The gap between businesses' AI strategies and execution arises from the difficulty in effectively harnessing data, such that reliable, trustworthy data support more effective business decisions and empower users with information to drive business outcomes.

A report by technology market research and intelligence firm the International Data Corporation showed that 89% of companies had an AI strategy and that there was no shortage of ambition; however, only 26% of these companies were deploying at scale, said data management and analytics services company Qlik head of AI practice Kyle Jourdan on September 9.

Speaking during the company's tour of countries it operates in, Qlik Middle East and Africa senior VP and GM Tejas Mehta said the message in 2024 that the success of AI applications depended on the data foundations that organisations used, remained true today.

“[Generative AI, or genAI] has exploded in the year since then, and business units are no longer asking about where to use AI, but how to do so responsibly and how to achieve a measurable impact,” he said.

This change had made the importance of leaders' roles in shaping their organisations' data more critical.

Successfully deploying AI systems at scale in an organisation required that companies bridge the gap between strategy and execution, embed the AI solutions where decisions were being made and empowered their teams with tools that they trusted and used to act quickly and confidently, he said.

Many of the challenges Qlik has heard reported by organisations that did not successfully adopt AI solutions are because there has been a lack trust in and governance of data.

The governance and quality of data products was important as high-quality data was needed to feed into AI use-cases that would consume the right information to provide the right answers, said Jourdan.

“All businesses struggle to realise value from their AI strategy and to implement AI solutions effectively and at scale.

“The challenge is not for businesses to have an AI strategy or plan, but how to get these systems into the hands of people to use in their daily roles to take the right action at the right time,” he said.

However, action alone was insufficient without confidence in the outcomes of these solutions from the data, such that users were sure they could trust the answer provided and then take action based on this information, he emphasised.

“Companies and processes cannot move fast if there is no trust in their data.”

Qlik's analytics experience provided it with an advantage as it was able to place AI solutions on top of companies' data to make it trustworthy and provide reliable answers from the solutions, Jourdan said.

Additionally, embedding these solutions in all parts of the business to place them into the hands of all users wis important to boost access to and use of these solutions to drive business outcomes.

“Trust, efficiency and easy, natural experiences are how companies can turn data into business value,” he said.

During a later demonstration of Qlik's products, Qlik principal solution architect Walid Wehbi used natural language queries to undertake work for three different typical business roles.

He highlighted that the users of these AI solutions could also view the sources from which the answers provided by the solution were derived.

Additionally, he emphasised that the Qlik AI solutions would not hallucinate because they used only a business's own data, and instead escalated a query to superiors in the organisation if a solution could not provide an answer to the query.

“People can rely on the answers, as the solution shows where it sourced the answers from and users can validate the answers from the data,” said Jourdan.