Initial report finds that nearly three in four decision makers believe not investing in AI will put business survival at risk, but declining data quality, regulatory complexity and integration are key to success. It has become clear that this is a barrier to
Senior decision makers recognize that AI is critical to business survival, but regulatory and technical challenges continue to loom despite increasing stakeholder pressure to rapidly deploy the technology. Performance analytics database provider is slowing down the process, according to a new report from our friends at Exasol. Exasol's 2024 AI and Analytics Report explores the current state of AI adoption, key challenges for data analytics, and the future for executives in light of data explosion and adoption of emerging technologies .
Exasol partnered with independent research firm Vanson Bourne to conduct a survey of 800 senior decision makers, data scientists and analysts in the US, UK and Germany to understand how companies approach data and analytics. We evaluated the biggest issues and their current status. We have plans to address these challenges in the short term (within two years).
Key findings include:
Decision makers and technology analysts believe that businesses will fail if they don't invest in AI now, but significant barriers to widespread adoption remain.
Nearly all (91%) respondents agree that AI will be one of the most important topics for their organizations over the next two years, and a whopping 72% believe that not investing in AI now will affect their future business. It acknowledges that its survival is at risk. Stakeholder pressure is also driving increased adoption of AI, with 45% saying they are under increasing pressure from stakeholders to adopt the technology. The most commonly cited reason for believing AI is important is creating new business or revenue streams (50%). Change employee roles and responsibilities (47%). Accelerating competitiveness in the market (46%); automating processes (43%).
But despite understanding how important this technology is to their future success, there are barriers to its seamless implementation, with nine in 10 (88%) citing evolving bureaucratic requirements. and that regulations for AI need to be made clearer. and lack of implementation strategy (44%). Poor data quality and insufficient amount of data (43%). Integration with existing systems (38%) is hindering widespread adoption of AI. With more than a third (38%) of companies planning to increase their AI infrastructure in the next few years, organizations need to find ways to overcome these obstacles.
Latency continues to hinder organizations’ data analytics and AI efforts
Organizations are struggling to make progress on data analytics and AI projects, with a whopping 78% of decision makers reporting gaps in at least one area of data science and machine learning (ML) models. Almost half (47%) cite the speed of implementing new data requirements as a challenge.
Even though most (96%) use BI acceleration engines to speed up queries directly within their tools, an astonishing 69% of BI users continue to struggle with poor report performance. I admit it. Additionally, 79% claim that it takes too much time for data teams to implement new business analytics requirements. This means that latency continues to hinder an organization's ability to innovate, data analytics projects, and the potential of AI.
Given the increasing volume of data and the acceleration of AI, the role of the chief data officer will evolve to become more integrated, impactful, and challenging.
The role of the chief data officer (CDO) will evolve with the integration of AI, including infrastructure development, AI-driven automation, and AI-driven insights. In fact, more than half (52%) of respondents believe that the CDO role needs to work more closely with other C-suite members, and 44% believe that the CDO role should work more closely with other C-suite members, while 44% believe that the CDO role should work more closely with other C-suite members, and 44% believe that CDOs should We believe the role will be integrated with the Chief AI Officer. concentration.
When it comes to forecasting business operations, 90% of companies expect to increase investment in headcount and budget over the next two years to support anticipated data growth. Roles expected to grow the most during this period include BI/analytics developers and engineers (both 48%). Data Analyst (46%); Data Architect/Modeler (45%). Despite the anticipated increase in workforce numbers, 47% of survey respondents reported that they are concerned that Generative AI will threaten their roles.
“AI has become essential to business success, but its effectiveness is determined by the tools, technology, and talent that power it on the back end. Our research highlights the differences between current BI tools and their deliverables. “More tools don't necessarily mean faster performance or better insights,” said Joerg Tewes, CEO of Exasol. . “As CDOs prepare for greater complexity and are tasked with doing more with less, they are evaluating their data analytics stack to ensure productivity, speed, and flexibility, all at a reasonable cost. need to do it.”
For more information, download the full 2024 AI and Analytics Report here.
methodology
Exasol commissioned independent market research firm Vanson Bourne to conduct a data, analytics and AI study. The study surveyed 800 senior IT and non-IT decision makers and data scientists/analysts in November 2023. Respondents were from the US, UK, and Germany, and all had some responsibility or knowledge of their organization's data. Scientific and analytical strategies or programs.
Respondents were from organizations with 1,000 or more employees across sectors such as financial services, healthcare (public and private), retail, and telecommunications. All interviews were conducted using a rigorous multi-level screening process to ensure that only suitable candidates were given the opportunity to participate.
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