New research commissioned by Exasol provides a snapshot of the current state of AI implementation in UK, US and Germany. Findings from the 2024 AI and Analytics Report provides clarity on companies’ expectations in terms of data and analytics budgets, data see volumes, headcount implications.
The report documents the AI implementation challenges among other topics, across the retail, healthcare, financial services and telecommunications sectors. Exasol is a high-performance analytics database provider. The report was based on a survey conducted by independent research firm Vanson Bourne.
Key Findings
As organisations prepare to leverage AI, UK companies are expecting the biggest percentage increases in data volumes in the retail and healthcare sectors. As a result, data and analytics budgets in these sectors are also expected to increase significantly over the coming years, with UK firms anticipating bigger percentage increases than US and German firms.
- Retail: UK retail companies expect a 59% rise in data volumes and a 48% rise in data and analytics budgets over the next 2-3 years. This is ahead of the US (35% and 39% respectively) and Germany (35% and 20% respectively).
- Healthcare: Data volumes are anticipated to surge globally across all sectors, with healthcare expected to see the largest increase. In the UK, healthcare data volumes are expected to grow by 93%. This is compared to the anticipated data volume growth of 135% in Germany and 59% in the US. However, UK companies project a 100% increase in their data and analytics budgets over the next 2-3 years. This far exceeds the expected rise of 60% in Germany and 74% in the US.
- Financial Services: UK financial services companies anticipate data volumes will grow by 54%. They also expect data and analytics budgets to rise by only 35%. In contrast, US and German financial services firms expect increases in data and analytics budgets to be broadly in line. Companies expect increases in data volumes: 56% and 55% respectively in the US and 24% and 25% respectively in Germany.
Greater headcount is expected across data and analytics roles
Many analysts have suggested the often-reported view that AI will lead to job losses. However, Exasol’s research shows that headcount in technical roles is expected to increase as a result of the growing importance and integration of AI within organisations. In addition to hiring skilled workers, training and upskilling employees is going to be vitally important as processes and businesses’ operations change.
UK organisations anticipate increases in headcount for modellers, engineers and data scientists in particular.
Implementing AI remains a challenge
However, considerable challenges remain in implementing AI, including regulation and governance, strategy and poor data quality/insufficient volume of data.
- 90% of UK respondents believe AI is one of the most important topics affecting them over the next two years.
- 79% think that those not investing in AI today would put their future business viability at risk.
However, companies face considerable implementation challenges.
- UK companies cited AI regulation and governance (bias, undetected errors, unintended consequences, privacy, security and compliance) (62%).
- A lack of strategy/implementation strategy (43%) and
- Poor data quality/insufficient volume of data (43%) as their top three concerns for adopting AI and machine learning.
When it comes to planning data and analytics initiatives to meet evolving business needs, the main concern for UK companies across sectors, is:
- Dealing with emerging regulations around the use of AI models, including LLM (40%). In contrast, the main concern for US and German companies, across sectors, regarding AI implementation is improving data engineering and data scientist productivity (36% and 45%, respectively).
According to Joerg Tewes, CEO of Exasol, “UK companies’ plans to significantly increase data and analytics budgets across critical sectors. This demonstrate commitment to harnessing AI and leveraging data-driven insights to optimise operations and crucially, to enhance and accelerate decision-making.”
“However, in order to accelerate AI implementation, companies need to evaluate their data analytics stack. This is needed to ensure productivity, speed, and flexibility – all at a reasonable cost,” Tewes adds.
Methodology
The Exasol report surveyed 800 senior decision makers, as well as data scientists/analysts, in both IT and non-IT roles, across organisations in the US (400 decision makers), the UK (200 decision makers), and Germany (200 decision makers) in four key sectors: financial services; healthcare; retail; and telecommunications. Survey respondents came from firms of varying sizes, including 1,000-2,999 employees, 3,000-4,999 employees, and 5,000 or more employees.
Enterprise Times: What this means for businesses
The Exasol report echoes similar themes from other industry bodies. Recently, Celigo published global research which suggests enterprise IT and operations leaders are realising positive results from early AI deployments. Benefits include greater productivity and efficiency, enhanced customer experience and reduced costs. As such, 97% of global enterprise IT and Operations leaders will increase their AI expenditure over the next 18 months.
The interesting key headline from this report is that UK companies plan to increase data and analytics budgets significantly. This is by a greater percentage than in the US and Germany in the retail and healthcare sectors. Needless to say, considerable challenges remain in implementing AI. These barriers to adoption include regulation and governance, strategy and poor data quality/insufficient volume of data.
However, the key lesson to learn for Enterprises looking to adopt AI comes from Exasol CEO, Joerg Tewes. To fully embrace and utilise the potential of AI, enterprises need to evaluate their current data analytics stack. Too many enterprises still have data silos based on internal business structures, as opposed to the customer journey workflow. As Joerg Tewes suggests, this is needed to ensure productivity, speed and flexibility are achieved.
To accelerate AI implementation, companies need to evaluate their data analytics stack. This will ensure productivity, speed, and flexibility—all at a reasonable cost.
The report echoes similar themes from other industry bodies. Recently, Celigo published global research that suggests enterprise IT and operations leaders are realising positive results from early AI deployments. Benefits include greater productivity and efficiency, enhanced customer experience, and reduced costs. As such, 97% of global enterprise IT and Operations leaders will increase their AI expenditure over the next 18 months.
