Qlik: Over Two-Thirds of Singapore’s Businesses Scaling Back AI Investment Due to Trust Issues

Qlik®, a global leader in data integration, analytics and Artificial Intelligence (AI), recently launched research of 4,200 C-Suite executives and AI decision-makers worldwide, revealing what is hindering AI progress globally and how to overcome these barriers. Data governance issues, insufficient resources, and a lack of AI skills hinder successful AI deployment worldwide, causing many projects to get stuck in the planning stages.

AI Projects Are Stuck in Planning—or Getting Scrapped

The importance of AI in achieving organisational success is not underestimated, with Qlik’s research finding that almost all (90%) of Singapore’s senior decision-makers believe AI is absolutely essential or very important to achieving success—including reaching strategic goals and increasing profits.

Despite this recognition, only some AI projects make it out of the planning stage to completion or implementation, with many scrapped before completion. In fact, 34% of Singaporean businesses have over 50 AI projects in the scoping or planning stages, which are not yet live projects—higher than the global average of 11%. And 11% have also had more than 50 projects progress to planning or beyond, only to pause or cancel them entirely, with the global average sitting at 8%.

Progressing more AI projects from planning to successful deployment will be vital for organisations to see a return on investment made into the technology and to better serve customers against competition.

Given the struggle to bring AI projects to fruition, many AI decision makers (79%) see the value in ‘ready-made’ AI solutions as a good foundation to enhance AI development. However, in Singapore, more than two thirds (72%) of AI projects are being developed internally, and most (67%) of the C-Suite executives on the island agree that these are better than ready-made solutions.

Lack of Skills, Data Governance, Budget, and Trust Are the Culprits—Qlik

Singapore faces the same challenges as the rest of the world when rolling-out AI projects. The most significant are data governance challenges (26%), budget constraints (28%), and a lack of trusted data for AI to work with (26%). A lack of skills to develop and deploy AI (19%) and roll-out AI once it is developed (23%) also slows AI adoption on the island.

While there is an overwhelming level of understanding around the need for AI, with almost all respondents worldwide (95%) saying they know what types of AI could be used in their business, trust from elsewhere in the business appears to be holding some companies back.

Over a third (37%) of AI decision makers globally say their senior managers lack trust in AI, and 42% feel less senior employees do not trust the technology. A fifth (21%) believe their customers do not trust AI either.

Worryingly, 61% say this lack of trust significantly reduces AI investment in their business. This sentiment is higher among businesses in Singapore, at 74%.

Better knowledge sharing across a business and its customers can help to increase that trust and subsequent investment, with 74% of respondents looking to promote the benefits of the technology more within their organisation and to their customers.

Building Trust Is Paramount to Advancing AI Implementation Globally

Providing AI training to upskill the workforce is another way to build trust and ensure AI projects go beyond planning and into successful deployment.

Globally, 65% of AI decision makers believe their country has the potential to lead the world in AI skills in the next five years. Singapore is slightly more optimistic about its potential, with 75% of C-Suite leaders believing the country can become an AI leader. To achieve this, 75% of respondents from Singapore believe their industries need to be better at nurturing and upskilling staff for AI, and 78% think the government needs to provide more funding and training in AI.

“Business leaders know the value of AI, but they face a multitude of barriers that prevent them from moving from proof of concept to value creating deployment of the technology. The first step to creating an AI strategy is to identify a clear use case, with defined goals and measures of success, and use this to identify the skills, resources and data needed to support it at scale. In doing so, you start to build trust and win management buy-in to help you succeed,” said James Fisher, Chief Strategy Officer at Qlik.

Learn more about how Qlik is supporting customers to get their AI solutions off the ground, including the use of Qlik Answers, the self-service AI solution with the power of GenAI here: https://www.qlik.com/us/products/qlik-answers.