Behind great AI is great data (Guest blog from NetApp)

Author: Grant Caley, UK&I Solutions Director at NetApp

Artificial intelligence has dominated political, news and business agendas for the past year. Recently, the UK government announced an investment of upwards of £100m to help achieve its ambition of becoming an AI innovation hub. It’s no wonder that across the UK businesses are turning to AI, driven by a desire for more efficiencies as well as productivity and sustainability benefits.

In fact, recent research by NetApp, the intelligent data infrastructure company, found that 59% of organisations are planning to increase their AI investments in 2024, compared to 2023. With a backdrop of rising costs, and challenging economic headwinds, it is more crucial than ever for businesses to deliver high return on investments.

67% of UK IT decision-makers view AI as strategically important to their operational success. However, without a clear understanding of how to access the benefits of AI or what the most effective use of AI is, organisations will suffer from directionless implementation. To ensure that businesses can realise the full potential of AI, data strategies that prepare to address common challenges regularly threatening AI adoption are critical. With a considered data management strategy businesses will not only benefit from better AI, they can also see greener outcomes.

Managing data to improve AI

Information fuels AI algorithms. It is the foundation of AI models. Unmanaged and disorganised data limits the usable information that AI models can be trained on. This can result in less valuable output. Consistent, high-quality, clean data that can be accessed in real-time and at scale, with appropriate security controls is therefore critical for generating the best AI results.

This starts with understanding the data landscape. 61% of IT leaders reported their data estates would grow this year. It’s clear the scale of the data clean-up challenge is only set to grow. Businesses must know how much data they have, what the data is and where this data is located.

Visibility across the data stack is essential for  various cloud environments. With data often coming from multiple systems and sources, connecting it before it can be processed is tricky. But with effective data management software that works across silos, businesses can gain better awareness of their data, and begin to clean it. This removes any duplicate, irrelevant or unnecessary information. When firms truly understand their data landscape, they can then strategically plan how much preparatory work is required to identify the right data, collect it, and organise it.

Organisations shouldn’t underestimate the challenges that come with managing vast quantities of data. They must take time to prepare in advance. Firms can’t solely rely on collecting masses of data from every business application, customer touchpoint and every device they can to generate actionable insights.

They must control the way they gather, prepare, and store information if they want to fully utilise AI. Because if AI models are trained on unclean data, organisations will sacrifice their anticipated efficiency gains. And further, disorganised data will threaten a business’ green goals, contributing to excess carbon consumption. 

Cleaner data is greener data

The value of cleaner, organised data goes beyond better AI, it can also have significant sustainability benefits. Research from NetApp found that 41% of UK data is unused or unwanted, with data waste causing unnecessary emissions and contributing to the impact the IT industry is having on sustainability. Every digital action has real-world consequences, emails on average can create around 4g of carbon dioxide, and with attachments can rise to 50g of carbon dioxide. To reduce a business’ emissions, tackling data waste is crucial.

Data minimalism may sound counter-intuitive, especially at a time when the value of data is skyrocketing. But the value is not in the amount collected, only in the quality of the data that can be used. 83% of IT leaders say that their department prioritises sustainability initiatives and a quarter (25%) note that reducing their organisation’s carbon footprint is the biggest motivator in streamlining their data estates. By adopting data minimalism and achieving cleaner greener data, businesses can ensure that their data storage is not contributing to unnecessary power usage. This will help them meet any sustainability goals.

Better data is better AI and better for the planet

Whether using AI-enabled data analysis for predictive maintenance or customer insights, successful AI integration depends on an intelligent data management strategy. AI is nothing without a robust data strategy behind it. This should be a top priority for any business wanting to harness AI.

Mismanaged data must be removed for improved data flows and to ensure organisations are well-equipped from the very start of their AI journeys for the best return on investment. And with cleaner organised data, businesses will benefit from greener data, which contributes to less carbon emissions for more climate value.

Those who neglect the importance of organised data risk falling behind with mismanaged AI solutions that lag, while contributing to unnecessary data waste. For this reason, data strategies that are aware of common challenges are unrivalled. By intelligently adopting data management, business, these leaders will benefit from better AI, highly valuable insights that will support further success, and demonstrable reduction of carbon emissions.