AI Now Runs Half of Salesforce Operations—But 40% of Agentic Projects Will Flop
Salesforce just crossed the Rubicon—50% of its operations now hum on AI autopilot. The catch? Nearly half its agentic projects are headed for the scrap heap.
### The AI Takeover (With a Side of Chaos)
No more guessing games—bots handle everything from CRM pipelines to customer tantrums. But the hype hits a wall: 40% of these 'intelligent' systems will faceplant by 2026. Blame it on rushed deployments or execs chasing shiny objects—either way, the failure tax is real.
### Wall Street’s Blind Faith
Investors keep throwing money at AI like it’s a meme stock. Newsflash—automation doesn’t magically fix broken workflows. Someone should tell the C-suite before they vaporize another quarter’s earnings on ‘revolutionary’ tech that barely functions.
Bottom line? AI’s eating Salesforce’s lunch—but it’s still spitting out half the seeds.
Marc says AI is 93% accurate but not flawless
Marc calls this a “digital labor revolution.” He claims Salesforce’s in-house models are now running with 93% accuracy, but he’s not pretending they’re perfect. “It’s pretty good,” he said, but “it’s not realistic” to expect 100%. He also said rival firms are nowhere NEAR that level because they don’t have the kind of data and metadata Salesforce does. That’s his not-so-subtle flex that volume wins in the AI race.
Still, there’s a catch. Not all AI is built equal. And not all projects are going well. Research firm Gartner is already predicting that over 40% of “agentic AI” projects will be canceled by the end of 2027. The reasons? Projects are expensive, the results are foggy, and risk controls are weak. Some of these tools are just HYPE wrapped in buzzwords.
Anushree Verma, who’s a Senior Director Analyst at Gartner, didn’t hold back. She said, “Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied.” She warned that this obsession with experimenting is stalling deployments and blocking production.
The problem, she says, is people jumping into AI without knowing what the heck they’re doing.
Agentic AI gets hype but low investment and even lower results
During a Gartner webinar in January 2025, 3,412 people were asked how much they’ve put into agentic AI. Only 19% had made serious investments. 42% had gone in cautiously. 8% haven’t touched it at all. The other 31% are either unsure or sitting back to watch. Not exactly confidence-inspiring.
Part of the problem is what Gartner calls “agent washing.” Vendors are rebranding their old junk—chatbots, RPAs, AI assistants—and slapping the agentic AI label on it. Out of the thousands of vendors, Gartner says only 130 are the real deal. The rest are noise. Verma said:
“Most agentic AI propositions lack significant value or return on investment (ROI), as current models don’t have the maturity and agency to autonomously achieve complex business goals or follow nuanced instructions over time.”
Translation: it’s mostly fluff.
Gartner says even the stuff that’s technically agentic doesn’t always belong there. A bunch of the current use cases being paraded around don’t even require agents. It’s marketing, not engineering. And most companies are just pouring money into undercooked tech.
Despite that, Gartner predicts that by 2028, 15% of daily work decisions will be made autonomously through agentic AI. It was literally 0% in 2024. Gartner also thinks 33% of enterprise software will come packed with agentic AI features by that same year, a huge surge from less than 1% today.
But to get there, tech teams have work to do. Integrating agents into old platforms is messy. It breaks workflows and costs a TON to patch up. Gartner says the better route is to scrap old systems and build new ones with agentic AI baked in from the start. Anything else is duct tape.
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