A little while back we did a great deep dive with Marc Benioff, Salesforce’s CEO. While I had him I did a deep dive on a question all of us need to understand better: just where are these massive AI budgets for software really coming from?
Salesforce CEO Marc Benioff’s learning: if you have a standalone “AI budget,” you’re probably doing AI wrong.
The Reality of AI Transformation
Despite all the excitement about AI transforming companies and employees over the past 3-4 years, Benioff notes that so far, the vast majority of companies have mostly failed with their AI initiatives.
“You don’t have that many great stories of how AI has transformed these companies [yet],” Benioff said bluntly. Walk into most enterprise boardrooms and ask for concrete ROI from their AI investments. You’ll get a lot of hand-waving and “strategic value” conversations, but precious few hard numbers.
This is why AgentForce has generated so much buzz for Salesforce—it’s early but it’s practical, specific, and tactical. It gives companies a clear action plan rather than another science lab experiment that goes nowhere.
Why Everyone Needs a Win (Yes, Even Salesforce)
Even Salesforce, with all their Einstein technology and AI capabilities, needed AgentForce to create that “whoa” moment. As Benioff put it: “This is actually dramatically impacting my business process itself.”
If Salesforce—the company that’s been pushing AI in CRM for years—needed a breakthrough moment, what does that tell us about where everyone else stands?
Everyone needs a huge win. Not a proof of concept. Not a pilot program. A real, measurable business impact that transforms how work gets done.
The Budget Migration: From AI Silos to Line of Business
This brings us to the core insight that every B2B executive needs to understand: AI budgets shouldn’t exist as separate line items according to Benioff. And where they do — it’s a flag.
Benioff’s take is contrarian but logical: “Where there was an AI budget, that was a mistake. It should be the line of business.”
Think about it this way:
- Your service team should be held accountable for AI-driven efficiency gains
- Your sales team should be measured on AI-augmented productivity
- Your operations team should deliver on AI-enabled cost reductions
The budget should come from the teams that will benefit from the technology, not from some centralized innovation fund that has no accountability for business outcomes.
The RBS Case Study: From AI Team to Business Impact
Benioff shared an example about Royal Bank of Scotland (RBS). Despite having an “incredible AI team” with PhD researchers from University of Waterloo, CEO Dave McKay wasn’t getting the value he wanted from years of AI experimentation.
The breakthrough came when they shifted focus from the AI team’s projects to specific business unit challenges—specifically, transforming their wealth management division and converting their call center to not only service customers but also sell mortgages.
“This fundamental transformation in their consciousness” happened when they stopped thinking about AI as a technology project and started thinking about it as business capability enhancement.
The Line of Business Accountability Framework
Here’s the practical framework that emerges from this conversation:
Service Teams: Hold them accountable for efficiency gains, reduced resolution times, and improved customer satisfaction through AI augmentation.
Sales Teams: Measure them on productivity improvements, better qualification, and increased deal velocity enabled by AI tools.
Operations Teams: Track cost reductions, process automation, and capacity expansion delivered through AI implementation.
Each team gets budget based on their ability to deliver measurable business outcomes—not on their ability to deploy cool AI technology.
Why Standalone AI Budgets Are Red Flags
If you have a completely separate AI budget, Benioff argues, “you’re probably not integrated at that level.”
This makes sense when you think about it. Standalone AI budgets often indicate:
- Lack of clear business case accountability
- Technology-first rather than outcome-first thinking
- Disconnect between AI initiatives and business strategy
- No ownership from the teams who should benefit most
The Strategic Capability Shift
The most interesting part of the RBS story was the realization that AI could give them capabilities “that were not on their business plan.” This isn’t just about doing existing things better—it’s about unlocking entirely new strategic possibilities.
But this only happens when AI initiatives are deeply embedded in line of business thinking, not when they’re isolated in innovation labs.
What This Means for Your B2B Company
If you’re running a B2B company, here are the key takeaways:
For Your Internal Operations: Stop asking for AI budget. Start asking your department heads how they’ll use AI to hit their existing targets better, faster, and cheaper.
For Your Product Strategy: Don’t build AI features because AI is hot or to check a box. Build them because they solve specific customer business problems that translate to measurable ROI.
For Your Sales Process: When selling AI-enabled features, sell to the business unit that will benefit, not to the CTO or Chief Innovation Officer.
You’re Job is To Enable Superior Outcomes with AI. Period.
The companies that will win with AI aren’t the ones with the biggest AI budgets or the most PhD researchers. They’re the ones that embed AI so deeply into their business operations that it becomes invisible infrastructure for superior performance.
As wealth management and other industries get “utterly changed by AI,” the winners will be those who moved fastest from AI experimentation to AI accountability—with budgets, ownership, and success metrics that live where the business impact actually happens.
The great AI budget migration is underway. The question isn’t whether your company will participate, but whether you’ll lead it or get left behind.
