of the largest CRM databases in the world is a massive advantage in this context. Customer relationship data is the fuel that powers efficient AI Agents, and very few companies on the planet have access to such a large and diverse volume of this information. This strategic position is what makes the Google Cloud partnership work for both sides: Google gains access to a data ecosystem of extremely high value, and Salesforce gains infrastructure and global distribution.
What still needs to be proven
With all the energy surrounding the announcements, it’s worth keeping a critical eye on what still needs to be demonstrated. Large-scale partnerships between companies the size of Salesforce and Google Cloud have a mixed track record in enterprise technology. The distance between what’s presented in a keynote and what actually lands in a real customer’s production environment can be significant, especially when it involves complex integrations, sensitive data, and operations that can’t tolerate failures. The market will be watching the first production use cases closely before making decisions based on these announcements.
Another relevant aspect is the question of return on investment for companies that adopt these solutions. AI Agents running on top of Google Cloud with data managed by Data Cloud 360 and orchestration by Agentforce is a powerful architecture, but it’s also an expensive one. For mid-size and large companies that already have contracts with multiple vendors, adding more licensing layers requires clear financial justification. Salesforce needs to show, with concrete numbers, that the reduction in operational costs and the revenue increase generated by the agents outweigh the cost of adoption — and that usually takes longer than hype cycles allow.
There’s also the question of adoption speed. Even if the technology works perfectly in test environments, large companies have long approval cycles, strict compliance teams, and internal processes that naturally slow down any implementation. Salesforce will need to offer not just the technology, but also consulting, support, and deployment methodologies that make adoption viable within the operational reality of its clients.
Finally, there’s the human dimension of all this. Automation at scale raises legitimate questions about the role of customer service, operations, and sales teams within companies that adopt these technologies. It’s not about demonizing technology, but about recognizing that the transition to an environment where AI Agents handle a growing share of operational tasks requires careful change management planning, team reskilling, and process redesign. Companies that manage this transition in a structured way will come out ahead. Those that treat AI as a direct replacement for people without a clear plan will likely face internal resistance and underwhelming results. The human factor remains the most complex variable in any technology transformation. 🙌
The outlook taking shape for CRM in the coming years
Salesforce’s recent moves with Google Cloud and Unisys aren’t isolated events. They’re part of a broader trend where CRM stops being a software category and becomes an operational intelligence platform. The ability to orchestrate AI agents across different clouds, automate millions of interactions, and deliver predictive insights in real time is the kind of capability that can justify larger contracts, higher retention, and expansion within existing accounts.
For investors and tech professionals following this market, now is the time to pay attention. The announcements are promising, the strategic vision is coherent, and the partnerships make sense on paper. But as always happens in technology, the difference between a good strategy and real results comes down to execution. The next few quarters will be decisive in understanding whether Salesforce is truly building the future of CRM or just repackaging familiar promises with a layer of artificial intelligence on top.
The enterprise technology market is at one of those moments where the pieces are being rearranged, and whoever nails the positioning now could define the dynamics of the industry for many years to come. Salesforce clearly wants to be in that leadership position. Now it just has to prove it can deliver. 📊
