If you go through McKinsey’s latest State of AI research, you will see an uncomfortable gap. 80% of the respondents said AI improved their individual productivity. But only 37% said AI helped in making a positive impact on EBIT. I call this a highly uncomfortable gap because most companies aren’t digging deeper into this anomaly. They are instead acting on it: redesigning roles and freezing hiring in the hope that this sudden burst of productivity will help further move their business forward.
But faster work and fewer hires are only potential cost savings. Unless companies convert this time freed up by AI into measurable business outcomes, the impact may never show up on the P&L. In this blog, we will break down why this gap exists and what the companies that are actually converting AI-driven time savings into EBIT impact do differently.
Why doesn't Individual Productivity Automatically Translate into Company Profit?
1. Individual Productivity ≠ Organisational Productivity
The problem is simpler than you think: individual productivity is not the same as organisational productivity. For instance, let’s assume your employee builds an FSD in 20 minutes with AI today (instead of her usual two hours). These saved minutes won’t show up on the income statement, obviously. They will be absorbed elsewhere. Maybe by more meetings or by more review cycles.
2. Bottleneck Only Moves. Not Disappear
Imagine widening one stretch of a highway. But the bottleneck sits at the next exit. Your car might move faster for a while. But it will eventually queue up just the same. AI similarly widens the lane inside your employee’s workflows. But your company’s profit is largely driven by what happens between these workflows. It could be handoffs or even decisions that determine how quickly value reaches your customers. If those stay unchanged, faster tasks simply mean longer waiting times somewhere else.
3. Usage is Mistaken for Impact
That sudden burst in individual productivity might push you to spend more on AI. This is understandable given the visible gain. In fact, many companies we knew invested and gave access to tools to a vast majority of their employees. Some even ranked staff by who consumed the most AI tokens. They didn’t realise those tokens cost money. Usage became a proxy for progress, and activity was mistaken for impact.
4. Visible Costs, Invisible Savings
It’s a quiet mismatch. Your costs will rise immediately and visibly. They can show up as licences or token bills. But your savings will remain scattered across thousands of small tasks. And unfortunately, no one is measuring the value generated by these tasks. Your employee A’s ten minutes saved here and B’s half an hour saved there are absolutely real. But unless you convert that saved time into more business output or lower cost-to-serve, your P&L will keep displaying just the costs.
How Successful Businesses Turn AI Productivity Gains into Measurable EBIT Impact
1. They Always Focus on Outcomes. Never the Tool
Before deploying AI across their teams, smart businesses identify the business metrics they want to improve. It could be cost per customer served. Or it could be something simpler like the time to resolve a support ticket. Either way, they make sure that the metrics they choose reflect what they want to achieve as a whole organisation and not how quickly one of their employees completes a task.
Once that’s complete, work backwards. Find out where AI can make a measurable difference. Move the conversation from “How much time can AI save?” to “What can the business achieve with that time?”
2. They Redesign Their Workflows Around the Time Saved
They then avoid making a very obvious mistake - automating individual tasks without changing the surrounding workflows. Because they know that this rarely delivers the full benefit. If AI reduces the time required to produce a first draft of the FSD, the document still has to wait three days for internal approval from the account manager. The overall cycle time will barely change.
You should first examine your entire workflows. Focus particularly on handoffs and approvals. In other words, all your downstream dependencies. Remember - the objective should never be to make individual tasks faster. It should reduce the time and resources required to deliver the final outcome. That’s when the P&L needle will move.
3. They Carefully Decide Where the Freed-Up Capacity Will Go
This is the stage where these companies convert their team’s productivity gains to financial value. After all, they do not want to see these productivity gains disappear into everyday work. For instance, if one of their CS agents saves 500 hours for their CS team by answering basic product-related questions from customers, they will quickly decide how those hours of the CS team will be used. For instance, delivering more projects or customers to the same team. And obviously this will never happen if they ignore the employees who have more time to spare now.
4. They Measure the Financial Impact. Not Just the Time Saved
For these companies, every minute saved is first an operational signal. Not a direct financial impact. And that’s why they take the extra effort to measure the actual impact. They do this by comparing the original value of the metric with the new value after implementation. Going back to the same example. Saving 500 hours for the CS team does not automatically mean the company has reduced payroll costs. But if those hours allow the company to serve more customers without adding staff, that’s a measurable impact. In other words, they have charted out a clear path for the productivity gain to translate into financial value.
Agentforce: From Individual Productivity to Business Impact
Salesforce Agentforce offers a way to move beyond individual AI productivity by embedding AI agents into your business workflows. Instead of simply helping employees complete tasks faster, agents can handle defined tasks and execute actions across connected processes.
For example, in sales, Agentforce can support lead qualification and CRM updates. In customer service, it can help resolve routine enquiries and automate parts of case handling. When these activities are connected effectively, you can reduce manual effort and improve team capacity.
But deploying Agentforce alone won't guarantee better financial results. The real opportunity lies in identifying workflows where AI can remove bottlenecks and measuring whether the improvements reduce costs or contribute to revenue growth.
This requires more than implementing the technology. You need Salesforce expertise to identify the right use cases and establish meaningful performance measures. Agentforce can provide the technological foundation, but turning its capabilities into measurable financial gains requires the right implementation strategy.
How Brysa Helps Turn AI Productivity Into Business Value
AI can help your sales and service teams work faster. But inefficient CRM processes can prevent those gains from reaching your bottom line. Brysa helps you optimise Salesforce through workflow automations and AI integration aligned with your business objectives.
From automating repetitive tasks to streamlining approvals and improving lead management, we help identify opportunities to reduce manual effort and improve operational efficiency. By connecting Salesforce capabilities to measurable business outcomes, you can move beyond AI adoption and focus on tangible value.
Want to turn Salesforce productivity gains into business results? Contact Brysa to discuss how we can help.