Reliable data paves the way for every AI journey

Guest post by John Tallon, Practice Director of AI & Data and Modern Apps and M365 Productivity, Storm Technology

Evolving from generating content to executing actions, from supporting innovation to driving competition, from being a passive enabler to an active differentiator – we are living and working in an age of AI transformation and its impact is felt by each person and every organisation. No matter the size of the company, the sector in which you work, where you are based or what department you look at, AI is changing how businesses operate.

With a 2024 Storm Technology survey revealing that well over half (59%) of IT leaders think their company needs to adopt AI to be competitive over the next three years, it is viewed as a catalyst for success. But while the building blocks of our AI future are already being stacked high, many businesses lack the right foundations. Those foundations consist of high-quality, well-managed data.

Worst enemy

With data being the key to unlocking AI potential and ensuring a return on investment, every journey must start there. Before a company even thinks about what AI solutions it would benefit from, it needs to look at the information at its disposal and the state that data is in. Having inaccurate, incomplete or unorganised data means AI tools will lack contextual data to reason over and ultimately fail to deliver real and meaningful value to your business.

To avoid this, you need to have not only good-quality information but well-prepared, well-managed data. Such insights need to be accessible, complete and devoid of errors. That means removing any gaps, duplicates or inconsistencies, while labelling and organising data properly. It also means securing information and, where relevant, updating datasets. As part of this process, companies should also identify which datasets are actually suitable and valuable for the application of AI.

Best practice

As well as data management, data governance is also critical, not only in terms of AI success but security. Without the right frameworks, AI platforms may be vulnerable to attack or manipulation. Again, as with subpar data, ineffective governance could create biases and ethical issues which stifle AI effectiveness and success. Moreover, this age of heightened innovation is also a time of heightened regulation.

For instance, regulations such as NIS2 have placed a whole new range of requirements on both private and public entities. And with such regulations continuing to evolve, compliance is more than just a box to check for growing organisations; it’s a business imperative.

Regardless of whether NIS2 applies to you or not, every company leveraging AI must put tools and processes in place to uphold compliance and avoid the reputational and financial risks associated with inadequate governance. Alongside legislative requirements, this approach also ensures that best practices are upheld within the organisation and teams are deploying AI not just productively and proactively but responsibly.

By deploying best practices when it comes to data, businesses can help to ensure AI efficacy and value, whilst securing information and upholding compliance. AI enables companies to work smarter today – from automating tasks and supporting productivity to predicting customer behaviours and managing projects – and achieve long-term business objectives. Without a doubt, AI has the power to take a company to new heights, but to realise the full benefit, they must put data first.

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