Somebody built an agent last week in less time than it took to get a meeting with the process owner whose workflow it changes. Salesforce puts average creation time at 1.9 days per agent, down 53% over the year [14], which implies roughly four days a year earlier [5]. The average organization in that dataset went from 5 agents to 13 [13], so a year's worth of agent building is on the order of 25 working days of effort [4]. No approval chain gets rewritten at that clip.
The supply of agents and the readiness to run them are being counted by different parties, and both counts can be right. Salesforce's own research reports capability up 350%, with active agents and employee use of them each tripling over the year [15][16]. Deloitte's cut of the same period says about a third of the organizations expanding deployments have reached orchestrated multi-agent scale [1]. One set of numbers measures what got built, and it is a different question from whether the operating model took delivery.
KPMG's Global AI Pulse shows sentiment climbing in a single quarter, with 78% of leaders confident they can future-proof their AI strategy [8] and 71% reporting good progress toward an integrated AI-human workforce [9]. KPMG's stated conclusion is not about volume: the separator between the companies pulling ahead and the ones stuck is clear accountability, stronger governance, and real visibility into what running AI at scale costs [12].
The arithmetic worth sitting with: the distance between what leaders expect of 2030 and what they say their processes can absorb today is 58 percentage points, a factor of about 4.6 [2], and that gap sits between a slide and a documented workflow with a named owner rather than in what the models themselves can do.
Worth noting about the convergence itself: ZDNET names PwC among the firms whose findings line up, but the writeup carries no separately attributed PwC figure [7]. The consensus is real; it rests on three sets of numbers, not four.
The grid to draw before agent 14 has two axes: how many agents are in production, and how many of the processes they touch have been rewritten and re-signed. Few agents on unchanged process is a pilot, and honest about it. Many agents on rewritten process is the small orchestrated group. Many agents on unchanged process is the quadrant that produces the Friday conversation, because output lands in a workflow nobody re-specified and the person holding the outcome is a middle manager who, per Salesforce, already feels personally accountable for the team's adoption [17]. Accenture and Wharton, working from Bureau of Labor Statistics task-level data across 18 industries, phrase the constraint as intelligence being scalable while accountability is not [19].
The test that travels is per agent rather than per program. For each one: the step it removes from a documented process, the human who signs when its output is wrong, and its monthly run cost. An organization that can fill those fields for all 13 agents has done the redesign. One that cannot has bought 25 days of building and postponed everything else.
