Generative AI beyond the trend: ensuring last year’s investments deliver this year and longer

By James Fisher, Chief Strategy Officer, Qlik.

  • 4 weeks ago Posted in

Last year, companies invested billions in generative AI technology, with early adopters either introducing third-party generative AI into their business or building their own. These investments are forecasted to have such a huge impact that a Goldman Sachs study claims it could raise global GDP by $7 trillion - an almost 7% growth - and boost productivity by 1.5. 

Most businesses will have prioritised education and planning. And, while these Goldman Sach’s forecasted numbers are undoubtedly impressive, to maintain momentum, businesses must move on to the next step: establishing a solid plan around using AI and seeing it through.

As a chief strategy officer, I’m always looking at the big picture and how to get to the implementation step. As part of your growth strategy, you decided to onboard AI – have you considered what comes next? How do we move from hype to reality? 

Here are a few tips. 

Empower your team with AI literacy skills

Sometimes, it is hard to believe we ever lived in a world without AI, much less generative AI. If you want your technology investments to deliver, your employees must be ready to embrace this technology in terms of attitude and skills.

Your team is still your most important asset, and an AI-savvy workforce is key to taking your business to the next level by implementing the technology efficiently and responsibly, making the most of existing operations and coming up with creative ways to implement AI. Therefore, one of the first things you should consider when planning your strategy for the next year is whether your team has the right skills to make the most of the new technology and how to support them. 

Generative AI is powered by data – so take care of it

Like traditional AI, generative AI needs data to function. Before you start relying on AI completely, take a close look at your data and make sure that, as a business, you are also investing in and maintaining robust data quality and governance processes, as well as ensuring data privacy and compliance with regulations. The quality of your data will determine the quality of the outcomes generated by the AI, so it is important to get it right. 

Gaining insights from unstructured data 

In the process of getting your data and data infrastructure ready to feed into the new generative AI systems, one of the biggest hurdles is finding the right way to get insights from your business’ unstructured data. 

The majority (Forrester says 80%) of the world’s data is unstructured. In other words, it is not neatly sorted in rows and columns - an example of this is emails and documents on your intranet. Most organisations have large amounts of untapped data, partly because the spread of generative AI use over the last twelve months has significantly increased the amount of information companies have available about their customers. This unstructured data, which contains precious insights that can be a total game changer, will feed your hungry generative AI with the information it needs to continue growing.

We at Qlik are currently helping many customers solve the challenge of gaining insights from unstructured data. Combining the power of structured and unstructured data will guarantee generative AI momentum throughout the year, as you will ensure that the technology has as much information about your business and clients as possible. 

Shift focus to data in 2024

As a business, you have already done the biggest job: studying the generative AI market, the latest trends and use cases. Perhaps you have also chosen which generative AI application will work best for you. 

The next year should be about shifting from hype to reality yet maintaining the momentum around generative AI and ensuring you make the most of those investments. Three areas which will contribute to this success are an AI-skilled workforce, strong data quality and governance process, and a comprehensive combination of structured and unstructured data. 

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