By: Kirsty Biddscombe, EMEA Business Lead AI, ML & Data Analytics at NetApp
Artificial intelligence has been dominating headlines, boardrooms and political agendas alike, and is transforming our personal and working lives. With the UK ambitious to become a global leader in AI (encouraged with a recently announced investment of £100m) it’s unsurprising to see UK businesses are keen to invest in the technology too. But how are organisations really faring on the road to AI adoption?
IT leaders are certainly preparing to embrace AI and its many benefits. New research from NetApp found that 59% of businesses plan to increase their investments in AI projects this year alone. At a time when we’re seeing the highest level of insolvencies since 1996, companies are looking to maximise any and all investment. AI is no exception, and many organisations are turning to these tools to increase productivity and achieve more with less.
Yet even with growing investments in AI, 69% of businesses admit their company is poorly prepared to properly implement this technology. As a result, businesses risk missing out on the potential of artificial intelligence by tripping on the first few hurdles – strategy and implementation.
A lag in learning
With only a fifth of businesses holding a strong understanding of how to harness AI, it’s clear that many organisations are trying to run before they can walk. In fact, a lack of long-term strategy, and clearly defined use-cases, mean that businesses are risking losing out on the targeted benefits AI could bring according to their business’ needs.
Just as information fuels AI, allowing tools to learn, businesses must gather as much information as possible on various AI tools, to implement an effective AI strategy to ensure both near future and long-term success. Without solid foundations in place, AI projects could fail in the long term, risking customer credibility, and wasting the financial investments made.
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Data is the fuel
If AI is a state-of-the-art engine giving an old car a new lease of life, then data is the fuel that can enable breakthrough speeds. Advanced solutions rely on the data that they draw on. Without a solid data strategy to underpin AI projects, businesses will struggle to deliver a successful solution. High quality, clean, real-time data with appropriate security controls is necessary for the most actionable and valuable insights. Because the cleaner the fuel, the more efficient and effective an engine will be in the short and long term.
Considered, organised, and consistent data is a must when data management and analysis tools are the most popular solutions chosen by businesses. Yet, much of the data being collected by organisations today is siloed, and unconnected, which makes it difficult to create successful AI solutions. With data being stored in various places, and being collected from multiple sources, it’s understandably difficult for firms to tackle deep rooted data silos. But without organised and up-to-date data, firms cannot gather the valuable insights they need for their business operations and strategy. And without data management foundations in place, manageable, secure, accessible and cyber-resilient information won’t be available for AI models.
This is something that relatively few UK IT leaders are aware of, in fact a fifth (19%) think that their company must first consolidate unstructured data before embarking on an AI journey. It does start with understanding data landscapes, and how much work is needed to clean the data behind a firm for a business to begin an AI strategy that has longevity.
Once this plan is in place, firms can focus on preparing to address the challenges that come with managing vast quantities of data to fuel AI solutions. A robust strategy that collects, prepares and stores data to fully harness AI solutions is critical to the success of the AI technologies adopted.
Effective AI needs organised data
AI will undoubtedly be a helping hand for firms looking to boost their productivity, effectiveness and efficiency. But the only way to gain a long-term competitive advantage will be contingent on the data fueling AI models.
If businesses want to get the most out of their AI, they need to start with getting the most out of their data. Jumping into the promises of AI’s potential without a clear data management strategy, risks AI solutions that lack effectiveness. Firms with mismanaged data will find they fall at common challenges, whereas those that plan ahead will benefit from high-powered AI performance. With intelligent, considered AI adoption, businesses will benefit from unrivalled insights that support their goals and ambitions.
