However, many are overlooking a fundamental question during this process: is the information feeding these AI initiatives actually ready?

For years, businesses have focused on collecting and storing data. Information now exists across emails, contracts, collaboration platforms, shared drives, cloud repositories, enterprise applications and archives. However, volume alone does not create value.

The reality is that much of this data remains unmanaged, inaccessible or underutilised. Often referred to as ‘dark data’, this growing pool of hidden enterprise information is becoming one of the biggest obstacles to meaningful AI adoption.

Research conducted by IBM suggests that more than 60% of organisations estimate at least half of their data is dark, while approximately one-third believe dark data accounts for 75% or more of their total information estate. These figures point to a significant disconnect between data accumulation and business value.

This matters because AI does not create intelligence from nothing, but rather amplifies what already exists. If information is fragmented, duplicated, outdated or poorly governed, then AI outcomes reflect those same weaknesses.

Organisations are information rich but intelligence poor

The root causes of dark data could include information silos across departments, ageing legacy platforms, a lack of governance, incomplete integration, compliance irony (when information is stored well beyond the mandatory period), or changing organisational priorities, where collection is prioritised over analysis.

Notably, says McKinsey, 70% of software used by Fortune 500 organisations is more than 20 years old, a statistic that illustrates the scale of modernisation challenges many enterprises still face. This also draws attention to the fact that, realistically, organisations cannot expect AI to compensate for decades of fragmented information practices.

These factors all contribute to a situation where organisations appear data rich on the surface but, in actual fact, they lack the ability to transform the information into actionable intelligence. The challenge becomes even more significant as AI initiatives expand.

What are the business consequences of dark data?

Poor information management is often treated as an IT issue, but its impact extends far beyond technology.

For example, from an operational perspective, organisations experience reduced productivity as employees spend more time searching for information or recreating existing work.

In terms of collaboration, poor version control and disconnected repositories make it harder for teams to work efficiently and confidently.

Security and compliance exposure also increase. Sensitive information may remain stored longer than necessary, retention requirements become difficult to enforce, and organisations risk falling short of regulatory expectations.

Customer outcomes are affected too. Delayed responses, repetitive requests and fragmented information ultimately reduce service quality and satisfaction. At the same time, businesses lose agility because they cannot confidently adopt automation or safely scale AI initiatives.

Information readiness foundational to AI success

One of the greatest misconceptions surrounding AI is that implementation begins with selecting a platform or deploying a use case. In reality, AI readiness actually begins with information readiness. This means organisations need to establish a structured approach to understanding and improving their information environments. But where do they start?

Ideally, the process should kick off with an audit of existing information assets to identify where content resides, who owns it and how it is being used.

From there, businesses need to classify their data, differentiating between unstructured, semi-structured and structured assets.

The third step is to address, or cleanse, what is commonly known as ROT data – information that is redundant, obsolete or trivial – to immediately reduce storage costs.

Next, companies should establish stronger governance practices across repositories and workflows implement strict policies for data retention and destruction.

Only once this foundation is in place should organisations accelerate AI deployment, introducing Al/ML tools to parse unstructured data and redact sensitive info.

Those that win with AI won’t necessarily move first

The businesses that ultimately derive the greatest value from AI are unlikely to be those deploying technology the fastest. Instead, success will belong to those creating visibility, governance and trust across their information environments.

For organisations looking to unlock the next phase of digital transformation, illuminating dark data is no longer optional. It is becoming the prerequisite for turning information into usable intelligence.

It cannot be denied though, says Shakeel Jhazbhay, General Manager: Digital Business Solutions at Hybrid IT systems integrator and managed services provider Datacentrix, that the digitisation journey of many businesses was catapulted swiftly forward during the pandemic, when pressure to think outside the box and reinvent themselves in order to be able to continue business was suddenly applied.

“The pandemic kicked off a requirement for rapid change, which brought with it a new culture in many organisations of digitisation, and in most cases, it was a move away from paper-based society to a more automated way of working,” he explains. “Companies quickly recognised the immense value in this and increased their activity in this space with more cloud-based engagement – and those that didn’t adapt have felt the negative impact.”

Pillars of the digitally transformed enterprise

According to Jhazbhay, the key foundations of the digital enterprise are: agility; adaptability; innovation; and, most importantly, people.

“Agility and adaptability were seriously tested when most of the world was placed under lockdown. We needed to empower our workforce to be able to work from anywhere, and the ‘work from home’ revolution pushed organisations to adapt to these changes rapidly, while, at the same time, ensuring that staff remained productive and still worked in a structured manner.

“Increasing global food and commodities prices have meant that some companies have continued to allow employees to practise this agile hybrid work culture, which lessens the impact without the business increasing allowances.

“Finally, while people are the foundation of any successful organisation, they are often left out of the core component of digital transformation, yet their positive adoption is a pillar of success.”

Where to from here?

Even beyond the pandemic, Jhazbhay continues, digital transformation is on the up and up, and as organisations regroup and reprioritise, there will be a greater focus placed on this at a strategic level, with its importance driven by business leadership.

“Truthfully, many companies find it difficult to think outside of the box. The digitally transformed enterprise, however, is able to see things in a more lateral way, and harness different types of technology to help drive the business forward.

“An effective digital transformation strategy will help organisations by guiding the way forward, and should provide an agile list of actions with quick wins and milestones set to continue with the momentum gained.

“Moving forward, companies should take stock, assessing the success and failures of their pandemic implementations, and the impact these have had on their people and the business itself. From here it is possible to move forward with digitisation in line with the strategic goals of the current organisation, something that should also be reconsidered, as these may have changed from when the business went into ‘protect’ mode,” Jhazbhay concludes.

About Datacentrix:

Datacentrix is a leading hybrid IT systems integrator and managed services provider that enables digitalisation success.

The expert teams leverage the power of ICT technologies to connect, transform, optimise and future-proof business, supporting clients throughout their digital journey.

Datacentrix offers deep technical expertise across a mature offering and provides proven execution capability that is endorsed by the world’s foremost technology partners.

With a strong African footprint, the company is recognised for its agility, in-depth industry knowledge, ethical practices and strong overall performance.

The company is a Level One (AAA) B-BBEE Contributor, with 135 percent procurement recognition.