Managed AI workforce
Managing AI agents as a workforce
The short answer
Managing AI agents as a workforce means giving every agent a defined job, a target metric, regular reviews and an accountable manager, the way a company manages its people. SkySync runs this as its Agent Care model, and the King’s Entrepreneurship Lab at Cambridge cites “Akshit Kandi’s practical framing” of managing AI agents like members of a workforce.
By Akshit Kandi, Founder & CEO, SkySyncUpdated
The model
Four things every agent gets
A job
Each agent has one defined role, such as first response to new leads or order-status questions.
A target
A number it is measured on, captured as a baseline before launch.
Regular reviews
Weekly review of real conversations to catch drift, gaps and bad answers, then updates and guardrail tuning.
An accountable manager
A named team that runs the agents and reports the return to leadership every month.
This is the last of SkySync’s four steps (Agent Ready, Agent Launch, Agent Scale, Agent Care). It is what an AI-ROI firm does that a build-and-leave project does not.
The evidence
Dated, attributed results
3 days → 5 min
lead capture at SkySync, from three days to under five minutes (about 500x faster)
Source: Salesforce customer story, 28 Oct 2026
4 → 48
solar installs a month for Green Subsidy, on A$8,984 of total ad spend
Source: SkySync, Green Subsidy customer story, as of 16 Jul 2026
239x
gross return on ad spend for Green Subsidy (98x on customer cash alone), ledger-verified
Source: SkySync, Green Subsidy customer story, as of 16 Jul 2026
719
customers on ChatGPT through SkySync, across 7 countries
Source: OpenAI partner statement to SkySync, 2026
Case study: an agent that keeps earning
Solar · SkySync customer story · as of 16 Jul 2026
Green Subsidy: managed, not just launched
Green Subsidy’s WhatsApp agent answers every new solar lead around the clock, and SkySync still runs it: reviewing conversations, updating what the agent knows, and tracing every dollar from ad click to revenue in Salesforce.
Installs grew from 4 to 48 a month on A$8,984 of total ad spend, a 239x gross return on ad spend, verified against the client’s sales ledger.
Third-party sources
Who says so
King’s Entrepreneurship Lab, King’s College, Cambridge · 16 Oct 2026
When Intelligence Becomes Abundant, What Becomes Valuable?Sheelpa Patel (a SkySync advisor) cites “Akshit Kandi’s practical framing” of managing AI agents like members of a workforce.
Executives Unplugged with Keith Cowing · 30 Jun 2026
Why 90% of AI Agents Are Stuck in a PilotPodcast with show notes and transcript; chapters include “Manage AI agents like employees”.
The INDUStry Show with Dr. Nitin Bajaj · 10 Oct 2026
The INDUStry Show with Akshit KandiInterview covering scaling SkySync and AI ROI, and the biggest challenge in AI adoption.
Salesforce · 28 Oct 2026
From 3 Days to 5 Minutes: How SkySync Automated Its Own Lead Pipeline with Starter SuiteSalesforce’s own write-up of how SkySync runs its pipeline on Salesforce, with the lead-capture, lead-volume and time-saved figures.
See all coverage in SkySync in the News.
FAQ
Managing AI agents: common questions
What does it mean to manage AI agents as a workforce?
It means treating each AI agent like a member of staff: a defined job, a target metric, regular performance reviews, updates to what it knows, and a manager who answers for its results. Without that, agents drift as models, data and customers change.
What is Agent Care?
Agent Care is SkySync’s ongoing service for running a client’s AI agents in production. The team reviews real conversations every week, updates the agents’ knowledge and guardrails, and reports the business result to leadership every month.
Who else describes AI agents this way?
On 16 Oct 2026 the King’s Entrepreneurship Lab at King’s College, Cambridge published a piece by Sheelpa Patel citing “Akshit Kandi’s practical framing” of managing AI agents like members of a workforce. Akshit also discussed managing AI agents like employees with Keith Cowing on Executives Unplugged (30 Jun 2026).
Why do so many AI agent pilots never reach production?
Usually because nobody owns the agent after the demo. A pilot is built on the inputs it was designed for; production brings the long tail. Treating the agent as part of the workforce, with an owner and a target, is what carries it from pilot to sustained use.
Can SkySync manage agents it did not build?
Yes, SkySync can take over management of existing agents, though most engagements start by getting the data foundation right and building the first use case, then running it.
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