​From Productivity To Capability: Rethinking AI Value

Luboslava Uram is COO and CTO at Solvd Group, a subsidiary of Allianz Group. Transforming the claim management experience.

​Sooner or later, almost every discussion about AI turns to productivity. How many hours did we save? How much faster are people? How much cost can we remove?

These are fair questions, and as COO and CTO, I ask them myself. We need to understand whether technology really creates value and whether the investment makes sense. But I increasingly think productivity is only the first layer of the AI discussion.​

There is enough evidence that AI can make people faster. A large field study involving more than 5,000 customer-support agents found that access to generative AI increased productivity by around 14% on average. So, the productivity case is real. What I question is whether this is where the biggest value will come from.

We have seen many technologies improve productivity before. Email made communication faster, ERP helped us standardize processes and information, workflow automation reduced manual activities. AI does all of this as well, but it can also change the amount and complexity of work an organization is able to handle.​

The World Economic Forum found that 86% of employers expect AI and information-processing technologies to transform their business by 2030. Microsoft’s 2026 Work Trend Index gives another interesting signal: 66% of surveyed AI users said AI allows them to spend more time on higher-value work, while 58% said they are producing work they could not have produced one year earlier.

For me, this is the important difference. Productivity asks whether we can do today’s work faster. Capability asks whether we can now do something that was not realistically possible, economical or scalable before.

From Faster Transactions To A Different Operation

I think this is the right direction.

I Would Change The AI Business Case

These are capability questions, but they are not soft questions. They can also be measured.