The inaugural report reveals that nearly three in four decision-makers believe that not investing in AI would put the viability of the business at risk. Yet poor data quality, regulatory complexity, and integration create barriers to success.
Senior decision-makers know that AI is essential to the viability of their business. Yet despite growing pressure from stakeholders to implement the technology quickly, regulatory and technological challenges are slowing the process, according to a new report from our friends at Exasol, the provider of high-performance analytical databases. Exasol 2024 »AI and Analytics Report» explores the current state of AI implementation, key data analytics challenges, and the future of the C-suite given the explosive growth of data and adoption of emerging technologies.
In partnership with Vanson Bourne, an independent research firm, Exasol surveyed 800 senior decision-makers as well as data scientists and analysts in the US, UK and Germany to evaluate data and analytics initiatives companies, including their main challenges and their performance. plan to address these challenges in the short term (within two years).
Key findings include:
Policymakers and technical analysts believe that failing to invest in AI today will cause businesses to fail, but there are still significant barriers to broader implementation.
Almost all respondents (91%) agree that AI is one of the most important topics for organizations over the next two years, with a whopping 72% admitting that not investing in AI today will jeopardize the future viability of the company. Stakeholder pressure is also a factor in increased adoption of AI, with 45% saying they are experiencing increased pressure from stakeholders to adopt the technology. The most cited reasons for believing in the importance of AI include creating new businesses or revenue streams (50%); changing workforce roles and responsibilities (47%); acceleration of competitiveness in the market (46%); and process automation (43%).
However, while there is an understanding of how critical technology is to future success, there are barriers to its seamless implementation, with nearly nine in ten (88%) saying that changing bureaucratic requirements and AI regulations require more clarity. In addition, lack of implementation strategy (44%); poor data quality and insufficient data volume (43%); and integration with existing systems (38%) hinder widespread adoption of AI. Organizations need to find ways to overcome these obstacles, as more than a third (38%) of companies plan to increase their AI infrastructure in the coming years.
Latency Continues to Hinder Organizations’ Data Analytics and AI Initiatives
Organizations are struggling to advance their data analytics and AI projects, with a staggering 78% of decision-makers reporting gaps in at least one area of their data science and machine learning models ( ML). Nearly half (47%) cite the speed of implementing new data requirements as a challenge.
Although most (96%) use BI acceleration engines to speed up queries directly in their tools, an astonishing 69% of BI users admit that they continue to struggle with slow reporting performance. Another 79% say new business analytics requirements are taking too long for their data teams to implement, meaning latency continues to hinder organizations’ innovation capabilities, data projects data analysis and its AI potential.
Given the increase in data volumes and the acceleration of AI, the role of the Chief Data Officer will evolve to become more integrated, more impactful and more challenging.
The role of the Chief Data Officer (CDO) will evolve in response to the integration of AI, including infrastructure development, AI-driven automation, and AI-driven insights. In fact, more than half (52%) of respondents believe the CDO role will need to work more closely with other members of senior management, and 44% believe it will merge with the Chief AI Officer as questions ethics and compliance remain an issue. to focus.
In terms of forecasting business operations, 90% of companies believe they will increase their headcount and/or budget investments over the next two years to support expected data growth. The roles expected to increase the most over this period include developers and BI/analytics engineers (both 48%); data analysts (46%); and data architects/modelers (45%). Despite the expected increase in headcount, 47% of respondents fear that generative AI threatens their role.
“AI has become essential to business success, but its effectiveness depends on the tools, technology and people powering it on the back end. Our study further proves that there is a significant gap between current BI tools and their results: more tools do not necessarily mean faster performance or better insights,” said Joerg Tewes, CEO of Exasol. “As CDOs prepare for increased complexity and are tasked with doing more with less, they must evaluate the data analytics stack to ensure productivity, speed and flexibility, all at a reasonable cost. »
For more information, please download the full “2024 AI and Analytics Report”. HERE.
Methodology
Exasol commissioned independent market research agency Vanson Bourne to conduct research on data, analytics and AI. The study surveyed 800 senior decision-makers in IT and non-IT roles, as well as 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 strategy or program.
Respondents came from organizations with 1,000 or more employees, in the following industries: financial services, healthcare (public and private), retail and telecommunications. All interviews were conducted using a rigorous, multi-tiered selection process to ensure that only suitable candidates had the opportunity to participate.
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