Why AI and unorganised data can't be friends

While it might be tempting to jump head-first into AI, doing so before you’ve got your data ducks in a row is premature. Just like you shouldn’t paint a wall before cleaning the surface or run a marathon without training, implementing AI on top of unorganised data is not going to get you the results you want. You will pay for lack of preparation both through making implementation slower and longer, but you’ll also run the risk of not achieving the outcomes you are hoping for.

AI not a silver bullet

We can all agree that the challenges and opportunities that AI can bring are a significant topic of discussion for organisations all over at the moment. However, it’s important to remember that as with any kind of new technology, AI is really no different. It can only be as good as the plans and design allow it to be. Even more so with AI, understanding what you want the business outcomes to be and what success looks like is more critical than ever. AI is not a silver bullet, it’s an extremely effective tool, but the benefits can only be realised when organisations are appropriately prepared and ready.

Becoming AI-ready is a multifaceted challenge for businesses, with organised data a critical piece of the solution. When a processing AI tool can understand where certain data is and then apply policies and rules to reach specific outcomes, that’s when the real magic happens. Universities can understand when cheating is happening, enterprise sales teams can streamline their proposal development and delivery, and organisations can quickly implement process efficiencies.

Better insights result in more informed, efficient decision-making and can help to keep operational costs low and productivity high. But this takes time and more importantly, planning. Businesses need to recognise AI isn’t a simple ‘get-rich-quick scheme’ that’s going to save them from a sliding economy. But with the appropriate measures in place, it can deliver significant dividends.

Getting organised

While AI has the potential to add immense value to organisations, there are a few things organisations need to establish beforehand.

First off the bat is goal setting. Research from McKinsey found organisations that find success with AI have a clearly defined vision and strategy behind the technology that is closely linked to broader business goals. Implementing AI for the sake of it will, in most cases, end up as a waste of money and resources. Think about where in the organisation AI is going to provide the most value and build a strategy that addresses the specific challenges identified. This might involve looking at areas that require high levels of manual processing, data analysis or where the scale of information is too great for it to be handled by human processing. This can range from things as simple as using AI tools to record transcripts, actions and outcomes from meetings, to significant undertakings of applying appropriate metadata to terabytes of content.

Once goals are set, organisations will need to focus on getting their data in order. AI and machine learning models are dependent on well-managed, high-quality data to create accurate insights and effectively automate processes. However, getting to this stage requires vigilant housekeeping. This means that a solid information management strategy is imperative to the use of automated intelligence. Generative AI, in particular, can only provide accurate and appropriate responses when it has good information to collate them from. This requires organisations to keep on top of their information management, ensuring information of value is retained and content that is no longer required is subject to appropriate lifecycle outcomes.

Lastly, staff need to be trained and understand the risks of, but also how to use AI and its capabilities. And this doesn’t just include the IT function. Every member of staff interacting with AI tools needs to understand how to use them in a way that maintains and improves its efficacy. Ultimately, if staff don’t know how to use AI tools properly, it’s not going to provide any tangible benefits. This means that policies governing access to and the use of AI are vital within any organisation, particularly in relation to the use of generative AI.

Mitigating risk

We know that data is the currency of the 21st century. We only need to read the headlines daily to understand that every organisation holding any kind of sensitive or personally identifiable information has a target on its back. This makes data a business risk that needs protecting.

Getting AI right can help reduce this risk. If an organisation’s data is in order, AI tools can help shore up defences by classifying sensitive information, controlling access and monitoring for threats. A well-established data strategy alongside AI tools allows organisations to form a complete view of their data sets and is critical in preventing as well as reducing the impact of potential breaches. Having proactive data management and protection strategies in place will also help to protect an organisation’s reputation and potentially reduce fines or reparations owed in the event of an incident. In some cases, it can also help to reduce cyber insurance policies.

It can be tempting to want to rush to take advantage of the latest and greatest AI tools. However, it’s important for organisations to take the time to put together clear goals as to what they want to achieve with AI, educate staff on how to effectively use it, and ensure data is properly organised before they implement it. Without these considerations, organisations risk wasting time and money while also falling behind competitors.

Image credit: iStock.com/Khanchit Khirisutchalual