Implementing cutting-edge technology, such as Salesforce’s Agentforce, is an exciting move for any company. Agentforce promises to offload routine tasks to digital helpers and boost productivity.
But after rolling it out, how do you know if your employees are actually using it?
Ensuring adoption is crucial; even the most powerful AI tool delivers no value if it sits unused. In this blog, you’ll learn why tracking Agentforce usage matters, how to measure it, and strategies to encourage widespread adoption.
Tracking whether employees are using Agentforce isn’t about micromanaging or playing Big Brother – it’s about ensuring a valuable tool is delivering value. You can’t manage what you don’t measure. Without visibility into usage, companies risk investing in AI capabilities that employees either underutilize or struggle with silently. Here are several key reasons why measuring Agentforce adoption is so important:
Agentforce likely represents a significant investment (in licensing, implementation, and training). Tracking usage data helps justify that the investment is paying off. If only 5% of your staff are using the AI agent when 100% have access, you’re not getting the full ROI. Leadership can also quantify how broadly the tool is being adopted and whether it’s saving as much time as expected.
Usage metrics can highlight teams or departments with low adoption rates. If one department barely uses Agentforce while others use it daily, that’s a flag. Perhaps those employees lack confidence in the AI, or they are unsure of its capabilities. Tracking who uses Agentforce (and who doesn’t) lets you target follow-up efforts – maybe a refresher workshop or sharing best practices – to the groups that need it most.
On the flip side, data will reveal power users and high-adopting teams. These Agentforce champions can be invaluable resources. For example, if your customer support team in Region A has 90% of reps actively using the AI (and they’re resolving 15% more inquiries per hour as a result), while Region B’s team lags behind, you can have Region A’s experts share their tips or workflows. Recognizing teams that embrace the tool also boosts morale and encourages others to follow suit. In essence, usage tracking helps propagate internal success stories.
Usage patterns show whether Agentforce meets employees’ needs. If workers try it but abandon it, or certain tasks have low use, the AI’s performance or scope may need adjusting. To address this, Agentforce 3.0 added a Command Center with analytics that track adoption, feedback, and success rates. Monitoring usage creates feedback loops: Are response times too slow? Which queries fail? These insights help optimize the AI or add resources, making tracking part of an agile cycle that ensures Agentforce enhances workflows instead of frustrating employees.
At a higher level, executives and HR can use adoption data in workforce planning. If only a fraction of the workforce is leveraging a tool that’s supposed to be enterprise-wide, that might call for a change management initiative. Alternatively, if adoption is high and yielding measurable productivity gains, that success can justify further AI investments or expansion to new use cases. In board meetings or QBRs, having hard numbers – “Agentforce usage grew from 20% to 60% of frontline staff this quarter, correlating with a 10% faster case resolution” – makes the impact of your digital transformation tangible.
In short, tracking usage of Agentforce is about ensuring people + AI actually equals productivity. It provides the clarity and control to turn a fancy new capability into sustained business results.
So, how can you actually tell if and how employees are using Agentforce? There are a few approaches, ranging from tools Salesforce provides to broader analytics solutions:
With Agentforce 3.0, Salesforce introduced the Agentforce Command Center, a built-in monitoring and analytics suite for your AI agents. The Command Center provides live dashboards to track agent activity and performance metrics.
For example, it can display agent adoption rates (how frequently the AI is being used), case resolution times, deflection rates (issues resolved by AI vs. passed to humans), quality scores of AI responses, and even the number of unique human users engaging with the agents.
Supervisors can even see real-time wallboard displays that show both human and AI agent activity side by side. Leveraging these native dashboards is a great starting point. If your organization has rolled out Agentforce, ensure your admins or team leads know how to access these metrics. Look at the “Unique Users” metric to gauge how many employees have tried the AI, and monitor trends over time (are more people adopting it week over week?). The built-in tools will give you a pulse on adoption without any extra development effort.
Beyond the pre-packaged dashboards, more technical teams can tap into Salesforce’s event logging and analytics capabilities for custom insights. Every interaction with Agentforce (e.g. an agent solving a case or answering a query) can be considered an event.
With some analytics effort, you could generate reports like “Agentforce queries per user per week” or “percentage of support cases where Agentforce was used vs. not used.”
If you have a Salesforce CRM Analytics (Tableau CRM) setup or even export logs to an external BI tool, you can craft tailored adoption reports. This approach might require a Salesforce admin or analyst to set up, but it allows slicing the data in ways the default dashboard might not (for instance, adoption by geography, by job role, or correlations with performance metrics specific to your org).
An even more comprehensive approach is to use a people analytics or work analytics platform that integrates data from Salesforce and other tools. This is where solutions like Worklytics come in.
Worklytics is a platform designed to give organizations visibility into how work gets done – including usage of various applications and AI features across the workforce. By connecting to Salesforce (along with other systems like Slack, Microsoft 365, Zoom, etc.), Worklytics can automatically pull in Agentforce usage data and combine it with other work activity data to provide rich insights.
For example, Worklytics can show which teams or roles are actively using Salesforce’s AI features (such as Agentforce or Einstein GPT) and how often, then correlate that with productivity outcomes.
It provides dashboards that track AI adoption rates over time, identify departments that might need extra support or training, and even let you benchmark your organization’s AI usage against industry peers.
The benefit of a unified platform is that you can see the full context – perhaps you discover that a sales team using Agentforce heavily is closing more deals and spending less time in internal meetings, suggesting the AI is streamlining their workflow. Meanwhile, another team might be stuck in old habits, which can be inferred from their low Agentforce usage, combined with unchanged time spent on manual tasks. Such cross-tool insights are hard to get from Salesforce’s native dashboard alone.
While not a technical measurement, don’t overlook simply asking employees about their Agentforce usage and experience. Usage logs tell if someone is using the tool, but a quick survey or manager check-in can reveal why or why not.
For instance, if data shows that a particular department’s usage is low, a follow-up survey might uncover that they had issues with the initial setup or didn’t understand how the AI could assist their specific tasks.
Combining the quantitative data (e.g., only 3 out of 10 team members have tried Agentforce) with the qualitative context (e.g., “we need a use-case cheat sheet for our finance team to see how it helps them”) provides a comprehensive picture. Additionally, engaging employees in dialogue demonstrates that the goal of tracking isn’t to penalize anyone, but to help everyone derive more value from the tool.
In practice, you might use a mix of the above. Many organizations begin with the built-in Salesforce dashboards for a quick check on adoption levels, and then progress to more advanced analytics as needed. The key is to ensure that the data is actually reviewed and discussed. Make Agentforce usage a regular topic in relevant meetings – for example, the head of customer service might review the AI adoption metrics weekly just as they review call volumes or CSAT scores.
If you’re looking for a robust way to track Agentforce usage and overall AI adoption across your organization, Worklytics offers a compelling solution. Worklytics is a people analytics platform built to help companies understand how work gets done, by aggregating data from the tools your teams use – Salesforce, Slack, Microsoft 365, project management tools, and more – into meaningful insights.
For the challenge of tracking Agentforce usage, Worklytics provides a few key advantages:
Modern workflows span multiple apps. A sales executive might use Salesforce Agentforce, chat with colleagues in Slack, and draft documents in Office 365, all in one afternoon. Worklytics can ingest activity data from all these sources and connect the dots.
For example, if higher Agentforce usage in Sales Cloud correlates with fewer internal emails or meetings. Or maybe your engineering team uses GitHub Copilot while your sales team uses Agentforce – Worklytics can track both and give you a combined “AI adoption dashboard” covering different tools by team.
This broad perspective is crucial for people analytics and HR leaders who want to foster digital adoption in general, not just siloed by each application.
Worklytics breaks down usage by attributes like department, team, role, or location. Instead of a raw log of events, you get actionable views – e.g., Marketing Department: Agentforce usage 10 interactions/user/week (low), Sales Department: 50 interactions/user/week (high).
It can highlight these gaps automatically. The platform even flags “power users” and “lagging teams” so you can quickly identify where to intervene. With a few clicks, you might export a list of top adopters (to potentially serve as champions or to simply congratulate) and a list of teams that haven’t embraced the AI yet. This beats combing through spreadsheets or multiple dashboards for each tool.
Worklytics keeps historical data, allowing you to track trends over time. You can see if the marketing team’s Agentforce usage increased after the training session last month, or if it has plateaued.
You can set targets and watch progress (e.g., aiming for 70% of customer support tickets to involve Agentforce in some way by next quarter, and monitor the climb toward that).
Moreover, Worklytics can benchmark your organization’s AI usage against others (in aggregate, anonymized form). This external frame of reference can be powerful – it might reveal, for instance, that your adoption rate is lagging behind industry averages, adding urgency to your efforts, or conversely that you’re ahead of the pack, which is a competitive strength to highlight.
A critical aspect of any analytics or tracking tool is privacy. Understandably, HR and executives want adoption data, but not at the cost of employee trust.
Worklytics is built with privacy by design – it aggregates and anonymizes data rather than exposing individual-level surveillance. In practice, this means you see insights like without spotlighting that “Alice used the AI 27 times today.”
The goal is to obtain actionable metrics without compromising personal privacy. By ensuring the data is used at a team or trend level, Worklytics helps companies avoid a “big brother” vibe while still reaping the benefits of measurement. This aligns with ethical people analytics practices – being transparent, fair, and focused on improvement, not punishment.
Some organizations might set up alerts or KPIs around usage. With Worklytics, you can configure notifications if, for example, Agentforce usage drops below a certain threshold for a particular team (indicating a potential issue), or if a sudden spike in usage occurs (perhaps a new use case has gone viral internally). Real-time visibility means you can be proactive. Worklytics essentially acts as an AI usage checker and coach – it not only reports metrics, but helps you act on them with features to drill down into details or automate reports to stakeholders.
By using Worklytics to track Agentforce and other tool usage, companies get a unified, privacy-conscious view of how new technologies are being adopted. Instead of juggling separate reports from Salesforce, Slack, etc., everything is in one place with context. For a busy HR analytics or IT team, that’s a huge time-saver and ensures nothing slips through the cracks.
Finally, Worklytics can tie these usage metrics to business outcomes. Would you like to know if using Agentforce actually correlates with higher customer satisfaction or faster project completion? Such analyses become possible when you have integrated data. This helps answer the ultimate question: Is our AI tool truly making a difference? If not, you have the data to diagnose why. If yes, you have the data to celebrate and double-down on success.
