- Most CFO say they still can’t make money with AI
- The traditional price fails in an artificial intelligence economy promoted by use
- The monetization of AI is now firmly in the list of priorities of the boardroom
Artificial intelligence is transforming all industries, but a new report has affirmed that many companies are not capturing their financial value.
A global study of 614 financial directors conducted by Digitalroute found that almost three quarters (71%) said they were struggling to monetize AI effectively, despite the fact that almost 90% appointed a critical priority of the mission in the next five years.
Only 29% of the companies currently have a monetization model of the in operation, and the rest are experiencing or “flying blind”, according to the data, and more than two thirds (68%) of technological companies say that their traditional price strategies are no longer applicable in an IA economy.
Second digital gold fever?
“The AI is in the second digital gold fever,” said Ari Vanttinen, how in Digitalroute. “But without visibility at the level of use, companies are playing with prices, profitability and even product viability. Our data shows that CFO urgently need real -time measurement and income management to convert AI of a cost line into a genuine gain engine.”
The joint rooms are realized: almost two thirds (64%) of the respondents say that the monetization of AI is now a formal priority of the Board, but only one in five companies can track the consumption of individual AI, leaving finance equipment with limited tools for precise billing, prognosis or margin analysis.
70% of the CFO cites the complexity of prices as the biggest barrier to climb AI, and more than half reports the misalignment between finance and product equipment.
Inherited systems are also a challenge: 63% of companies are investing in a new income management infrastructure, recognizing that traditional cash contribution systems are not suitable for AI prices models based on use.
The study also highlights regional differences. Nordic countries lead the implementation but fight with profitability, while France and the United Kingdom show early commercial returns. The United States is still a world leader in the development of AI, but the data suggests a slightly more cautious approach to monetization at the organizational level.
Although US companies clearly understand the importance of AI, many are still developing the necessary internal frameworks to escalate effectively.
The United States obtains a score highly on the perceived meaning, but remains slightly behind the United Kingdom in terms of perceived criticality, indicating a broader and more experimental culture that has not yet transmitted completely to commercial execution.
The report recommends three steps for success: first, meter consumption at the characteristic level; second, prices based on the value and use of the model before launch; and third, align the equipment of products, finance and income around shared data.
As Vanttinen says, “each notice is now an income event. When companies can see, price and invoice for the use of real -time, unlock the margins that the market expects.”
