Artificial intelligence is generating financial returns for many companies, but a new study suggests businesses are struggling to move successful AI experiments into large-scale operations.

A BearingPoint study found that nearly 75% of companies reported positive financial returns from AI initiatives.

Yet only 13% were successfully on track with their broader AI strategies.

The AI scaling problem

Many companies have successfully tested AI tools in individual departments or projects.

The challenge is integrating those systems across entire organizations.

Older IT infrastructure is one of the obstacles.

Companies may also face regulatory requirements that make large-scale deployment more complicated.

Why this matters

The AI industry has attracted enormous investment because businesses expect artificial intelligence to improve productivity and reduce costs.

But successful experiments do not automatically translate into company-wide transformation.

Businesses need suitable data, infrastructure, security systems, employees and governance frameworks.

AI enters its next phase

The study suggests the next stage of the AI boom could be less about experimentation and more about implementation.

Companies that cannot integrate AI into their existing systems may struggle to capture the full benefits of their investments.

What happens next?

Businesses are expected to continue investing in AI while trying to solve the infrastructure and regulatory problems slowing adoption.

The gap between companies experimenting with AI and companies successfully deploying it at scale could become increasingly important for investors and workers.