Unlocking AI’s true potential: the power of a robust data foundation | usagoldmines.com

For businesses, data is their one constant. In the age of AI, data itself has not changed, but how it is delivered, and what companies can do with it has. Think of the arrival of Netflix and its effect on Blockbuster. The core product remained the same, but the way it was delivered and consumed was completely new, and that meant Blockbuster ceased to exist.

Data is becoming a key tool for businesses hoping to weather today’s tough economic climate and overcome common industry challenges, from inflation to supply chain issues. Those who have not yet got to grips with their data are more at risk from economic difficulties, as data, underpinned by a robust data strategy and paired with artificial intelligence (AI), can deliver the insight and foresight needed to remain competitive and manage market fluctuations. Companies that fail to engage with their data or those that implement AI ineffectively may face the same fate as Blockbuster.

Building the foundations

Data is as valuable to a company as any other asset on a balance sheet. Organizations cannot be valued by revenue alone, but also by the data they own and the impact it has on the business. All companies have data at their fingertips, but to turn that into business value, it has to be correlated, analyzed and used correctly. Organizations can’t make the most of their data if it is sitting in siloes.

Businesses must have a strong data foundation in place: this is the jumping-off point for data exploration and analysis. Once organizations have onboarded onto a modern data platform to serve as this foundation, it’s time for leaders to think carefully about what sort of AI they want to use. As a first step, they should consider enterprise AI tools, which can be applied to organizations to enhance various business functions. To enable this, businesses need to build a consolidated and open data strategy to run these AI models.

Generative AI (genAI) excels at creating new content based on inputs, often fueled by huge data models. While it has many uses, the vastness of the data required can result in issues within an organization’s data foundation if they are unable to ingest and analyze such quantities of data. While there is mass excitement around genAI, companies should avoid rushing into implementation, as the models will not be properly trained on all the data available. This can result in inaccuracies and hallucinations, turning AI investments sour and leading business leaders to cut back on spend.

Enterprise AI should instead be the first port of call for businesses, as it is based on smaller data sets, for a certain purpose or benefit as opposed to having potentially infinite uses. For example, since building an enterprise data foundation, Zoom has built enterprise-grade AI applications for everyone within the company, enabling smarter business decisions as teams have access to the right data at the right time.

Now, anyone within the business can chat with their data in natural language to glean key business insights and increase productivity. Enterprise AI is also more energy efficient, using AI for purpose and leveraging the technology where it makes the most sense. While GenAI will see more mainstream use, the two are not mutually exclusive and businesses will likely need to consider both on their AI journey.

The right culture

Technology, by its very nature, is disruptive and aims to drive automation within an organization. This can have a big impact on people, but business leaders need to minimize any uncertainty around AI as much as possible and work to dispel the natural fear that the technology might herald an era of job losses. The latest research from PwC shows that the opposite will happen: AI will bring an era of gradual job growth, helping to ensure there are enough workers so that organizations can find the people they need. What will change are the skills required by workers.

Traditional skills are already disappearing from job adverts, and new skills are appearing, with this change happening 25% faster in roles where AI automation is having an impact. Businesses need to consider the right people for the job and hire them into roles where they can develop their existing skills while giving them learning opportunities to gain new skills.

Culture is hugely important when it comes to implementing technologies such as AI. Business leaders need to first ensure they have access to education and resources so they can get to grips with the technology themselves. Then and only then should they aim to educate their workforce on the benefits of the technology and the skills they will need to engage with it.

This will help establish an open dialogue for employees and leaders to discuss AI use within a company and its purpose, resulting in an increased appetite for engaging with the technology. Businesses can then assess the right tools, policies and data processes and how they will use AI.

Data and survival

Today, the goal for many businesses is to implement AI and reap its rewards. While AI is the current destination, it’ll become a stepping stone to the next destination that all companies are vying to reach. This is a cycle all industries go through, some organizations survive, and some don’t. To be one of the companies that thrive in the age of AI, leaders need to steer their organizations in the right direction, and ensure there is a strong foundation in place to support a consolidated data strategy, enabling them to differentiate themselves from the competition and deliver for customers.

Doing so requires careful planning, and a shift away from siloed approaches, as well as a step change in company culture. By building this foundation, and avoiding the pitfalls of adopting AI too rapidly, business leaders can build companies fit to grow into an AI-powered future.

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