In the age of artificial intelligence (AI), the nature of data has not changed, but how it is delivered and the opportunities it creates for businesses has evolved.
Take Netflix and its impact on Blockbuster as an example. The core product stayed the same, but the way it was accessed and consumed evolved completely, ultimately causing Blockbuster’s decline.
In today’s challenging economic environment, data is a vital resource for businesses dealing with inflation, supply chain disruptions, and other industry pressures. Companies that fail to harness their data effectively are more vulnerable to economic instability. With a strong data strategy, combined with the power of AI, businesses can gain the insight and foresight needed to remain competitive and adapt to market shifts. Those that overlook the value of data or implement AI ineffectively risk facing the same fate as Blockbuster.
Laying the groundwork
Data is just as valuable to a business as any asset on its balance sheet. A company’s worth is not defined by revenue alone, but also by the data it holds and the impact it drives. While every organisation has access to data, its true value is only realised when it is connected, analysed, and used effectively. Data trapped in silos prevents businesses from unlocking its full potential.
A strong data foundation is essential for businesses, serving as the starting point for effective data exploration and analysis. As AI continues to reshape how organisations operate and do business, adopting a modern data platform becomes an essential first step. With this foundation in place, business leaders must then carefully consider the type of AI they wish to implement, ensuring it aligns with their strategic objectives and operational needs. A key first step is exploring enterprise AI, which can enhance various business functions. To enable this, companies need a unified and open data strategy to support the successful deployment of AI models.
Generative AI (GenAI) is highly effective at producing new content based on inputs, often powered by vast data models. However, the sheer volume of data required can strain an organisation’s data infrastructure if it is not equipped to ingest and analyse such large quantities. Despite the excitement surrounding GenAI, businesses should avoid rushing into implementation. Without proper training on all available data, models can produce inaccuracies and hallucinations, ultimately undermining AI investments and prompting leaders to scale back spending.
Businesses should prioritise enterprise AI as their starting point, as it operates on smaller, purpose-driven data sets rather than vast, open-ended models. For example, after establishing a strong data foundation, Zoom developed enterprise-grade AI applications that provide employees with real-time access to the right data, enabling smarter decision-making. Now, anyone in the organisation can interact with data using natural language to gain key insights and boost productivity. Enterprise AI is also more
energy efficient, applying AI where it delivers the most value. While GenAI is set to become more mainstream, the two technologies are not mutually exclusive, and businesses will likely need to incorporate both into their AI strategy.
Fostering the right mindset
Technology is inherently disruptive, designed to drive automation and efficiency within organisations. While this transformation can significantly impact employees, business leaders must address concerns about AI and ease fears of job losses. In reality, research from PwC suggests the opposite—AI is expected to fuel gradual job growth, ensuring businesses can access the talent they need. What will evolve are the skills required rather than the number of jobs available.
Traditional skills are gradually disappearing from job adverts, while new skills are emerging—25% faster in roles impacted by AI automation. Businesses must focus on hiring the right talent, placing individuals in roles where they can build on their existing expertise while also providing opportunities to develop new skills.
A strong organisational culture is essential for successfully implementing technologies like AI. Business leaders must first equip themselves with the necessary education and resources to fully understand the technology. Only then should they focus on educating their workforce on AI’s benefits and the skills required to engage with it. This approach fosters open dialogue between employees and leadership, encouraging discussions on AI’s role and purpose within the company. As a result, businesses can cultivate a greater willingness to embrace AI while carefully evaluating the right tools, policies, and data processes to support its effective use.
Data as a lifeline for business success
In today’s current landscape, many businesses are focused on implementing AI to unlock its benefits. However, while AI is the current goal, it will soon become a stepping stone to the next major innovation that companies strive to embrace. This cycle is familiar across industries as some businesses adapt and thrive while others fail to keep up. To succeed in the AI era, leaders must guide their organisations in the right direction, establishing a solid foundation with a unified data strategy. This will enable them to stand out from the competition and continue delivering value to their customers.
Achieving this requires careful planning, a move away from siloed practices, and a fundamental shift in company culture. By establishing a strong foundation and adopting AI at a measured pace, business leaders can create organisations that are well equipped to thrive in an AI driven future. It is important to remember that AI is only ever as good as the data it is given, which means a solid data foundation forms the bedrock that allows AI to succeed.
About the Author
James Petter is VP, EMEA at Snowflake. Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.
Featured image: Tirachard
