AI isn’t an immediate solution to every business problem. AI-driven platforms are only as useful as the data that feeds them. Poor data quality can create issues including algorithms learning from incorrect information and existing biases being exacerbated. Tackling data head-on is key to unleashing the power of AI.
Becoming AI-ready
26% of IT leaders say that AI and machine learning is a major tech initiative driving IT investments, according to CIO’s State of the CIO 2023 report, and they need to ensure this money isn’t wasted. Businesses need to glean value from their own data environment, rather than just snapshots of it. The problem is that too many firms have essentially locked their data down so that no member of staff can access it. This might work in averting data breaches, but it’s essentially preventing people from opening a treasure chest of valuable insights.
Implementing AI solutions on an disorganised siloes of data can even be harmful. Duplications and incomplete datasets can create biased or inaccurate insights and decisions. Back in 2018, Amazon was forced to scrap an AI-driven recruitment tool because it inadvertently favoured and suggested male candidates. The reason? The system had been trained on data submitted by mostly men over a 10-year period.
Giving every piece of data a name is also critical. If it isn’t labelled correctly, algorithms can’t identify relevant information to learn from and accurately automate the tasks that are too complex or time-consuming for humans to undertake. Data needs to be unleashed from its hiding place so that businesses know exactly what they have and where value can be derived.
The journey to data fitness
To use AI to its full potential, organisations need to prioritise their data fitness. It all starts with a data assessment that identifies where of data is hidden within the technology ecosystem. This audit process can also identify what type of storage every iteration of data sits on, how long it should be retained for and when it was last accessed and by whom
Accurate and clean data is essential for AI solutions to effectively complete tasks. Fragmented data that is hidden in the shadows can be relocated to a more appropriate location. Data that is most needed for AI can be moved to more accessible storage, with lower-priority data shifted to cheaper storage.
With any unneeded duplicate files removed from the equation, learning algorithms can access accurate insights to be used for automated solutions. An effective governance structure at the final stage, with set rules, can provide a reliable pipeline of useful data for those significant AI investments.
With data fitness assured, staff can benefit from self-service capabilities. Connected datasets, rather than in siloes, grant users the ability to find answers to their questions from an AI-driven tool. Internal and external data with metadata-based labels can provide the relevant context. Self-service capabilities are also critical to reducing the costs associated with a data scientist. Businesses can avoid the expense of these highly specialised professionals by becoming data fit as a priority.
Data fitness is also critical when looking at the future of AI. It’s going to be hugely transformative by allowing people to be smarter and giving them access to information for quicker and more informed decisions. AI isn’t anything new, but it’s definitely becoming more mainstream and accessible now. Just like we now have a PC on every desk in every office, AI will be truly pervasive in the coming years. But it’s about getting data management right, as within 2-5 years the organisations that don’t will be at a competitive disadvantage.
Unleashing AI with data
The enthusiasm for AI is evident, but realising its full potential hinges on solid data management. As AI becomes more prevalent in the business world, it’s essential for organisations to maintain clean, accessible and well-governed data. Ensuring high data quality can eliminate errors in AI applications and enable businesses to make quicker, smarter decisions. Companies that prioritise proper data management now will gain a competitive edge in the future, while those that overlook it will fall behind in an AI-centric landscape.
Andrew Carr is the Managing Director at Camwood.
