Play the long game in AI

As a global leader in data integration, analytics, and artificial intelligence (AI), Qlik understands that embracing AI is essential for businesses to thrive. Much like the transformative impact of the internet, AI promises to reshape industries in ways we can’t fully anticipate yet. While most organisations are still in the early stages of their AI journey, the luxury of waiting is not an option.

A key reminder is that unstructured data is an untapped treasure: to generate relevant and accurate insights, AI models require the right contextual data. For this reason, businesses need to develop a flexible, robust data ecosystem – one that supports their needs without locking them into a single platform.

To truly succeed with AI, companies must play the long game. There is no one-size-fits-all solution, and sustained effort is required to ensure long-term success and business continuity.

This can be simplified as follows:

Diversify your path: My advice is to avoid putting all your eggs in one basket. Explore a variety of functions, models, and use cases. Focus on key areas to build tailored, effective solutions, and be cautious of the ‘use-case trap’ – limiting functionality to only narrow applications. It’s also important to recognize that generative AI is not a one-size-fits-all solution. Just as the left and right brain complement each other in humans, traditional AI and generative AI can work together, each bringing unique value to the table.

Walk before you can run: According to the six principles of AI-ready data, your data should be diverse, consumable, discoverable, timely, accurate and secure. Therefore, it’s prudent to remember that smaller models can also deliver fast value with less risk and complexity. Your choice of models, and their deployment, is important. Take advantage of AI in your existing applications.

Don’t skip steps: Establishing a responsible AI framework is crucial. This means defining clear steps and parameters for AI policies and data governance, as well as outlining the roles and responsibilities for governance committees and ensuring proper oversight of vendors. Taking these foundational steps will help safeguard the ethical use of AI and ensure compliance.

The AI reality today

When organisations consider how they can derive real value from AI, we see from a number of different sources that it’s still early days in the AI journey for most businesses, as mentioned previously, and this is confirmed by the following statistics:

• Formalised AI strategy: Only 25 percent of organisations have a formalised AI strategy (according to a 2024 Qlik study).
• Realising value with generative AI: Between 18 percent and 36 percent of organisations are achieving benefits to a ‘large’ or ‘very large’ extent (source: Deloitte, May 2024).
• Having an AI-skilled workforce: Here, around one-third of companies (35 percent) believe that they have the AI skills needed in their enterprise to be successful (source: Ventana Research, February 2024).
• Implementing AI responsibly: Only nine percent of businesses feel that they are ‘very prepared’ to implement generative AI in a responsible manner (source: McKinsey, March 2024).
• Scaling generative AI: Just 10 percent of organisations are scaling one or more generative AI applications across functions or across the enterprise (source: BCG, February 2024).

Your business’s data must be available in real time, or as near as possible, to support your environment. It must be trusted and able to be run at scale wherever you need it to go.

As we think about preparing data for analytics and use cases, and also improving the quality of the data itself, we need to break down silos that may exist within the organisation. Siloes lead to errors and the possibility of getting different results from the same data.

Qlik can support companies by first assisting them with their data to become AI-ready, and thereafter maximising their AI usage going forward. With trusted, real-time data at the foundation, and a commitment to continuous improvement, businesses will be well-positioned to derive lasting value from AI, now and in the future.