18 trillion dollars in prison: study reveals the four 'business debts' that smother AI in companies

A new study of Genpac consulting in partnership with HFS Research estimates that $18 trillion in economic value are 'closed' within companies around the world due to four large corporate debts: outdated technology, poor data quality, inefficient processes and unprepared workforce. According to the research published by Pharmaphorum, these bottlenecks prevent artificial intelligence from being implemented effectively, blocking productivity and innovation gains.

The 4 Corporate Debts that Block the Value of AI

The study classifies obstacles into four main categories. Technological debt refers to legacy systems and outdated infrastructure that do not support modern AI solutions. The data debt arises from the low quality, fragmentation and lack of governance of corporate information. The process debt represents manual and inefficient workflows that cannot be automated. Finally, the Talent debt reflects the scarcity of professionals with AI skills and data.

Like Business Debts Lock up the AI Potential?

Each debt acts as a lost link in the implementation chain. Without updated technology, AI models cannot run on a scale. Inconsistent data generates inaccurate results. Misdesigned processes make automation unfeasible. And the lack of qualified professionals prevents companies from extracting actionable insights. Together, these factors create an estimated 'contained value' of US$18 trillion – an amount equivalent to the GDP of countries like the United States and China combined.

Why Do Business Debts Affect Brazilian Companies?

Brazil, as an emerging economy with strong presence of sectors such as finance, retail and agribusiness, faces the same challenges. Companies that do not resolve these debts risk falling behind in the AI race. The good news is that the study points out paths: investing in IT modernization, creating data governance strategies, redesigning processes and empowering teams. Initiatives such as expanding data centers — such as the one announced by Microsoft in Texas — show that the infrastructure is being strengthened, but the larger bottleneck is within organizations.

How to Overcome Business Debts and Release AI Value?

Genpact suggests a three-step approach: diagnosing the degree of each debt, prioritizing the most impactful actions and creating a transformation script. The consultancy argues that the implementation of AI should not be seen as an isolated project, but as a systemic change. Solving these debts can unlock not only operational efficiency, but also new revenue sources – releasing the so-called $18 trillion value.

Frequently Asked Questions about Business Debts and AI

What is 'business debt' in the context of AI?

They are accumulated deficits in technology, data, processes and talent that prevent the effective adoption of artificial intelligence, resulting in unrealized economic value.

How do I measure the amount stuck in my company?

The study recommends an internal audit to assess maturity in each of the four areas, comparing with industry benchmarks and estimating potential impact based on productivity and revenue metrics.

Is that $18 trillion worth realistic?

The estimate combines data on AI penetration, sector productivity and inefficiency costs; although it is a projection, experts consider the plausible number as an indicator of global economic potential.