Salesforce is taking on archrival Microsoft in the competitive new space of copilots, which are AI assistants designed to help developers improve the customer experience (CX) across business interactions such as sales and support.

In an effort to improve its brand-awareness in a highly competitive space, Salesforce is going after leading agent/copilot competitors, including Google Gemini, OpenAI GPT, and IBM watsonx via Salesforce Agentforce’s autonomous decision-making abilities in response to enterprises’ demand for data/AI abstraction.

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Salesforce Dreamforce takeaways

Following last month’s Salesforce Dreamforce mega conference held in San Francisco, the most provocative takeaway is the newly available autonomous agents for providing more accessible and advanced GenAI capabilities to the app development process.

Salesforce executives, starting with CEO Mark Benioff, made it abundantly clear they were going after Microsoft Copilot with the newly branded and advanced AI assistant, previously called Einstein AI.

This is an ambitious plan considering that Microsoft’s vast popularity is due to Copilot’s deep integration with Microsoft products, including Teams, Outlook, PowerPoint, and Word. Microsoft also has an edge with the broader developer community, via GitHub Copilot. Enterprise DevOps teams predominantly use Microsoft Copilot based on their prevalent use of the Azure portfolio of developer tools and platforms to support app modernisation initiatives.

“Salesforce has an uphill battle as it seeks to gain mindshare against those heavyweights. Its best approach is to emphasise the autonomous qualities of its product, such as supporting more automation through AI and analytics to go above and beyond traditional stock chatbot answers in order to improve and personalise the customer experience,” said Charlotte Dunlap, Research Director at GlobalData.

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“This is critical considering how many enterprises continue to fork over hefty premiums for professional services associated with ongoing unfamiliarity of immature GenAI technology. DevOps teams ill-equipped to formulate cohesive strategies complain of an inability to locate knowledgeable third-party expertise with an understanding of how GenAI fits into their current IT systems, particularly as they grapple with security and governance concerns,” she added. “The more automation/autonomy Salesforce builds into Agentforce as part of its traditional business apps and platforms offerings, the better its AI tools can be used intuitively, spurring greater adoption. Once again, this is where Salesforce reaps the benefits of leading integration capabilities provided by MuleSoft, not to mention its merits as the industry’s pioneer in low-code/intuitive app platforms.” 

This is also why Salesforce talks up the idea of higher levels of abstraction around its data, such as Data Cloud, coupled with low-level UI.

Now, Salesforce is talking about abstracting AI and models, such as its Atlas Reasoning Engine, or the learning analytics engine which can go beyond traditional AI assistants to take broader actions involving customer requirements – actions that previously required human interaction. The agent support takes place across sales, service, and marketing functions.

Simplifying the developer experience

How well Salesforce executes on its latest GenAI strategy will become more evident in coming months. But the company is keenly aware of what is riding on its ability to leverage past successes of effectively simplifying the developer experience.

Enterprises are demanding improved support from technology providers not only with AI innovations, but through thought leadership, which can help them make their case for going after budget and executive support. Enterprises tell GlobalData that they continue to struggle to gain such support.