"AI cannot be a bolt-on, it must be built in".

Sparta Global CEO and Co Founder David Rai says AI cannot be a bolt-on, it must be built in. You can read the full Forbes article here.

Artificial intelligence continues to dominate boardroom agendas in 2026, with organisations across every sector accelerating investment in AI technologies and the skills needed to support them. From driving efficiency and innovation to improving governance and financial planning, the potential benefits are clear. Yet many businesses are discovering that turning AI ambition into real value is more difficult than expected.

One of the biggest barriers is data debt—the hidden accumulation of poor data quality, inconsistent standards and fragmented legacy systems. Much like building a house on unstable foundations, deploying AI on weak data infrastructure can lead to unreliable insights, operational risk and diminished return on investment.

Despite global spending on AI services projected to rise from $283 billion in 2025 to $325 billion in 2026, organisations that fail to address data quality may struggle to unlock the technology’s full potential. Without clear governance, traceable data and consistent standards, even the most advanced AI tools can produce misleading outputs and undermine stakeholder confidence.

For this reason, addressing data debt must become a C-suite priority, alongside AI adoption itself. Businesses that treat data as a strategic asset—investing in governance, modern architecture and skilled data professionals—will be far better positioned to deploy AI effectively and remain competitive.

This article explores why data debt is one of the most critical barriers to AI success and outlines practical steps organisations can take to build the strong data foundations needed for an AI-driven future.

You can read the full Forbes article here.